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Mint Mobile Review after 3 Weeks

Original Post got moved for having a referral link, dropping the text of the review sans referral link here. Hope anyone considering mint mobile finds it helpful.
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Most people don’t question a hefty Verizon Wireless bill. The coverage and network quality have been industry bests for years and so the “You Get What You Pay For” mantra kept my family entrenched for 13 years. Verizon recently provided semi-deceptive sales tactics and indifferent customer service prompting an exploration of the options. Not surprisingly cheaper plans abound, so the question is…do other service providers provide ‘good enough’ quality to go along with their too-good-to-be-true price points.
Verizon did eventually make things right, but not until after hours on customer service chats and phone calls getting bounced between numerous Verizon associates. So like a slow rolling boulder loosened from it’s centuries-old resting place, my complacency had given way to a momentum pulling me from the “Can you hear me Now” network.
So where does one start if contemplating a change from the biggest, arguably best and most expensive cellular service? First let’s discuss key industry dynamics.
Second, each company has their own distinct features. The importance of each differs on one’s personal preferences.
Lastly, let’s not forget Cost. After considering features and soliciting friends’ opinions about T-Mobile’s network (which weren’t great by the way), I found a plan that was too inexpensive not to try. Mint Mobile is an MVNO that piggybacks on the T-Mobile network. I’m trying their 3-month trial plan that provides unlimited talk/text and 3GB of 4G/5G data per month for $15/mo. They offer Wifi Calling, options to purchase International Prepaid Credits and had the cheapest plan I found along with many online reviewers calling them a top MVNO.
I don’t want anyone unhappy from something I recommend, so below are pros & cons to review before considering a switch. If you’d like to try it out, you can save $15 off their three month trial, which costs $45 paid in full ($15/mo) for the 3GB data plan before the $15 credit. If you need more data there are other offerings; $60 ($20/mo) for 8GB, $75 for 12GB and $90 ($30/mo) for the Unlimited data plan. I’ve also only been using their network for 3 weeks now, so your results may vary, but since the plans are cheap and you can bring your current phone, there is little financial risk to trying them out as long as you aren’t currently on a contract.
PROS

CONS

OTHER SERVICES CONSIDERED

DATA SAVING TECHNIQUES TO REDUCE YOUR BILL

PARTING THOUGHTS

I’m happy with Mint Mobile’s service after 3 weeks. If you live in a big town or city, it may be a really good fit to save money. I wish I would have called their customer service when I initially had setup issues, rather than trying to figure it out myself. You should bring a phone and Mint Mobile doesn’t offer cell phone discounts but does appear to offer payment plans. If you need a new phone and don’t want to break the bank, you can’t go wrong with the Pixel 4a or Pixel 4a 5G coming out soon. And now that I’ve made the switch I don’t anticipate going back and spending more, but we’ll see if there are gotchas waiting in the wings.
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[Table] I’m Dr. Samantha Joel. My team and I use AI to predict the relationship satisfaction of 11,000 couples - AMA!

Source
Clarification from the researcher regarding the title:
... The decision to put "AI" in the title was made by the media team in order to shorten the title. Although it's technically correct ... "Machine learning" is a more accurate descriptor.
Questions Answers
Hi! Thanks for doing this AMA. What would you say is the biggest takeaway for a couple based on the results of your study? And is there anything a single person should take from it while looking for a partner? If I'm understanding it correctly, it looks like a lot of the factors that lead to success are things it might not be easy to evaluate until you've actually been in a relationship with someone for a bit. Thank you! I think the biggest takeaway, to paraphrase my old friend and colleague Geoff MacDonald, is that the person you choose may not be as important as the relationship you build. As a culture, we put so much emphasis on choosing the right person. These results suggest that it’s really more important to be the right person. To create the conditions that will allow a relationship to flourish.
In terms of your point about evaluations, this is something I’ve spent a lot of time thinking about myself. Can a relationship be objectively evaluated—are some partnerships inherently better than others--and if so, when do these objective criteria first come online? This is somewhere my students and I would really like to take our research next. We want to recruit couples in brand new relationships and study how they evaluate each other for compatibility and fit, and how those evaluations change as the relationship develops.
We were supposed to launch the study in March, but it got stalled due to COVID. Hopefully soon we’ll be able to open the lab up again, and I’ll have some more concrete answers for you.
Did any of your couples include arranged marriages? I ask this because my husband and I both come from cultures with a high degree of parental/community involvement in matchmaking. Without even planning to do so, we did effectively the same thing to ourselves. I told him on our first date (set up by our friend community) that I was only interested in someone who was serious about marriage/kids and he agreed. We operated under the idea that we would do our best to build a healthy relationship that would end in marriage and I think that mindset is key to us having such a happy, healthy, and satisfied relationship now. I would be curious to see if other couples who were in either arranged marriages (willfully) or had a very strong marriage goal early on had the same results as couples who did not. Not to my knowledge. Our data were from Canada, the US, the Netherlands, New Zealand, Israel, and Switzerland. Very Western-centric, as you can see, so they don't lend themselves well to cross-cultural research questions.
Arranged marriages have always intrigued me, and a long-term research goal of mine is to prospectively follow people in arranged marriages and compare their trajectories to the trajectories of self-selected marriages.
The existing literature that I know of on arranged marriage--and it's not a very large literature-- has produced pretty mixed findings. Some studies have compared people in arranged vs. self-selected marriages and found no differences in relationship quality. Some have found higher quality for the self-selected marriages. Some studies have shown different results depending on which marital quality measure you use, or on how you define "arranged". So it's very much a topic in need of further research.
As a single person looking for a long-term relationship partner....do the results of this study mean I could be happy with literally anybody? Aren't there some people who would be more likely to appreciate me and act in ways that show me they're committed to our relationship? (and vice versa) That’s really hard to say. One of the limitations of the project is self-selection – we only looked at couples who are already together. We didn’t, say, pair people at random. If we had, we might have found much stronger partner effects. So, there may very well be plenty of people who you wouldn’t match well with, but those people are selected out by the time you enroll in our study.
What the results do suggest is that by the time you’re in a sufficiently established partnership to enroll in a research study together, your partner’s traits aren’t very important anymore.
Really, we need a lot more research on the early relationship stages—how do these relationship dynamics form in the first place?—to produce a satisfying answer to your question.
Have you found that the partnerships need to have a similar understanding of what the commitment translates to? For example, putting equal effort into maintaining the home, or equal involvement with children. Do any of the studies collect information to confirm or deny the reliability of zodiac sign (eastern and western) compatibility? For participants who had a “type” they were attracted to while dating, did their significant other match that description? This is one of the more interesting aspects of the findings, IMO – we did not find any evidence for any kind of partner matching predicting relationship quality.
The algorithm we were using detects interactions. So if my traits and preferences match with your traits and preferences to predict relationship quality, we should have picked up on that. For example, if Andrea says she likes extraverted guys, and she’s happy with Tom because he’s an extraverted guy, we should have found that putting Andrea’s desired extraversion and Tom’s own extraversion into the same model would have predicted more variance than either on its own. But that’s not what happens. Combining both partner’s variables didn’t predict more variance than just one partner’s variables. So that goes against the idea of matching, similarity, having a type, etc. If there was any matching going on, it didn’t predict how happy people were with their partners.
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Very thought provoking. Have you been able to find evidence that predicts the relationship quality? And thank you for doing this AMA! Relationship-specific variables did a great job of predicting relationship quality. Your own perceptions of the relationship--such as your own sexual satisfaction, how much conflict you think there is in the relationship, and how committed you think your partner is--predicted 45% of the variance in your own relationship quality, at the beginning of the study. These same variables also predicted 18% of relationship satisfaction at the end of the study.
And in fact, no other variables added to that total variance explained. Not your traits, not your partner’s traits, and not your partner’s perceptions of the relationship. All of the effects were driven by own judgments about the relationship.
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So, basically, if one is in a relationship and they are making the point to perceive themselves as in a happy relationship, they will be. How much does it matter to the success of the relationship if one perceives themselves positively but the other does not? That’s a great question. My team and I were surprised that the partner’s perceptions of the relationship predicted so much less variance than own perceptions. Own perceptions of the relationship predicted 45% of the variance in relationship quality, but the partner’s perceptions (measured with the exact same variables!) predicted only 15%.
That difference suggests that there’s a pretty big discrepancy in those ratings--how you perceive the relationship is not necessarily how your partner perceives it. It’s not clear at this point what the implications of those discrepancies are, or where they come from, but that would be a great topic for future research. How can two people be in the same relationship, and disagree so much about what it’s like?
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I'm an extrovert and I've been intensely unhappy dating introverts. So this seems to go against my own experiences, because there's not enough in common between us to keep a relationship going, and I don't feel that they care about me enough to compromise (e.g. they agree to attend game night with me once a month vs weekly). I think this really highlights that self-selection problem I mentioned—your relationships with introverts may not last long enough to be included in a study like this, which means those data are not part of the results. That’s why I really want to see more data on fledging relationships. I’d love to enroll you in a study at the point when you have just started dating an introvert, and ask you about your experiences over those few ephemeral weeks or months that the relationship lasts before it fizzles out. Those sorts of data are so difficult to collect but I think they’re a really important piece of the puzzle.
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Well I've been with my introverted husband for nine years. We've decided just recently that separation is probably the best course of action in the future (neither of us want to make such a large decision right now, in the midst of the world being on pause and both of us being depressed about it). I'm really sorry to hear that, Transplanted_Cactus.
Why do you think that it's so difficult to predict which relationships will work out well, and which won't? (whether using AI or not) Thanks for doing the AMA! That’s a great question. I think when it comes to relationship quality and longevity, there are a lot of chaotic processes at work that make long-term prediction difficult. Stressors and life events that come up, idiosyncratic experiences that you might happen to have with your partner, other people who may enter or exit your life and who give you different perspectives and ways of thinking about the partnership, etc.
So we can predict the aspects of the relationship that are stable, but they also change over time in unpredictable ways. I think that’s because the changes are largely driven by these kinds of environmental and contextual factors that are very difficult to measure, let alone predict.
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Dr. John Gottman has been able to predict divorce with 94% accuracy. Check him out, his books are fantastic! I can't speak to Gottman's books, which I'm sure are fantastic. But, from what I can tell, his claim that he can predict divorce with 94% accuracy comes from this study of 52 couples, published in 1992: https://search-proquest-com.proxy1.lib.uwo.ca/docview/614305792?accountid=15115
13.5% of the sample had divorced over a three-year period, or 7 couples. After the data were already in hand, the researchers used a discriminant function analysis with nine predictors to predict which couples divorced, with 93.6% accuracy.
This model suffers from a statistical problem called overfitting. With a small sample size, and a technique that doesn't use any kind of cross-validation, you can essentially keep adding predictors until you explain close to 100% of the variance. We call that a saturated model. Almost all the variance has technically been "explained", but only for the very specific sample that the model was built on. If I went and recruited 52 new couples, and applied this exact same model to those data, the accuracy would likely be much less - likely closer to 86.5% (which is the baseline here - you get 86.5% accuracy if you simply predict that no one gets divorced).
Tldr Although I have lots of respect for Gottman, I am incredibly dubious of that 94% claim.
Thanks for doing this Dr. Joel! Very interesting research. What made you think machine learning would be a good way to study the success of romantic relationships? Well, traditional statistical methods that we use in this field—like regression and multilevel modelling--are really great for delving into the mechanisms or inner workings of a handful of variables. But, they aren’t very good at dealing with a large number of variables at once.
The major advantage of machine learning is that it can handle a very large number of predictors, and tell you which ones are really driving prediction, as well as how well they are performing as a group. So, the goal of the project was to take all of the many many variables that have already been examined in separate studies, and make them directly compete for that variance. Which of these hundreds of measures are most important, and when taken as a whole, how well do they perform?
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Really interesting work and I really appreciate the approachable explanations. Out of curiosity, what kind of machine learning are you using? How many features are you starting with and how are those coded? We conducted the analyses with Random Forests, using the randomForests package in R. Each dataset was collected by a different team of researchers and therefore had different predictors - typically ~50 variables per dataset, which we manually coded into either features of the self or features of the relationship. We also used the VSURF package to initially pair down the number of predictors in each model.
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Got it thank you! Why did you choose random forests? Key advantages: it can handle a very large number of predictors at once, it's able to capture non-linear effects and interactions, and its use of out-of-bag sampling helps to minimize overfitting issues.
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Just for clarity, these aren't advantages that are unique to random forests at all. Instead, with a dataset like yours, any choice of standard classical classifier should have performed similarly. The random forest is nice because it lends itself to interpretability of feature importance through the GINI coefficient, and doesnt require a separate feature selector. I'm wondering why you called it AI in the post though? In the machine learning community, we wouldnt call this AI. I'm not sure if you're aware, but the public perception that this kind of thing is AI has been harmful to our field. Our dependent measure was continuous, so this was random forests built on regression trees, rather than classification trees. But yes - plenty of other ML methods likely would have done a fine job.
The decision to put "AI" in the title was made by the media team in order to shorten the title. Although it's technically correct, I do agree with you that it's a stretch. "Machine learning" is a more accurate descriptor.
Do these factors change in order of importance with age? Is there any set of factors that predicts divorce? In fact, age was one of the only demographic variables that performed well in our models. Age contributed to 68% of the models we tested. Now, machine learning is pretty black boxy, so we can’t tell you exactly what age is doing in these models. But it’s quite possible that it’s a moderator of a lot of the other variables—that different variables are important for relationship quality depending on your age.
We did not try to predict divorce or breakups in these models. Other papers have done that though, although not with machine learning. Karney & Bradbury 1995 (https://psycnet.apa.org/buy/1995-36558-001 ) is, I believe, still the most comprehensive paper to date on the predictors of divorce. Le et al 2010 (https://onlinelibrary.wiley.com/doi/full/10.1111/j.1475-6811.2010.01285.x?casa_token=pSw5wWgnZSYAAAAA%3ANGeIEDkDNcUmWWi4XiZN1gXDX4F8zMGP98V_O7sWkaW-Z8N0XZ0IuoJNoaSWAwHlZstwN_18X99JT8WQ) is the best paper on predictors of breakups.
Top predictors of divorce and breakups tend to be global evaluations of the relationship. Variables like how satisfied you are in the relationship, and how committed you are to the relationship. That’s part of why we focused on these outcome variables in our project.
Hello, Very interesting findings! What would you suggest single people using tinder etc should make sure to find out early / use in their “screening” process for best possible outcomes? Insofar as our data can speak to this (which is debatable), I would say you want to look for a partner who seems genuinely interested in you, who is good at perspective-taking with you, and who seems to be responsive to your needs. Someone who makes you feel understood, validated, and cared for. If I was a betting person, I would bet on those things.
How do control for the self-reported nature of the data? I would imagine people would be biased in their description of their current relationship compared to past relationships or the prospect of a future one. More plainly, I would expect Ex's to have a largely negative connotation and re-entering the dating pool requires substantial effort; so I may respond more positively about my current relationship. Absolutely – people tend to hold a lot of positive illusions about their romantic partners, and to perceive their partners in a highly biased way. But, I think I would push back on the idea that this is something that needs to be controlled for or somehow subtracted from the ratings. When we’re talking about relationship quality, really, perception is reality. You’re happy if you think you’re happy! It’s an inherently subjective construct.
I think that’s why own traits did such a better job of predicting relationship quality than the partner’s traits, in these analyses. Your own proneness to things like positive and negative affect are going to shape how you perceive your partner and the relationship, and therefore how satisfied you are with that relationship. To a large extent, we project our own personalities, feelings, biases, etc. onto our partners.
Dr. Joel! Really interesting research, I can't imagine the tenacity needed to collaborate and coordinate with so many researchers. Looking forward, what variables do you envision accounting for that initial spark between two people, before an established relationship exists? My colleagues and I looked at this very question in another project, where we applied machine learning to speed-dating data. These data were collected by Paul Eastwick (key player in the current project), and also by Eli Finkel. They had over a hundred measures in that study, which I fed into the algorithms. But, despite that, we found that we could not predict that initial spark at all. Zero variance explained.
https://journals.sagepub.com/doi/full/10.1177/0956797617714580?casa_token=SinsSsmAG6EAAAAA%3Ah1e4KUls_Ohk0ODleHlTLpD7l94PfX0R9GZ2yMVjR--ERRHNwSHkymy7nD1WOeJh3enfqRf-uZvWCA
What do you think of the ‘love languages’ and are there any parallels? The love languages are a really fun and intuitive concept. Unfortunately the scale on the website is, psychometrically speaking, a mess. One of the big problems with it is its forced choice format. It makes you choose between options in a way that artificially exaggerates your preference for one love language over another.
I saw a talk by a graduate student once who tried to validate a love languages scale and use it in her research. But when she measured the languages with a Likert scale, she got a huge ceiling effect. Everyone topped out on most of the languages, e.g., most everyone loves hugs, AND receiving presents, AND quality time etc. Basically, she found that everyone speaks every love language.
Are you against the Gottman research that’s been done and widely used as a relationship predictor? How is your work different and how is it the same? Thanks! IIRC, the Gottman findings you're referring to attempted to predict divorce, using coded interactions that were videotaped in the lab. That's pretty different from our project, which predicted relationship quality with primarily self-report variables. So, we can't directly speak to the veracity of Gottman's findings with these data.
I am personally quite skeptical about the claim that divorce can be predicted with 94% accuracy, using any combination of variables. That seems extremely high. The data and code supporting that claim are not available to my knowledge, but I suspect that the models may be quite overfitted to a particular dataset, and would thus have difficulty replicating in a different dataset.
If​ you​ were​ to​ give​ a​ teenager​ an​ advice​ about​ pursuing​ AI​ field, which​ courses​ or​ curriculum​s would​ you​ recommend​ both​ bachelor and​ master​ degree? This I can't say much about, as I took a pretty serendipitous route to learning about machine learning. My background is in psychology, which includes a lot of statistical training but not machine learning per se. I think it's safe to say that you can't go wrong with programming and statistics courses. If you learn some programming environments like maybe R or Python, and learn about some foundational statistical techniques like regression, that should give you a solid basis of knowledge.
What was your methodology for quantifying which factors are most predictive? Meaning, how did you model the data and how did you establish importance of each variable? The project included 43 longitudinal datasets. Each dataset included a large questionnaire collected at the beginning of the study (different measures in each study). We organized all measures collected at baseline into traits vs. relationship variables, reported by each partner. Then, we put different combinations of those groups of variables into Random Forests models to predict relationship satisfaction and commitment at the beginning vs. the end of the study. In total, we ran up to 42 Random Forest models on each study, then meta-analyzed the results.
The Random Forest algorithm pulls out the most important variables and lists them in their order of strength. It also tells you the total amount of variance explained.
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Thanks for the detailed response. Where would one be able to look up the details of the study such as how feature importance was computed (I assume based on decreasing node impurity), if results were cross validated (and how folds were created), and what the predictive performance of the classifiers was? I'm interested since the importance of the variables is only meaningful when the model has good generalization performance. I could not find such details when doing a quick keyword search on the paper. You can find all of the code and detailed results for each dataset here: https://osf.io/g8tm7/
These are random forests built on regression trees, not classification trees, so feature importance is calculated based on reduction of the MSE. Results were not cross-validated - instead we relied on the models' out of bag performance (essentially, the technique tests each tree on a sample not used to construct the tree).
What would be more useful for growing a healthy relationship? 1 horse-sized duck or 100 duck-sized horses? Well Dr. MacDonald, taking an academic approach to this question, I would have to say that having 1 horse-sized advisor would likely be more useful than 100 duck-sized advisors.
Did you study partners with open relationships? Do you believe that open relationships can be long lasting and fulfilling? Thank you for all the hard work. It's incredibly intriguing. I'll have a lot to read up on tonight. This project didn’t really touch on open relationships, but I have done other work in this area. A couple of years ago, one of my students recruited 233 people who were interested in opening up their relationships—but hadn’t done so yet—and tracked them over two months. https://journals.sagepub.com/doi/abs/10.1177/1948550619897157
We found no differences in relationship quality between those who opened up over the course of the study and those who didn’t. We did find increases in sexual satisfaction for those who opened up. This is consistent with other, cross-sectional work on open relationships. So, we don’t have definitive answers yet, but so far, the data are looking promising for open relationships!
Hi Dr Joel, Thanks for the AMA. I was reading your paper, and its really interesting, could you please tell me what 'actor' and 'partner' variables/effects are? "Actor" refers to the person who's relationship quality we're predicting, and "partner" refers to their partner. So, if Andreas and Mary are participating in this study, and we are trying to predict whether Andreas is happy in the relationship, Andreas is the actor and Mary is the partner. When we're predicting Mary's satisfaction, Mary is the actor, and Andreas is the partner. We set the models up this way instead of distinguishing the partners by gender (e.g., husband and wife) so that we can include same-sex couples in the analyses.
So basically, you guys determined that successful relationships are more likely to be successful? I don't mean to be snarky, but how can you say you are predicting how happy people will be with their relationships by essentially asking them, how happy are you with these different aspects of your relationship? This study comes across as more commentary than prediction. The study would be interesting if you could prove that political idealogy, body type, age, religion, upbringing, personality traits are all predictors of varying degree as to whether a relationship will be successful because those are data points that remain somewhat constant before and after the start of a new relationship, and you could then determine how compatible a couple would be together should they choose to pursue a relationship, but the way I am reading this is that you guys basically asked people how happy they were with certain aspects of their relationship, and then said, "if you are in a good relationship, you are more likely to be happy!" It should not have taken 43 data sets from 11,000 couples and a machine learning algorithm to figure this out. This is obvious. Sure, maybe people didn't have an exact value to assign to each variable, but it's no secret that if you don't feel your partner isn't committed to the relationship or you aren't sexually satisfied, the relationship is likely doomed. Can you please offer me a rebuttal to this criticism? I totally get this perspective. But the thing is, it's not science's job to be counterintuitive. Its job is to be robust and accurate, and sometimes reality is just not that surprising.
Many of those more "interesting" variables you mentioned-- political ideology, religion, upbringing, etc--were in this project. They were measured, they were tested, and they didn't work. This project had hundreds of measures, many of which, it turns out, just aren't that important.
For example, take individual differences. Many of these studies included measures of:
- education
- income
- stress levels
- anxiety
- depression
- relationship beliefs
- the big five measures (extraversion, openness, etc.)
- life values
- ethnicity
- self-control
All that stuff combined, measured from one partner, explained a grand total of 5% of the variance in the other partner's relationship satisfaction. That's it.
We preregistered these analyses before we ran them, and were prepared to publish them no matter how they came out. This is how they came out, so this is what we published.
How many of the couples reported being unhappy? Because my experience, compared to what you've answered so far, and what I've read from literally thousands of women on a forum in regards to why they are happy in their relationships, has been entirely opposite of what your data is saying. Most couples were pretty happy, as is typical of relationship samples. But, the responses did cover the full range of the scale, so there were plenty of unhappy couples in there as well.
Hard to say why the results differ from the first-hand accounts you have read. But, the data are the data, and this is what the data showed!
Will the ai ever be released to the public? Yes! Details of the project, including all of the code and meta-data, are available here: https://osf.io/d6yk
What’s your 2nd favorite aquatic creature? Top favorite is whales, hands-down. Second favorite? Gonna go with dolphins. Cetaceans for the win.
Do you want to develop an app? I fully, deeply, absolutely do not. https://twitter.com/datingdecisions/status/1288635730336591872
which relationships last longer? the ones with people with different interests or similar interests? We didn't predict relationship longevity per se. But in terms of predicting relationship satisfaction and commitment, we found no evidence that matching matters in any way. Combining both partner's traits into one model did not predict more variance than one partner's traits on their own.
So we found no evidence for the idea that birds of a feather flock together, nor did we find evidence for the idea that opposites attract.
I mean, aren't those factors pretty obvious anyway? Why do we need an algorithm to analyze 11,000 couples to tell us we need decent sex, affection, and trust? It's a good point - the variables that wound up being important are pretty intuitive. But, many of the variables that didn't make the cut seem intuitive as well. For example, you'll notice that gender is not on the list. There are hundreds of studies on the importance of gender in relationships, and it was measured in every study we had. Yet, it almost never emerged as a predictor.
So, I think this is the sort of project where any results would have appeared obvious in retrospect. To me, the surprising findings are not so much the stuff that worked, but the stuff that didn't work. You can see a full list of all the variables tested here: https://osf.io/8fzku/
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Surely that's because (almost) no one for who gender is important enters a relationship with someone who isn't that gender? I'm sure if we could take a group and randomize partners gender - gender preference would emerge as significant. I feel like these results say "Gender isn't important in a partner as long as you pick the gender you want your partner to be" Not gender preference, gender. YOUR gender.
If relationship satisfaction operates differently depending on your gender--for example, if men and women prefer different things in a relationship--then gender should have emerged as a consistent predictor in our models.
I'm preparing to apply for MSc thesis to research in Western. I am an international student. What would be your suggestion to get in and conduct my research successfully? This could be a whole other post, but one key piece of advice I have for people applying to graduate school is to spend some time on that research statement. The statement provides an opportunity for you to demonstrate:
* Intrinsic motivation (are you confident that graduate school is how you want to spend your next 5-6 years?)
* Prior research-related experience (how have you honed your academic interests and skills?)
* Research interest fit (is this lab a place where you will be able to conduct the kind of research you want to do?)
Also, be sure to do a bit of research into the advisor you're applying to work with and make sure that there's fit there, both in terms of research interests and in terms of their mentoring style.
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I've identified two Computer Science professors at Western and reading though their papers and work. So I should have my exact research statement before applying for the University and contacting the professor? Or will I get admission because of my profile and later discuss with my professor to choose a research statement? You should begin by contacting the professors, briefly explaining your research interests to them and asking if they are accepting students. Then if they are accepting students, you should craft your research statement, which you include as part of your application to the program.
Hey, I'm also from UWO. Do you have any papers published that I could learn further? Hello, fellow Mustang! A full list of my publications is available on my lab website: http://relationshipdecisions.org/publications/
Have you ever watched Black Mirror, or anything else explaining why this is a bad idea? Black Mirror is a really nice illustration of the importance of research ethics boards.
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I think they were referring to the episode Hang the DJ which I won't spoil but is very pertinent to your work. I came to ask if you had seen this. Ethics aside, I love the Hang the DJ episode of Black Mirror. It's consistent with my view of relationship compatibility, which is that you cannot predict the quality of a relationship that hasn't formed yet.
Hi! Thanks for doing this ama. Did you study same sex couples? Were there any discernible differences in relationship satisfaction? Some of the studies had a modest number of same-sex couples, and many studies had sexual orientation as a measure. Neither gender nor sexual orientation tended to emerge as a predictor in the models, suggesting that there probably weren't a lot of differences there. That said, we did not dig into the data and directly test for differences.
So why do you even think that it is possible to predict the future of a couple ? In my experience computers are not very good with predictions. And what are your objective points with wich you feed the ai. And I think that your work is really great and interesting :) Thank you, Party_Frozy! Certainly, we went into this project prepared for the possibility that we would not be able to predict relationship quality at all. In fact, the last time my colleagues and I embarked on a machine learning project, it was with speed dating data, and we reached exactly this conclusion – we could NOT predict which pairs of individuals would be attracted to each other. (https://journals.sagepub.com/doi/abs/10.1177/0956797617714580)
So we were pleased to find that we could predict up to 18% of the variance in relationship quality over time. It’s a modest amount, and there’s certainly lots of unexplained variance left there. But it’s more than 0 and that’s exciting!
The predictors we used in the model were hundreds of self-reported measures collected from the couples. There was a total of 43 datasets, each of which measured different things. Tons of traits, preferences, relationship judgments, demographic variables, etc. Some more concrete and objective than others.
the below is a reply to the above
Why apply machine learning to something as nebulous and subjective as human relationships? Are you interested in applying ML to other areas of social science, or perhaps even the humanities? It seems to me that you're doing some cross disciplinary research. Is your background more in social science or computer science? My background is in psychology. I'm a relationships researcher, so romantic relationships are really my focus. I agree that relationships are incredibly nebulous and subjective, which is part of why they are so fascinating to me! I think they’re a central part of many people’s lives, so it’s worth pulling out all the methodological stops to try to understand them, empirically.
I take a multi-method approach to studying relationships. In other projects I've used videotaped interactions between couples, daily experience studies where we send brief surveys to couples about their relationships each day, longitudinal methods where we track relationships over months or years, etc.
the below is a reply to the above
One of the interesting things about data mining is its ability to find correlations that people wouldn't normally think of. Have you considered adding some objective variables such as height, weight, eye color, frequency of sex, etc., along with people's subjective assessments of the quality of their relationships, how long their relationships last, etc? Or do you do that already? Many of the variables you listed there were included in at least a subset of the datasets we had. Sexual frequency was commonly measured, and was a decent predictor. Specific physical characteristics (e.g., height, weight) were not measured frequently enough to really say how useful they were. When they appeared, we categorized them as individual differences.
Why can't you predict anything with covid? Believe me: the COVID research is coming. Many academics are currently studying relationships in the wake of COVID, but collecting data, writing up the results, and getting them published is a very slow process. Expect an explosion of papers in another 1-2 years.
How did you like WesternU? London is a great area. I've only lived here for two years, but so far I like it a lot! Western is a great place to work- awesome students, and tons of research support. London is a smaller city than I'm used to, but it has a lot of hidden gems. The longer I live here the more it grows on me.
submitted by 500scnds to tabled [link] [comments]

I've got a second job "leasing" my mind while I sleep. My last assignment ruined my life.

Lots of people these days have second or third jobs. The days of a K-12 education getting you the mortgage, the car and the white picket fence are long gone. I used to get frustrated at the fact that I “did everything right”, studied hard, went to a good college, got a decent qualification, and I still struggled. But after a few months of averaging four hours sleep a night and getting stock levels between your daytime employment at the cafe and your job night-managing a big box store mixed up eventually you just resign yourself to it in a numb way. But when these two grim service industry hustles still didn’t make ends meet I used to turn to the surveys.
They are lots of websites that pay you a little cash (or vouchers or coupons or rewards points) to spill little details about yourself. Age, gender, occupation, education, favourite colour, preferred holiday destination and so on. In the era of “big data”, social media espionage and surveillance capitalism it’s really no different than submitting yourself as a guinea pig for medical trials, only instead of expending a liver or appendix for quick cash you’re selling little parts of your personality to keep the lights on.
So when I spotted the “Happy Valley Dream Survey” I was intrigued.
None of these surveys had ever asked me about my dreams before. Oh aspirations definitely. Where do you think you’ll be in five years, what’s your ideal occupation, what was your dream job as a kid. Little pieces of personal minutiae dedicated to building up an advertising profile in some corner office somewhere so they could figure out what kind of toaster all the baristas that used to dream of being vets would collectively prefer. But none had ever inquired about those mad nighttime hallucinations all of us humans merely take as a matter of course. Wake up sweating at 3am after facing down a High School English test in your boxer shorts? All a lovely part of the human condition.
So I clicked in and answered. It was relatively simple, only asking you to describe the strangest dreams you’d had in the last month and rate the frequency at which you remembered your dreams as well as the relative strangeness of your reported dreams in comparison to more ‘regular dreams’. As a teenager I had been briefly obsessed with the idea of lucid dreaming, the ability to remain conscious in and take control of your dreams, and although it had never fully come to fruition it had kept me in the habit of keeping a dream journal which meant, in comparison to most of my population, I tended to remember much more of my dreams. I threw in some bullet points on some my strangest recent night-time reveries (one of which involving a spirited debate with Mr T and Queen Elizabeth about the relative benefits of Robespierre’s Reign of Terror) pinged off the information and used to newfound spare change to grab myself a little breakfast pastry on the way to my coffee shop job.
I tend not to answer unknown numbers, having that perennial fear it’s a scammer or a debt collector of some kind, so I have no idea what compelled me to answer that one. On a rare night off I was peaceful dozing, tongue lolling out and drooling, the whole nine years, when I was awoken by the cacophony of my factory settings ring tone. When I answered the phone I thought curiously that I couldn’t remember what I had just been dreaming about.
“Hello...am I speaking to DBTraven right now?”
“Uh...yeah”
“Oh how very wonderful. I’m calling from the Happy Valley Subconscious Services Centre. We were very interested to see the results of your survey and feel you may be an excellent candidate for much more lucrative opportunities. Could you come down to our Services Centre on [My City Street] immediately?”
My foggy brain took a moment to process the request. It was 3am...who in their right mind is operating some kind of survey centre at 3 o clock in the morning. My immediate thought was I had accidentally joined some kind of cult and would end up roped into a kind of group marriage scenario was I to head down there.
“If we see you in the next half hour we’re pay you one thousand dollars no questions asked. All we ask is you come and talk to us”.
At that point I was certain of two things. One, I had in fact volunteered myself to be part of some kind of bizarre end-times cult where I would have to drink poison to ascend into a UFO. Two, that 1000 dollars upfront would go a long way to digging me out of the rent hole I was in and maybe might even give me enough breathing space to afford an apartment where I couldn’t fry bacon on the stove from where I lay in the bed. I got dressed in a flash and head downtown…
...to find myself standing outside a Nail Salon. “Cutie-cles” the sign blared in hot pink, with an attractive woman winking slyly and brandishing her long, ornate nails. The lights were off inside and you could almost see the space where bustle and gossip were meant to occupy, between the gaudy vanity mirrors and cream recliner chairs. There was something eerie about it but, more importantly, an empty nail salon seemed unlikely to be the source of my dreamed-of cash injection. Just as dejection was beginning to seep in I received a text.
“Side Entrance. Say your name, followed by the word “Awake”.”
Things got more ‘Eyes Wide Shut’ by the minute but, mind filled with far off dreams of an apartment where the “bed-room” was in fact a separate room, I floated on down the alley beside the nail salon. I came to what looked like an emergency exit and rapped on the door a couple of times, producing a few hollow thuds. After I heard nothing for a few seconds I called my name into the darkness and, after a moment of hesitation, said the word “awake”.
The door swung open to reveal a halogen-humming hallway. A man in a security officer’s uniform regarded me, while his fellow behind him patted down a girl about my age who seemed dazed and drowsy. He instructed me curtly to follow him and we walked down the hallway as the girl behind me had something taped to the inside of her coat and was ushered out the door. My heart rose into my throat as we walked, passing peeling paint and bare walls. This looked neither like an innovative survey start up nor some kind of death cult, but instead the sort of place where organised criminals might bet on bare knuckle boxing matches. I was shocked when we emerged into an airy foyer and I was greeted by a smiling, professional looking receptionist in a neatly pressed pantsuit.
“Mr Traven! We are just so very delighted to meet you”.
She looked away from me and started tick-tacking on the computer in front of her before I could respond and she then swiveled around to face me and informed me the 1000 dollars had now been deposited in my account. Not wanting to look a gift horse in the mouth and still a bit stunned by the whole situation I elected not to question the fact that the survey sites had always said your banking details were held securely and were inaccessible by any of the private organisations you were surveying for. Before I could say one word I was being whisked into a little glass cubicle behind reception marked “Dream Lab 1” to be greeted by a woman, a few years younger than myself, in a lab coat draped over a hideous lime green sweater.
“Have you ever wanted to do good in the world, without lifting a finger, and also benefit yourself financially at the same time?”
No ‘hello’. No ‘how are you’. Not even a quick review of my medical history or further strange surveys. I could feel my hair begin to prickle with suspicion. It was the kind of conversation opener you expected to be quickly followed by a reassurance that “no, this is in fact a kind of ‘inverted funnel’ funding model!”.
But I just nodded. I figured I could squeeze these freaks for a little more before I got the hell out of dodge.
“Have you ever read about those people who used the idle processing power of their gaming consoles to simulate protein folding and assist in fighting disease?”
Recalling some fragment of a headline I had read somewhere I told her that I had. She smiled and continued with her earnest-sounding sales pitch.
“Well we do something like that here. While you sleep we borrow some the subconscious processing power you ordinarily use for dreaming and lend it out to private clients working on everything from medical solutions to prime number generation. If you’ve ever dreamed of...um desired to get paid handsomely to sleep then this is an incredible opportunity to be on the cutting edge of science and fill up your pocket at the same time”.
It didn’t immediately scream “orgies, sister-wives and armed stand offs with the government” but I couldn’t help but feel that there was more to the whole process. I inquired about how exactly the whole process worked and the woman, who I would later come to know as Dr Tanner, pulled a thin metallic shard from her pocket and offered to show me how. Feeling the weight of my landlord’s unread text message in my pocket I went for it.
I awoke and equations were swimming in the halogen. Mathematical symbols floated along in the light like those alphabet spagetthios, Greek symbols in a synchronised swim with incomprehensibly large numbers for someone used only to price tags and sales taxes as his primary act of numeracy in the day to day. As they vanished I rose from the firm mattress and met the face of a smiling doctor Tanner.
“You may have just helped to advance the field of theoretical mathematics by a year or more. Not a bad way to make 3 grand huh?”
My head was hazy and, grabbing beneath the fog, I felt the warm intensity of my original suspicion. My phone didn’t seem to work in the confines of the ‘services centre’ so I asked Dr Tanner if there was some way I could check my account. She gladly volunteered her information and there was 4 grand staring back at me, more money than I had ever seen in one place, never meant my perennially barrel scraping bank account. Taking all precautions to delete my login information from her computer also gave me time to collect myself and pick my jaw up off the floor.
“Would you be interested in continued opportunities with Happy Valley?” she asked.
As I walked toward the exit one of the security guards begin to rustle in his desk for something to give me but the other held a hand up at him.
“Awake” he cautioned his colleague and the two let me out into the night air without incident.
The next day I went looking for a luxury beyond my wildest imagination: an apartment with windows.
If you’ve ever turned around to a domineering boss, told them “I quit” alongside some choice profanity and home truths, you’ll understand the sense of pleasure that coursed through my veins on the day I strolled out of the coffeshop for the last time. I had already moved to part time in my retail gig, full of the inimitable pleasure of half-assing things when you come in on your weekend shift and knowing your incompetence will be erased by whatever calamities occur in the days you’re off. I felt totally and completely free and the only inconvenience I had to show for it were the sometimes odd residues of those tasks that occupied my sleep: the chemical formulae I spotted sometimes in the early morning light or inheritance task calculations drizzling down my shower curtains as I open my eyes after washing my hair. A small price to pay, I thought, as I strode to the door of my 1st floor one bedroom apartment. I greeted the doorman-my doorman!- as I stepped inside and for a moment I thought he looked just a tad familiar.
I convinced myself it was another piece of ‘dreamy debris’ when I heard him mutter the word “awake” as I crossed the threshold.
For the past several months I had been “working from home” so the speak. Dr Tanner had informed me that the first few sessions usually required pretty strict observation of the ‘sleeper agent’ as she liked to jokingly call me, but eventually Happy Valley were content to send me home with the NeuroChip and inform me by email of clients and payment information every couple of nights. At that point I simply couldn’t believe my luck and my friends marveled at my tasteful, airy apartment and the carefree manner in which I ordered rounds of drinks at the bar with wild abandon. It also didn’t hurt my love life, is all I’ll say.
Happy Valley kept me under a strict non-disclosure agreement, which Dr Tanner said related to the ‘experimental prototype nature’ of the subconscious interface technology I was using. When people asked I told them I had picked up a job with a research-related start up which technically wasn’t all that far from the truth. They didn’t also need to know that when they saw me stare blankly into the head of my beer sometimes it was because I was seeing visions of molecules breaking apart and recombining in new and indecipherable ways.
When Dr Tanner told me I would have to come back to the services centre for my next appointment at the unsocial hour of 1am I must admit I bristled slightly. I had grown used to my comfortable, dream-computing playboy lifestyle and any imposition on it seemed like an intolerable demand. I had come along way from glumly agreeing to stay behind and clean out grease traps.
“This assignment is of a serious and sensitive nature. We feel you are the most capable agent we have at the moment and we would very much like you to take it on”.
The flattery was pleasant but I needed a little bit more convincing.
“And of course it will be incredibly lucrative. Have you ever wanted to used hundred dollar bills to mop up your two century vintage wine you spilled on your marble floor. It’s that kind of lucrative”.
The doorman’s eyes burned into my back as I hurried out the door.
“It’s government related...that’s as much as I can tell you”.
Dr Tanner perched on her chair in the corner next to the observation bed and chewed the corner of her lip, in thought. Were those nerves I detected in the ordinarily unflappable Doctor? That I didn’t like and it set my nerves jangling.
“I’m going to be flying drones or something in my sleep aren’t I?” I asked, partly as a joke and partly as an expression of the uneasy suspicion that was welling up inside me. Tanner laughed it off and soberly reassured me that no “military or foreign policy objectives would be satisfied” by my assignment. She followed up with this reassurance with implication of the fortune this assignment would bring me. I believe the phrase “set for life” may have been thrown in there once or twice. She sure knew how to speak to a cash-strapped millenial. Perhaps, I suspected, because she may have been one herself. I lay down on the bed with my mind swimming with visions of financial security and all the avocado toast one could eat….
….and awoke, staring at my hands, covered in blood. The light was low and at first I thought the stains were mud. Had I fallen somewhere? Where had I been?
I looked out to find myself in a spectacular penthouse apartment. Floor to ceiling windows, kitchen island, state of the art home cinema. Had I merely skipped directly to the “unfathomably wealthy” part of all this. My heart beat, deep and rich. I was still caught in the relaxed rhythm of a dream. Until I saw the body.
I had thought it was just a pile of clothes on the bed. As my eyes grew used to the dim light, the only source being that of the early morning skyline spilling in, I could make out hair and ears and wounds. My heart began to pound and my legs almost gave way. An older man in a silk dressing gown, splayed on the bleed as his blood seeped into the mattress. What took over then was instinct and all that remained in my conscious mind was a string of blaring profanities as I washed my hands and splashed my clothes in a panic.
I was already speed-walking my way down the hallway (“don’t run don’t run don’t run running is suspicious”) when I heard Dr Tanner’s voice.
“He’s awake! This can’t be possible”.
I turned in fright but no sign. It was then my thoughts turned to the NueroChip. I tugged at where it sat like a parasitic insect behind my ear but its pincers refused to give. Was it being controlled remotely? It was then my palms began to sweat and I felt that pit of my stomach fear. I looked to one of the maintenance closets in the hallway I was walking down. You know that feeling in a dream, where you know something terrible is coming but you haven’t quite seen it yet? I knew whatever was on the other side of that door was coming and it meant to do me harm but I was rooted to the spot.
The Dr Tanner phased through the door, towering over me quite larger than her ordinarily more diminutive frame.
“This was not supposed to happen. Everything has gone wrong. One of those minimum wage morons in security didn’t do his job properly. But….”
A pall of resignation came over her face, as though she was acknowledging the death of friend
“High risk, high reward. I’m afraid you’re going to have to take the rap for this one. Oh and don’t bother mentioning Happy Valley. By the time the sun comes up we’ll be nothing but an empty commercial space once tied to a shell company”
With that she disintegrated and I took off, heart hammering, into the night air.
I’ve been hiding out in a disused stock room of my old coffee shop for days now. I remember how I used to fantasise, after surreptitiously getting the key for this place copied, about how I was going to plant some heinous, smelly object in here to get back at my boss someday. Instead I’ve hidden myself. The NeuroChip won’t come off and I haven’t slept since that night. Nightmares are now beamed into my skull remotely and every time I fall asleep I spend an impossible length of time in terror and agony. I see visions of detectives stooping down, brushing fancy sushi knives in that apartment for fingertips. I see that old man’s twisting maw chasing me through endless nonsensical hotel hallways.
So I do not sleep any more and my body aches for rest. But I am beginning to dream while awake and the shapes and shadows in my vision are my own.
--------
If you believe you might have use for my skills in your secretive organisation, please check out my resume here
submitted by DBTraven to nosleep [link] [comments]

[Tales From the Terran Republic] Sweatshop Sheloran, Agent Mongrave Stumbles, and Gloria Reborn

So what's been happening in the Republic these days?
The rest of this series can be found here
Author's note:
Ok, so Old Earth supercapacitors are used by the Republic... In one VERY specific application...
***
A plath, robed in translucent silken robes, strode down a strange corridor. The walls and floor were made of a slightly moving membrane, shot through with pulsing veins carrying fluids in a rainbow of colors.
A glowing orb, one of many that illuminated the hallway, drifted over to her and started to cuddle. She smiled fondly as she petted it as it made little urgent squeaking sounds.
“Oh, you want a treat?” she asked in a strange language as she reached into a fold of her robe and pulled out a crimson berry.
The orb bounced up and down happily in mid-air as a tiny mouth opened eager to accept the morsel.
The plath laughed as the light-beast gobbled it up. “Beast” wasn’t exactly the right word. It was actually a fruit that had matured on one of the glow-trees in the main garden.
She squeezed it gently as it giggled. It was still quite firm, still a good month before it would be ready for harvesting. It was an exquisite specimen, so clever, and very long lived for its kind! It would make a magnificent feast when its cycle was complete.
She examined it closely, reaching out with her senses as she sang softly. Its seed was forming nicely already wrapped with a healthy layer of fat. Such richness already!
Yes, this one, she thought with great satisfaction. “You shall become a mighty tree, little one,” she crooned at it as it beamed happily (and literally) at her.
The illuminator followed her as she walked down the hall rubbing happily against her. As she walked a row of bulbous growths sprayed oxygen rich beautifully scented air at her. She inhaled deeply, savoring the fragrance. She stooped down and sang at the soil. It parted at her voice moving gently away from the roots. As the illuminator fruit hovered helpfully above her.
Such a good little drupe! She reached up and gave it’s underside tickles. It cooed with delight.
After examining them, the soil closed back with a beautiful song and a wave of her hand.
Finally! she thought with a satisfied smiled. There had been no sign of the blight in months. It appeared that they finally had put it to rest.
Everything on the ship in perfect balance, she thought. If only we were similarly blessed.
She cocked her head slightly. She was being watched again. Now who is that? she mused. It wasn’t her rivals or the misguided revisionists. Of that she was sure. It was different, not real but yet was.
She paused at a section of wall and crouched placing her hands on the floor. Nobody had followed her.
She rose and caressed one of the walls, singing softly as she did so.
The wall quivered and started to thin, becoming transparent, revealing a pitch black chamber behind it. Leaving her favorite illuminator behind, she stepped into the thin gelatinous membrane, passing through it with ease. It thickened and became opaque, tough, and leathery just like the rest of the passage in seconds.
The chamber started to gently glow in soft cyan hues with phosphorescent fungi when it recognized her scent. Had she been someone else, her little darlings would have had a much different reaction.
One could never be too careful, especially these days.
She waited, silently, her hands on the bones of the ancient vessel in which they traveled the other realm, crossing the gulf between the stars in mere days.
The ancient cellulose bones whispered to her. They said that nobody followed.
“Thank you old friend,” she said pressing her head against the beams.
She then shrugged off her garments, letting the silken wisps float to the floor. Her graceful form then moved to a small tray, grown into the wall, filled with a nutrient rich broth.
Inside, were a row of small flask gourds in a rainbow of hues. She selected two. She then walked to a small circular pool in the center of the chamber filled with absolutely pure water.
She knelt by the pool and a small pore in the first gourd opened. She placed two drops of purified malporixlorh extract on her tongue. She shivered as the potent drug entered her bloodstream, her mind, her soul, unlocking that which was bound.
After a few minutes of meditation, the second gourd opened, it’s top forming a small lip. She poured a small measure of an oily substance in the water, its surface soon covered with endlessly shifting prismatic colors.
She then closed her eyes. Small ripples spread around their edges as glands secreted a greasy, waxy substance that instantly melted coating a thin, almost invisible membrane.
She opened her eyes… Then she opened them again as the transparent covering slid back revealing her real eyes, the secretions causing colors to dance across their surface.
She stared into the pool, transfixed by the constantly shifting colors. They then started to intensify as time slowed down.
Small creatures living in the lining of the pool started to glow as she extended her senses beyond the walls of the ancient ship, out into the formless, timeless void of the outer realm in which she traveled, peering into the endless shifting tides of the past, present, and future, constantly changing like the colors on the surface of the water.
She smirked. Nothing changed, not really. Their fate was fixed, as it was ever since their terrible “mistake” that really wasn’t one. Try as they might, her fellow plath would not succeed. Every move they made to avoid what they were doomed to become only set it more firmly in the singing strings of reality.
She took a moment to see the struggling lines of probability as the two sides waged their pathetic war. Her sisters were fighting and all too often these days dying to prevent the foolish revisionists from tearing down all that they had built over hundreds of thousand of years. Both sides were fools. Her brothers and sisters were fighting and dying trying to preserve something that didn’t need preserving and the fundamentalists were fighting to stop that which could not be stopped.
They would not stop it. They couldn’t. They could only delay things a little. Fate’s judgment, especially when annoyed, was absolute.
The fate of the plath, and in a more immediate and pressing sense, her own, was sealed, not that it mattered. The past was set. The future was set. The only thing they were free to toy with was the present.
And her present was going to be as pleasant as possible for as long as possible. Then, just like that little glowing drupe, her cycle would end filled with happiness and peace as she rejoined all that is.
She realized that she was being distracted by the brightest colors and cleared her mind, peering deeper, looking for the soul that was caressing her being in the dead of night.
She took another drop of malporixlorh, a risk, but a worthwhile one as her mind expanded further.
There! deep in the timelessness somewhere… somewhen an individual’s mind was swimming through the void vibrating in time with the strands of fate, their fate.
She smiled and the shifting colors of her eyes synced with the shimmering of the pool. She saw her!
“Hello there,” she sang softly.
***
Sheloran awoke with a gasp, sitting bolt-upright in bed.
“Murrph?” Craxina muttered as she awoke.
“The dream again?” she asked.
“Yeah,” Sheloran replied. “It was really freaky this time,” she said as she shuddered. It felt like someone was staring at her.
“You should really stop playing that game,” Craxina said sleepily as she snuggled Sheloran.
“I know… I know,” Sheloran replied. This all started after playing “Submerged!”. It was an older title but there was just something about it. The surreal organic landscapes, and the strange little cult following that still kept the servers running after twenty years, had entranced her from the first second she loaded it.
She literally couldn’t stop playing. She had always scoffed at “gaming addiction”, but she was really starting to wonder.
And the more she played it the more intense the dreams. They terrified her. They weren’t gory or violent, like some of her nightmares, they were just… Weird… Scary weird...
Really scary.
There was no way she was going to sleep again tonight. She started to get out of bed.
“Where you goin’?” Craxina asked.
“I’m just going to sit for awhile,” she said as she wrapped a silken robe, something that she recently bought online, around her night dress.
“You’re going to play aren’t you?” Craxina asked accusingly.
“Not after that last dream,” Sheloran said as she started to make a pot of tea. She really wished she had some Helson Grass or Arenaul Herb. She had taken for granted all of the herbs and plants of her homeworld. The creators had blessed them with such bounty. For the thousandth time that week she wished she had the presence of mind to snatch a few seeds, a clipping or two.
As soon as that pooping border opened back up, she was definitely going to be getting her buddies to go pick up a few hundred different seeds. It was going to be tricky, since they were “sacred” but credits talk and dogma walks. Somebody would be willing to go foraging for a few bucks (or games).
She was getting those fucking seeds… Oops… She was getting those darn seeds, she thought as she corrected herself. What was with her potty mouth these days? The Great Prophet warned about obscenity. It was “dangerous”… for some reason.
She sat down with a book on Terran botany as she sipped her tea. She started unconsciously flipping the pages faster and faster. She suddenly stopped, staring at an organic molecule.
That’s close! she thought excitedly and then blinked. She could work with that!
Close to what and what, exactly am I going to do to it?
Oh poop, there was that strange feeling again. She set down her tea and reached for a bottle of absinthe. Absinthe was yummy!
And it certainly took the edge off...
As she took out a box of sugar cubes, Craxina quiet snoring started to fill the room. She smiled. She used to find it so annoying but now, it was really comforting. It was really nice having someone to sleep with. It wasn’t a boyfriend but still, it was nice. Then again, plath, even boyfriends and girlfriends, didn’t sleep together. Heck, even husbands and wives didn’t. She wondered why? It was nice to have someone next to you. Some of the things that the priests said the Great Prophet commanded seemed kinda loopy every now and then. (May the Great Prophet forgive her.)
What was the harm of “sleeping alongside one another”? It wasn’t like they were “doing anything”… (Not that Craxina hadn’t offered… Fortunately, she was fine with the word “no” for once...)
She was starting to think the Great Prophet was just opposed to a good time.
No, he meant well. He really did. He was just… misguided...
What!?! Great, now I really am a heretic...
Her eyes suddenly looked over at her very nice VR rig.
She was already awake and just a little Submerged wouldn’t hurt.
She walked over and put on the modified headset and smiled as a shimmering pool filled her vision. She couldn’t wait to see how her little demon/flower hybrids were doing!
***
The next morning Craxina woke up to an empty bed.
She looked over towards the VR rig. There she was, asleep with the headset on.
“Wake up, junkie,” Craxina said only halfway joking as she nudged Sheloran.
“I’th ras lori’kiah-shun?” Sheloran mumbled.
“What?” Craxina asked in alarm, her fur standing on end for a second as shivers ran down her spine (and not in a good way).
“Huh?” Sheloran asked hazily as she pulled off the headset. “Sorry, I guess I dozed off.”
“Do you gamers have your own language or something?”
“What?” Sheloran asked in confusion, “No.”
“You just said something really weird. It was like really creepy.”
“Did I?”
“Yeah! It sounded, I don’t know… demonic or something!”
“Well, I am the Befouler,” Sheloran joked, “Grr!” She really didn’t want to think about… whatever just happened.
Craxina just laughed along but in all honesty, Sheloran was starting to scare her a little…
And it was getting worse…
***
Helen Mongrave drank her morning coffee as she accessed a certain dating website.
She smiled. There was a rather filthy message from an “admirer”.
“Oh, Jon,” she laughed fondly. He still had the same sense of humor he had in boarding school.
She loaded up a script and processed the unsolicited dick pic that was attached. At least it wasn’t his dick. She knew for a fact, unless he had a very uncharacteristic growth spurt, he was nowhere nearly that well endowed.
A message slowly started to appear.
He had made it into the Republic and was wanting a list of who he could trust as well as a briefing of the latest developments.
She loaded a rather graphic image that was definitely not to Jon’s taste and encrypted her reply with a chuckle.
Let’s see how Jon likes that one! she chuckled to herself. Jon was a pretty good man, or had grown into one. Yeah, he screwed up royally in the past but she couldn’t help but wonder if maybe, after all this bullshit was finally over, maybe…
***
Sheloran wiped down the counter and cleaned the espresso machines for the sixth time that morning as she tried not to think about last night.
Maybe she should just uninstall that fuc-… that darn game.
The Great Prophet was right! she thought as she felt something stir inside her. Obscenity is dangerous! That’s it! No more potty-mouth!
“May the Prophet guide my steps, guide my thoughts… May he guide me away from the darkness...” she repeated to herself, a quiet little mantra.
The door opened and a small xeno walked in with fuzzy pale fur and a cute little snout, a garthra? She thought it was a garthra, a Federation species.
“Hi!” Sheloran said brightly. A customer! A lot of her business, both legit and somewhat less so, depended on the Federation trade, something that had been brought to a screeching halt. A lot of the neighborhood was in the same boat. The whole free port zone was for the Feds, not the Empire, and a lot of the businesses in the area were run by Federation emigres just as reliant on the Fed trade as she was.
The whole place had almost shut down. If it wasn’t for her annoyingly profitable den of ill-repute she would definitely be in trouble. “The girls” (and a few boys and other genders) were pretty much what was keeping the door open these days.
“H-hello...” the little female said nervously.
“Can I help you?” Sheloran asked hopefully. “Maybe some media?” God, she hoped it was media. That was the whole reason for this whole goddam-… pooping thing.
“I… I heard… I heard that...” she said as she clutched at her pretty little dress. “I heard that someone could… make some money here? By doing… doing...” she buried her face in her little hands and made a strangled little yelping noise.
Sheloran didn’t know garthras? (she was pretty sure it was a garthra) very well but she knew crying when she heard it!
Poop. She sighed sadly. Unfortunately this was becoming far too common. People were stuck with no way to get home (or couldn’t return for one bullshi-… poopy reason or another) or their business were tanking or their employers were going under. Desperation was setting in and she was filling out way too many union cards for the wrong reasons.
It was… wrong, she thought as she felt an odd pressure around her eyes. Her eyes had been bugging her here lately. She probably needed some Eyesoothe, that’s what you took when your eyes were hurting like this. It made it go away. Some Restful Palm wouldn’t go amiss either. It really helped with the unsettling dreams and recurrent unpleasant thoughts she’d been having.
Maybe some Void Balm too! What she wouldn’t give for just a few blossoms. Absinthe just wasn’t cutting it anymore, at least in quantities remotely close to advisable.
Not knowing what to do she walked around the counter and started to wrap her arms around the distressed xeno. The poor garthra collapsed into her arms, sobbing inconsolably.
Sheloran squeezed her eyes shut and winced as her orbits ached. Seriously, this was fucked up… Messed up! I meant messed up!… Great Prophet guide my steps...
“It’s… It’s going to be ok,” Sheloran said, not really believing it.
***
A few minutes later after Sheloran calmed her down and gave her a soothing cup of peppermint tea (She wasn’t sure why but she was definitely certain it would help… And it did!)
“Have you eaten today?” Sheloran asked as Uhrrbet (that was her name) sipped her tea.
She shook her head.
“Did you eat yesterday?”
Uhrrbet’s nose started to run (garthra “tears” were really snotty!) as she shook her head.
“Well that I can help with!” Sheloran said with a smile. “Do you like donuts?”
Uhrrbet’s eyes lit up.
“Come around back,” Sheloran smiled, the pressure in her eyes finally subsiding, “Plonxi damn… I mean darn… Great Prophet guide me!… She darn near bought out a bakery this morning.”
As Uhrrbet was stuffing herself with yeasty goodness Craxina walked in, robe annoyingly open.
“I tell you,” Craxina exclaimed as she dried herself off (after a shower! Get your head out of the gutter, perv!), “that guy was freaky! You won’t believe what he wanted me to do!” she laughed. “I thought I’d heard them all but, wow!”
Uhrrbet stiffened up as Craxina started to go into detail.
“Not a good time, Craxi,” Sheloran said urgently making a cutting off motion behind Uhrrbet’s back.
“Oh, it isn’t bad at all!” Craxina said to Uhrrbet. “You don’t even have to try to shove one inside you, if you don’t wanna. You can just play with it or put it in your mouth! Their stuff tastes really good!”
Uhrrbet’s nose started to run.
“Craxi. Go. Away!” Sheloran said as her eyes started to pulse.
“Yessh!” Craxi said, her damp fur trying to stand on end. “Alright! Alright! Jesus!” she yelped as she snatched a donut and scurried off.
“Sorry about that,” Sheloran said to Uhrrbet trying to calm her back down. “Craxi is… well her whole species is… They’re different from most of us.”
“It’s… ok…” Uhrrbet said between damp sniffles. “I… I guess I need to get… used to...”
She broke down, dripping boogers onto the donuts.
I hate my job, Sheloran thought as she held Uhrrbet. This was supposed to be fun, selling games to Federation delinquents. It wasn’t supposed to be this bullshit.
“Hey… hey...” Sheloran said soothingly, somewhat at a loss. “Look, you don’t have to do this.”
“I do!” Uhrrbet wailed. “I owe the Harkeen money! If I don’t come to work for you, I’ll have to work for them!”
Sheloran snarled as her eyes started killing her. Those… jerkfaced bullies! She hated them with a passion! They were part of the Threen mafia and were a constant pain. They thought they ran the free port. She already had more than one run-in with those… fucker-… Jerks!. She had done a couple of “union membership drives” involving some of their “employees”. They liked to growl and spit but they just a bunch of scared little bullies. When the union came calling they always backed down but sooner or later, they were right back at it. Drugs, prostitution, “protection rackets”, stuff like that.
She didn’t have a problem with them because she had the union at her back but so many others had no choice but to pay them off.
And the cops were useless. They didn’t care what happened “down here”. They just broke up fights and if something worse happened they would collect the bodies and make arrests if they could.
She really should start selling weapons… It wouldn’t take much to get a dealer’s license…
But most of the little Feds were too timid to use them anyway. That’s the problem. Everyone ran scared of them.
“Is there anything else you can do?” Sheloran asked helplessly. “A skill, a trade… anything?”
“I… I can sew,” she said hopefully. “I made this dress!”
“Well that’s something!” Sheloran said cheerfully. “Hand made anything is valuable! If you can sew then there is no reason why you couldn’t make human clothes and sell them!”
“But I don’t have money for fabric or anything,” Uhrrbet said helplessly. “And if I don’t pay them something by tomorrow they say they’ll… they’ll...”
She started crying again.
Voiddammit… I mean poop… Great Prophet help me! Please!
“(Sigh)… How much do you owe?” Sheloran asked cursing herself (for real) for asking.
“Fifteen hundred… Sixteen hundred by tomorrow,” she said helplessly.
“Ok,” Sheloran said as she pulled out a transactor. “I’ll front you the cash to pay them off, and you can work here, I still have space. I’ll pay you by the piece and then… I’ll sell it… somehow… I don’t know, I’ll set up a website or something.”
Uhrrbet looked up at her in hopeful disbelief.
“You’d… You’d do that?”
Why? Sheloran implored the universe. Why are you doing this to me?
“Sure, why not?” Sheloran replied. “My ‘normal’ business is in the crapper. Might as well diversify a little. Let’s call it an investment. If it works out then great! If not… then we can talk about a union card.”
“Thank you!” Uhrrbet exclaimed throwing her little arms (and tail) around a somewhat uncomfortable Sheloran. “Thank you! Thank you so much!”
“It’s what I do… apparently.” Sheloran said as she hugged her back.
At least my eyes aren’t hurting anymore. That’s worth something.
***
Helen Mongrave clicked “send” on her naughty little picture with a laugh. Jon was just going to “love” that! Furries were definitely not his thing!
Hey, that rabbit was pretty cute if she did say so herself!
Chuckling to herself, she shrugged into her shoulder holster, threw on her jacket, and headed out towards her grav-car. It was an older model, but it still worked great. Besides, she loved her old junker!
At least it gave her coworkers an easy target for the ration of shit they liked to throw back and forth. She pretended it bothered her so they would keep at that instead of finding something that really stung.
As she was reaching her car she noted movement out of the corner of her eye.
Two “suits” approached. Cheap ill-fitting suits, obvious bulges from their shoulder-holsters…
Agency. She would bet her life on it.
Fuck... she thought as she unbuttoned her jacket.
“Ms. Mongrave?” a broad-shouldered human with a buzz-cut asked.
“Never heard of her,” Helen replied as she turned to face them and surveyed the area. Two agents visible, probably more.
She was fucked.
“You need to come with us, ma’am,” the man said as he reached into his jacket.
She just smiled and drew her pistol…
And promptly tried to shove it in her mouth.
Zap
A heavy-stunner bolt cut her down before she could silence herself.
Helen Mongrave, dropping her pistol, collapsed.
The two agents caught her before she hit the ground as an unmarked van screeched to a halt and the door flew open.
Within seconds, Helen was gone.
***
Jon burst into laughter as he checked his messages.
“What?” Skippy asked as she walked up and wrapped her arms around him. “Who the fuck is that bitch?” Skippy laughed as she saw the picture. “Making a move on my man? I’ll kill her!”
“I guess the cat’s out of the bag,” Jon laughed as he started decrypting the message. “Can’t keep anything from that woman,” he chuckled, "never could."
He stopped chuckling as he read. It wasn’t good. It went way deeper than he hoped.
“Jesus,” he muttered.
“That bad?”
“Worse,” Jon replied. “I don’t know how to fix this.”
Skippy flashed a toothy smile as her blades slowly extended.
“I have an idea...”
“Let’s hope it doesn’t come to that,” Jon replied. “The Republic has been though enough… Oh hey!”
“That sounds encouraging.”
“I never thought in a million years I’d say this but I fucking love Jessica Morgan!” he said as he pointed at the screen.
“Wow...” Skippy replied. “That’s a shitload of money!”
“I wonder how loyal her inner circle really is?” he chuckled.
“Why don’t you ask that bitch in the hold?”
“According to her they are like a cult,” Jon replied, “completely unshakable.”
“They thought the same about her, you know,” Skippy grinned. “I wonder how many other ‘unhappy diners’ there are?”
“Dare to dream...” Jon replied as he pulled Skippy onto his lap.
“What?” Skippy asked. “That picture get your motor running?”
“Nah,” Jon said as he pulled her in for a kiss. “I got the real thing right here.”
Skippy giggled as she started to pull off his t-shirt.
Jon’s communicator started to ring.
“Goddammit,” he muttered as Skippy just signed, nuzzled his neck, and started to get dressed.
Jon looked at the screen and frowned. Rasheed was calling? On a live connection?
That wasn’t good.
“Lubricants Unlimited customer service department,” Jon answered. “Your asshole is our asshole!”
“Jon,” Rasheed said grimly, “They got Helen.”
“What?!?”
“Grabbed her about an hour ago. They are accusing her of treason and conspiring against the Republic.”
“Isn’t that a bit redundant?” Jon replied.
“This is serious, Jon! She knows everything! If she talks...”
“It’s a lot worse than just serious,” Jon said with a frown, “However, if they are doing this officially, then she’s probably in the system somewhere. Everyone breaks but it’s going to take time to crack her open. Find her. We’ll handle the rest.”
“Ok. We’ll find her,” Rasheed said regaining his composure.
“Don’t be a hero, Rasheed,” Jon said grimly. “If it looks like it’s getting too warm, you guys need to bolt. We don’t need to compound the tragedy.”
“If we run, we lose the agency,” Rasheed replied. “I’m not handing over Republic Intel to that bitch!”
“We might not have a choice,” Jon replied. “If you can’t locate her, go. I’d rather lose the agency than lose the agency and some damn good operatives and analysts.”
Rasheed’s worried face suddenly broke into a wry smile.
“What?”
“Since we are technically ‘criminals’,” he replied, “Why don’t we call in the big guns?”
“Huh?”
“Question,” Rasheed said as his smile grew. “which criminal did you keep a holo of on your desk?”
“I like the idea but they don’t operate in the Republic,” Jon replied.
“Yeah,” Rasheed said with a grin, “about that...”
***
In a hollowed out asteroid on the outskirts of Sol, Harval Smythe and a motley assortment of humans and xenos all stood anxiously beside it…
Absolute perfection… The single greatest achievement of his life.
A flaxen beauty with the most frightening eyes he had even seen in his life silently walked beside it lightly running her fingers along the hull.
“We worked around the clock, ma’am,” he said nervously, unnerved by her silence.
“I paid for quality, not haste,” she said in a leaden voice.
What the hell was she? he thought as he was filled with dread. Something was seriously wrong with her.
“It’s… perfect, ma’am,” he stammered as his crew all nodded furiously. “We have all of the NDT results and diagnostics right here,” he said as he handed her a tablet.
Gloria took it and after a few moments she looked up, her eyes flashing with anger.
He flinched. He thought the dead eyes were bad. These were worse!
“These results are not expected. You have deviated from my specifications. I am… displeased.”
Fear gripped his heart. There was little doubt what that might mean.
“Y-yes… we made some adjustments… Improvements!” he yelped. “Look!” he gestured at the tablet. “We increased power output by fifteen percent and your thrust to weight ratio has increased significantly! And we added safety features!”
“Safety?” she hissed advancing upon him slowly.
“Oh shit,” a large black man muttered as he picked up a communicator, “Shelia?” he said urgently. “You might want to get down here! Gloria is about to go Yellowstone!”
“Fuck,” an annoyed voice replied. “Stop her.”
“No way!” the giant exclaimed. “She’s in her unhappy place!”
“The exposure levels in the cockpit were completely unacceptable!” Harval yelped as he backed away, “We added a modified reactor shielding unit around the cockpit! The increased power levels more than make up for it and it reduces your net signal emissions by two percent! Look! Please for the love of God look!…" he begged as Gloria slowly kept walking towards him with glassy porcelain like eyes. "Look at the specs you stupid bitch!” He screamed, suddenly enraged. He had created a masterpiece, goddammit!
“Oh no,” a small brunette gasped quietly as she looked away.
Gloria blinked in surprise and looked at the tablet again. There was the briefest flicker of life in her eyes and then with a slow exhale they glazed over again.
“I’m taking it out,” she said after a few moments.
“Yes! Please!” Harval exclaimed.
“Tell T’sunk’al to try to find me,” she said as she climbed inside the sleek black ship.
There was absolutely no sound as it powered up. The hangar doors opened and before they had stopped moving the ship was gone leaving nothing but a small hurricane as it left.
“Fuck!” Jessie screamed as she dove for cover.
Outside the black ship banked, rolled and dived with ever increasing speed.
“We just got pinged.” T’sunk’al said in his trademark unflappable tone. “Range… One-hundred yards?!?… Hyperspace event! Range… unknown!… She got us again… Range… No way!” he exclaimed. “Fifty yards?!?”
The Paper Tiger shuddered.
“She just rubbed our shields!” the chief shouted, “Crazy bitch!”
“Hyperspace event!” T’sunk’al yelled. “Close enough to flash our shields!”
The ship shuddered again.
“Fucking stop that!” the chief yelled into the microphone.
“Where the fuck is she?!?” T’sunk’al yelled, his normally unflappable nature thoroughly flapped.
“Hyperspace event!” he shouted. “How the hell is she jumping so fast?”
“She’s fluttering the banks!” the chief said shaking his head, “Recharging them with the surge from the shields as she slams through space time! I’ve heard rumors about this but I’ve never actually seen it done before. It’s suicide! One fraction of a second off and… boom! It takes a true master to even think about pulling it off and even so, those banks must be made out of unicorn hooves or something! Where is she venting the heat? She can’t be sitting in it, right? Not even she would cook herself, would she?”
WHAM
“What the fuck was that?!?” Sheila yelled.
“Direct contact to our shields with the hull of the ship,” the chief shouted angrily. “She missed us by less than a meter!” He grabbed the mic. “Goddammit! If you fry the shields you are the one cleaning the conduits!”
“We just got painted by direct targeting,” T’sunk’al said, “range… Hyperspace event!… We’re painted… From the other side!… Range… Oh I don’t even fucking care anymore…”
***
Harval and about a dozen very nervous men and women of several races stood nervously in the shop bay.
Suddenly there was a blast of wind…
And the ship was there, so fast that nobody really saw it pull in.
It landed, and Gloria stepped out, eyes as dead as ever.
She walked up to Harval…
“So… Is it-”
Before he could react Gloria lunged…
And gently kissed him on the lips.
He stared in disbelief.
Her eyes were as dead as ever…
But there were tears running down her cheeks.
Without a word she pulled out a transactor…
“Rerun all diagnostics,” she said without emotion. “Recheck the frame. I’ll pay double for your time.”
“Yes, ma’am!”
***
“You crazy bit-” the chief started to yell as Gloria entered the Tiger, and then fell silent.
Gloria, the brigand, the psychopath, was gone.
It was Gloria, the Ice Queen, Gloria the Undying, Lieutenant Samuels, the Lich Queen, the Angel of Death, who stepped aboard.
“Jessie,” Gloria said in a cold dead voice almost like the one she always used, “Do you have targets for me?”
“Um… Yeah,” Jessie said quietly just staring at her.
“Lieutenant,” the chief said briskly. “I’ve confirmed the measurements. We can just barely fit your ship in the hold, barely. I would say that it would be impossible to actually land in here but I doubt it will be an issue.”
“How much room for munitions?” Lieutenant Samuels asked calmly.
“We can carry two complete loadouts, at least, maybe more if we install roof racks.”
“Excellent, Chief,” Gloria the Revenant, replied with a faint smile. “Give me a couple of feet. You can have the rest.”
“Yes, ma’am,” the chief said before he caught himself with a wince. He didn’t mean to do that!
“Welcome back, Lieutenant,” Sheila said with a smile.
There was the briefest flicker in The Lich Queen’s eyes as she simply nodded in reply, then it was gone.
submitted by slightlyassholic to HFY [link] [comments]

Ultimate Gambling Guide for GTA Online - odds, probabilities, and optimal strategies

This is not mine, the creator of this is u/enderpiet
​
Since the Diamond Casino update, I have seen a large number of 12-year-olds posting Blackjack memes on this sub. As a parent, this has me very worried.
On top of that, I have seen some of the most trustworthy GTA Youtubers giving flawed gambling advice, which can have damaging impact on their gullible audiences.
So that's why I decided to write this up, to educate everyone on the subject, so there will be no more misunderstandings.
(2020 Update down at the bottom.)
If you're one of those Youtubers that wants to use this information in a video, feel free to do so. The more people (especially kids) that become educated about gambling, the better.
But then also please go back and review your own work, and delete or edit the videos that are giving out the wrong advice, like where you're saying you have "a good strategy for making money with roulette", or some other nonsense that I've heard this week. Delete that please.
Before I get into the individual games, I need to discuss a few concepts first, that will make understanding the rest a lot easier.
Expected return and variance
A game like Roulette or Slots has a fixed expected return on your bets. This is a percentage that you have no way of influencing. Say you are flipping a coin against a friend, and you both put up $1. The winner gets the pot. Since the odds are even at 50%, in the long run, you will expect to break even. Your expected return is 100% of your bet.
But imagine if you would play this coin flipping game in a casino against the house. On the "house rules" listed at the table they would probably say that you would only get 95 cents back for every win, while you are forfeiting a dollar on every loss. Would you still play?
Sounds stupid to do so, but still, everybody does it. Every bet they place on Roulette, every coin they put into a Slot machine, is based on the same concept.
Those few cents they take on every bet are their profit margin, and has paid for all the Vegas lights, the Mirage volcanoes, and the Bellagio fountains. Make no mistake - casino gambling games are not designed to make you lose, because sure, you can get lucky on a single night, but they are designed to make them win. That's the beauty of it. They can both exist at the same time.
Too many people that don't see how this works, are just destined for disaster. Just because you went on a lucky streak and won 8 games out of 10, does not mean that flipping coins is a profitable game, or that choosing tails is a winning strategy. Always be aware of the house edge, your true chances of winning, and just realize that you got lucky. There is no such thing as a strategy in flipping a coin that will give you a higher expected return, so it's just pure gambling, just like Slots and Roulette.
Most casino games are made in such a way, that your expected return is a little under 100%. This means that from every dollar bet at the tables, the casino expects to keep a few cents. For individual players, results may vary. Some will win, most will lose. But for the house, it doesn't matter. They take millions of bets each day, so for them, the expected average works out a lot sooner. In short: the house always wins.
When looking at the house edge, we're talking about the expected long-term result, based on the game's house rules. But for a player, it can take literally tens of thousands of hands or spins before you also reach this average number. Until that time, you can experience huge upswings and downswings, that are the result of nothing but short-term luck, which is called variance.
Some games and some bets have a much higher variance than others, which means your actual results will differ enormously from what you're expected to be at.
Take for example betting on red/black at the Roulette table. This is a low-variance proposition, because it has a high percentage chance of occurring, and a low payout.
Contrast this with betting single numbers in Roulette, which only win once every 38 spins on average. This bet has a much higher variance, meaning you can easily hit a dry spell, and not hit anything for 200 bets in a row, or you can see a single number hit three times in five consecutive spins. This is not a freak occurrence in high-variance bets.
Even though the expected return in both these bets is exactly the same, there's a huge difference in variance, causing massive differences in short-term results, which can go both ways. You need to be aware of this, before you decide what types of bets you are comfortable with placing.
Gamblers' Fallacy
Another thing to realize, is that each individual game, hand, or spin, is completely independent from the one(s) before it, and after it.
Gamblers tend to believe, that the chance of a certain outcome is increased, based on previous results.
The most famous example comes from the Casino de Monte Carlo, where the Roulette wheel managed to land on black 26 times in a row. Gamblers lost many millions during that streak, all frantically betting on red, believing that the odds were in favor of the wheel coming out on red, after producing so many blacks. This is not true. Each round is completely independent, and the odds are exactly the same.
You will hear people say things like a Blackjack table being "hot" or "cold", which is completely superstitious, and should be ignored. The exception was when Blackjack was being dealt from a shoe. It made card counting possible. But with the introduction of shuffle machines, and continuous shuffling like is being used in GTA, this no longer exists.
This is also why "chasing your losses" is a very bad idea. After being on a losing streak for some time, many gamblers believe that now it's their turn to start winning. So they will often increase their bet size, believing that when their predicted winning streak comes around, they will win back their losses, and more.
The reality of it, more often than not, is that people will indeed start playing higher and higher limits, until they are completely broke. Nobody is ever "due for a win". There is never a guarantee that you're about to start winning. In fact, the opposite is more likely to be true. You are, after all, in a casino.
Betting systems
Some people like to think that they have a fool-proof betting system, like the Martingale system. Simply increase or even double your bet when you lose, and keep doing that until you win. In theory, this system will always win. So that's why table limits were introduced, and where the system fails.
If you start at the Roulette table, playing red/black, with a small 750 chip wager, and just double your bet every time you lose, you only have to lose 6 times in a row, before you will be betting the table limit of 48,000, just to get that 750 chip profit.
Sure, you can go on all evening without this happening, winning 750 chips each time, but this losing streak only has to happen once, and you're bust. Any betting system like this is ill-advised, because you are hugely increasing your so-called "risk of ruin", and that's what we were trying to avoid.
And even if your starting bet is only 100 chips, after only nine straight losses, and nine doubled bets, you are betting the table limit at 50,000 chips. If you lose that bet, you're 100,000 chips in the hole, with no way to recover that with your 100 chip base wager.
So don't believe anyone that says this is the perfect system to always win in the casino. Sooner or later they will understand why they were wrong, when they're asking you for a loan.
Set your limits BEFORE you start playing
One final point before we get into the games, a general tip for people that head out to play: money management.
Just like in real life, before you go to the casino, decide on a maximum amount that you are WILLING TO LOSE.
Bet small enough, so that amount can last you through the entire evening, and you will not be tempted to run to the ATM to continue playing.
Considering GTA money, some people will be comfortable losing 1% of their GTA bank balance, some people will be comfortable with gambling away 5% of their total GTA savings. It's up to you what you can handle. Decide for yourself where it will start to hurt, and don't cross that line.
But whatever number you decide on, as soon as you lost that amount, get up and walk away. Don't chase your losses, stick to your limits, and accept that this has not been your day. There is always another game tomorrow. Always agree with yourself on a simple stop-loss rule, how much you would want to lose at most, and simply stop playing when you get there.
Same goes for winning. You can decide on a number, how much profit you would like to take away from the casino. You can go on a hot streak and be up half a million in a short period of time, but if you would continue to play longer, looking for more, chances are that you're going to lose it all back.
Most people are happy with doubling their daily casino budget, for example. Others are looking for 10 bets profit in Blackjack. Whatever you choose, when you hit that number, you can stop playing and bank your profits, or you can continue playing if you're still enjoying the games, but then only just play minimum bet sizes. Then you're just playing for fun, not for money. You've already made your profit, so simply keep it in your pocket, and don't risk losing it again.
Either way, decide on what your money management strategy will be, and STICK TO IT.
Casino games in GTA Online
Now, I'm going to dive into the games that you can find at the Diamond casino, ordered from worst to best.
6) Slots
Generally the rule is this: the less strategy a game has, the worse it is for the player. And with slots, this is definitely the case.
The only influence you have, is choosing what type of machine you're going to play. Basically, there are two types of slot machines:
-high frequency, low payout slots
-low frequency, high payout slots
In the first type, there is no huge (progressive) jackpot on offer, just your average selection of prizes that don't go up to crazy amounts.
This will result in a player having many more spins resulting in a win. The amounts that you win on the bigger prizes, will be smaller, but they do come around more often. This type of slot machine has a lower variance, which means that your money should last you longer, winning many smaller prizes along the way to keep you going.
The second type of slot machine lures you in with the temptation of a huge jackpot prize. Even though the long-term expected return on these machines is the same as the previous type, the prize distribution is hugely different. The large jackpot prize weighs heavily on the scale of expected return, but the chance of it hitting is extremely small. This results in a much higher variance on this type of machine. Usually your money will go down very fast, because the smaller prizes are less rewarding than on the other type of machine.
At the Diamond, the info screen says the player return at slots is set at 98.7%. This means that, on average, for every maximum bet of 2,500 chips, you expect to lose 32.5 chips.
This might not seem like a lot, but the danger of slots is that the game is extremely fast. You can spin about once every 6 seconds, which would result in an expected LOSS of about 20,000 chips per hour of playing.
But again, in this long-term expected number, the large jackpot awards are also factored in, and as long as you don't hit those big prizes, you'll see your money go down a lot faster.
In any case, thank heavens the max bet is only set at 2,500, or else we would see more players go bankrupt at alarming rates.
Optimal strategy for slots:
There is none. Because after betting, you have no more influence over the outcome. The only choices you have, is what type of machine you want to play at, and how much money you are going to risk. And those are all personal preference. As long as you stick to your loss limits, as discussed above, there's no harm in having a go every once in a while, hoping to get a lucky hit. Just realize that you don't have a high chance of scoring a big win, so as soon as you do, get up and walk away.
5) Roulette
Roulette is also a game where you have no influence over the outcome. There is zero skill involved. You place your bet, and that's it.
In traditional French roulette, a table has only the single-zero, but of course, for American casinos that wasn't enough of a house edge, so they simply doubled their profits by adding a second zero. The house edge was increased from 1/37 to 1/19, which is huge.
This makes playing on a double-zero roulette table by definition a sucker's play.
The payouts scale evenly, which means that a bet on a single number, and a bet on half of the numbers, and everything in between, yields the same expected return. The only difference, again, being the variance that you are willing to subject yourself to.
The player return for double-zero Roulette for all bets is 94.74%.
Except for the 5-number bet, which can only be made by placing a bet on the two top rows that contain 0, 00, 1, 2 and 3. The expected return on this bet is lower: 92.1%. This is because it only pays out 6-1. Why? Well, the number 36 isn't divisible by 5, so the greedy people that came up with double-zero Roulette had to round it off someway, and as expected, it wasn't going to be in the players' favor.Just remember that that 5-number bet is the worst bet at the table, and should be avoided. All other possible bets have the same expected return.
So it really doesn't matter how you spread your bets, if you bet only one chip, or if you litter the entire table with a bucketload of chips. Each chip you put out there, has the same expected return, so there is no strategy that will improve your long-term results.
Assuming that you're betting the maximum table amount of 50,000 chips, you will be looking at an expected loss of about 2,630 chips per spin. Considering that a round takes about 45 seconds to complete, your expected LOSS at the GTA Roulette tables will be around 200,000 chips per hour of playing.
Optimal strategy for double-zero roulette:
Stay away. Stay far away.
4) Three Card Poker
With Three Card Poker, we come across the first game where there is actually some strategy involved. You get to look at your cards, and then decide if you want to fold, and surrender your ante, or double your bet.
Additionally, you can choose to place a side bet on "Pair Plus", which offers progressive payouts.
There are some websites out there that ran all the numbers with computer simulations, and even though I would like to quote the source here, these websites are understandably littered to the max with online casino ads, so that's why I have decided against doing that.
Optimal strategy for Three Card Poker:
For this game you only have to remember one strategy rule: Always bet on any high card queen-six-four or better, and fold any high card queen-six-three or lower. That's it. Just don't forget to double check if you're not folding a straight or a flush, and you'll be fine.
This strategy will result in an expected return of 96.63%.
The Pair Plus sidebet, with the payout table that is used at the Diamond casino, gives you an expected return of 97.68%, which is actually a bit better than the main ante bet.
So by playing both wagers, you're reducing your expected losses per bet, but since you're betting more, you're also increasing your expected loss per hour.
My advice would obviously be to not play this game at all, but if you do, put as much of your bet as possible on the Pair Plus, while making our Ante bet as small as you can.
To be able to compare it to the other games at the Diamond, let's stay on that 50,000 maximum wager, meaning making your ante bet 35,000, and your pair plus bet 15,000, if the table would allow it.
This results in an expected loss of about 1,525 chips per hand, and with a round taking about 45 seconds, this adds up to an expected LOSS of around 120,000 chips per hour of playing. In comparison, if you would only play the ante bet for 50,000 per hand, you expect to lose 1,685 chips per hand, which means an expected LOSS of about 135,000 chips per hour. So the more out of that 50,000 wager you can put on the "Pair Plus" sidebet, the better.
Even though it may be fun to try out this game for a bit, since there's only one simple strategy rule to follow, you'll soon find yourself robotically grinding down your bankroll until it has vaporized. You're not missing out on anything if you skip these tables, there is no real challenge.
Just like with Roulette and Slots, if you want to try it out nonetheless, you can just bet the minimum amounts and only play for fun, so it won't matter if you win or lose.
3) Blackjack
Blackjack is the most complicated game by far. Simply because the player has to make a series of decisions, which will largely decide the outcome. Luckily, there is such a thing as an optimal strategy, which will be outlined below.
However, the strategy is also dependent on the house rules. These not only affect your expected return, but in some places also your decisions.
Here are the house rules at the Diamond casino:
-The game uses 4 standard decks, and a continuous shuffle.
-Blackjack pays 3 to 2, dealer checks for early blackjack.
-No insurance offered, no surrender.
-Dealer stands on soft 17.
-Double down on any two cards.
-Player can split only once, but doubling after split is allowed.
-Seven-Card Charlie.
Under these rules, and following the "basic strategy" chart, your expected return at Blackjack is a shade under 99.6%, which is extremely good for a casino game, that's why Blackjack should be your table game of choice.
But it comes at a price: you are going to have to memorize the relatively complicated strategy chart, or at least stick it to your monitor until you have it in your head. But in case you ever stumble into a real-life casino, you won't regret having this table memorized, so I would definitely advise you to work on that.
The strategy chart might look complicated at first, but you will be able to notice certain patterns. Your decisions are mainly based on the dealer's upcard, which is basically divided into a weak card (2 to 6), and a strong card (7 to ace).
When a dealer shows a strong card, you will be hitting more often with the risk of going bust, but when a dealer shows a weak card, you're not taking that risk, and you will be standing more, but also doubling and splitting more. You want to increase your bets when the odds are in your favor, and get out cheap when they're not.
But it also helps to take some time to think about why a certain advice is given. For example, why does it say that you always have to split two eights, even against an ace. Well, that's because two eights equals 16, which is the worst total you can have. It's better to split them up, and give yourself a chance of finding a 17, 18 or 19 with the next card. Once you see the logic in that, you'll have one less thing to memorize.
The playing advice in the basic strategy chart is a result of computer simulations that ran all possible outcomes against each other, and produced the most profitable decision for each situation. So you can't go wrong following it.
Optimal strategy for Blackjack with Seven-Card Charlie
The added house rule of Seven-Card Charlie, adds a small advantage for the player, and it does influence a few strategy decisions. For example, you might have a 14 with 6 cards, against the dealer's 5 upcard.
Normally this would be an automatic stand, but if you're only one card away from the Seven-Card Charlie, meaning an instant win for the player, regardless of the dealer's hand, it turns it into a hit.
Here's the most optimal strategy chart to follow for the Diamond Casino house rules:https://prnt.sc/olct6g
You'll see that two fives are missing from the chart, and that's because you never split them. You treat them as a regular 10. You also never split tens. Just stand on 20.
If you follow this strategy religiously, even with a maximum wager of 50,000 chips, you only expect to lose about 215 chips per hand, and with rounds taking about 30 seconds, that amounts to an expected LOSS of 26,000 chips per hour, which is only half a bet. A small price to pay for an hour of entertainment.
But since the expected return is so extremely close to 100%, you will see more positive short-term results than with other games. But obviously it can also swing the other way. Again, this is supposed to be the game where your money lasts you the longest, but always set your loss and win limits before you sit down. That rule simply always applies.
Still, even with optimal strategies applied, all these games are expected to lose you money in the long run. So betting any kind of large amounts is not advised. If you simply want to enjoy playing these games, there's nothing wrong with betting a minimal amount. Playing these games for a longer period of time will already cost you money anyway, since your daily property fees will still be charged while you're playing in the GTA casino. As long as you can play for fun, there's nothing wrong, but when you see yourself betting insane chunks of your entire bank balance to try to recoup some unfortunate losses, you're doing it wrong.
As the commercials in Britain all correctly say: when the fun stops, stop.
2) Virtual Horse Racing
Now onto the good stuff. I ran some numbers, and I believe Rockstar has made a mistake with the horse racing game. Because as it stands, and if I read the numbers correctly, this game is actually profitable for the player. You can actually make money with this, at least, until Rockstar figures out their mistake and patches it.
If anyone wants to jump into the math and double check this to make sure, please do so. I will add any corrections to this post. This is one of those "to good to be true" things, so I keep thinking that I might have overlooked something. So please verify it if you can.
The setup is this. There is a pool of 100 horses, each with their own attached payout. These are divided into 3 groups, ranked by their odds. From each group, 2 horses are randomly selected to provide a pool of six runners for you to bet on.
Now it's not an actual race you're looking at. You are looking at a raffle. This is important to realize.
Each horse gets awarded a certain number of raffle tickets. The favorites get awarded more tickets than the underdogs, and therefore, have a higher chance of winning.
If this distribution works like it does in the real-life casinos, then the raffle tickets are awarded according to the betting odds.
Example 1: imagine a race with 3 runners, all have 2/1 odds, representing a 33.3% chance of winning. (Because 2/1 means 2 AGAINST 1, so 3 total.) In this case, each horse gets one third of the raffle tickets, giving them an equal chance to win.
Example 2: imagine a race with 3 runners, one has 1/1 odds (or EVENS), representing a 50% chance of winning, and the other two horses are marked up as 3/1, with a 25% chance of winning. The favorite gets half the tickets, the other two get a quarter of the tickets each.
A ticket is drawn, and you'll have a winner.
It doesn't matter in this game which horse you bet on, because the expected return is always the same: 100% or break-even, for the above examples.
Now, what happens if the percentages don't exactly add up to 100%?
They must add up to 100%, because there will always be a winner. And only one winner.
So when this is the case, the actual winning chances of the horses are adjusted to meet the 100% requirement, using their payout odds to determine the scale.
So, if the represented percentages add up to more than 100%, the actual winning chances of the runners will be DECREASED, resulting in all bets becoming losing propositions for the players.
Example: In a 6-horse race, all runners are listed at 4/1, representing a 20% chance. Only with six runners that amounts to 120%. So all chances are scaled down by 1/6th, to end up at 100%.
This means your horse's chances are reduced from 20% to 16.67%, turning it into a losing bet: 5 times you will lose your bet, and 1 time you will win, but only get 4 bets back in this instance, instead of 5. A losing bet in the long run.
This is the type of odds that you find in regular casinos, with fields as large as 15 runners to bet on, where the assumed winning chances always add up to more than 100%, therefore are decreased for all runners, resulting in a house edge.
But in GTA Online's Inside Track, there are other scenarios, because of the small field, and the way that they are put together.
In some cases, the represented percentages when added up, are LESS than 100%, meaning that the actual winning chances of all runners, are INCREASED.
This creates profitable bets for the players, because in the long run, you're expecting to win more money than you lose. This is a gambler's dream, pure and simple.
So, according to the in-game information, the three groups of horses are divided as follows:
-Favorites: EVENS to 5-1
-Outsiders: 6-1 to 15-1
-Underdogs: 16-1 to 30-1
Let's take the two most extreme examples to show what's happening.
The worst possible field to bet on: two runners at EVENS, two runners at 6-1, and two runners at 16-1.
EVENS represents a 50% chance, 6-1 is 14.29%, and 16-1 is 5.88%. Add those up and you land on a total of 140.34%.
This means that the actual winning chances of the horses are decreased by 28.75% (to get that 140% down to 100%), which makes betting on this field extremely unwise.
A horse at EVENS will only come in as a winner 35.63% of the time, instead of 50%,
a horse at 6-1 will only win 10.18% of the time,
and an underdog at 16-1 will only win 4.19% of the time.
The expected return on a bet on any of the horses in this field is only 71.26%, so a maximum bet of 10,000 chips on any of these horses holds an expected LOSS of 2,875 chips.
These returns are the same, because the winning chances are scaled equally, according to the payout numbers. So it really doesn't matter which horse you bet on, in the long run, you expect the same results.
But as explained before, it does influence variance, and therefore your short-term result, which can swing both ways.
But now, the best possible field to bet on: two runners at 5-1, two runners at 15-1, and two runners at 30-1.
Odds at 5-1 represents a winning chance of 16.67%, 15-1 odds means 6.25% chance, and 30-1 odds means a 3.23% chance of winning. Add these six horses together, and you only get 52.285%.
This means that, to get from 52% to 100%, the actual winning chances of these horses will be almost doubled! Multiplied by 1.91 to be exact.
So the 5-1 favorites will now win 31.88% of the time, instead of 16.67%,
the 15-1 runners will win 11.95% of the time,
and the underdogs at 30-1 odds will still win 6.17% of the time.
When betting on this field, the expected return on your bet is 191.25%!
This means that a max bet of 10,000 chips will result in an expected PROFIT of 9,125 chips.
This is printing money, if there ever was such a thing.
Optimal strategy for Virtual Horse racing
So all you have to do, is only bet high on the games where you have an expected positive return, and bet the absolute minimum on the games where your expected return is negative. Or back out of the racing game to refresh the field.
If you don't have a way to quickly add up all the percentages, and until somebody shows up here with a neatly formatted table, just use a few general rules of thumb:
-Always bet the maximum on a race with favorites at 2/1 and 3/1 or higher in it.
-Simply skip all races with two favorites at EVENS in it, and at EVENS and 2/1. Or bet the minimum, if you can't skip or refresh the field.
-To decide if you should play races with other favorite combinations EVENS and 3/1, EVENS and 4/1, EVENS and 5/1, or two favorites at 2/1, the payouts on the other four runners determine whether or not it's profitable to play them. The results of betting on these fields vary from an expected 1,330 chip loss (worst-case) to an expected 1,680 chip win (best-case), with a max bet of 10,000 chips.
But if you're not looking for another strategy chart, you might just want to skip these borderline cases, and just cherry pick the best ones, which are easy to recognize, and with which you can never go wrong.
It's difficult to put a number on an expected win-rate, because it all depends on which fields you get presented with, but it's not unreasonable to state that you can maintain a steady win-rate of around 200,000 chips per hour, with about 50 seconds per race.
Remember, you're not trying to win every race. You're trying to win the most money per hour. So don't sweat it when you bet on a 4/1 favorite, and lose a couple of races in a row. It will still be more profitable in the long run. You have the math on your side.
To reduce negative variance, always bet on the favorite, when betting on profitable fields. We're not gambling anymore, we're grinding out a steady profit. We want to keep the swings to a minimum.
I contacted Rockstar support to verify if this is indeed how it works, but the only reply I got after 6 weeks is that they were "looking into it".
User u/Garsant made a useful Excel-worksheet, available for you to download, where you can quickly type in the payouts on the horses, to see if it produces a profitable bet or not. You can find it in his post here: https://www.reddit.com/gtaonline/comments/ekp8na/gta_online_inside_track_odd_calculato
1) Wheel of Fortune
The number one profitable casino game in GTA Online is obviously the Wheel of Fortune, because it costs you nothing to play.
Unfortunately, you only get one free spin per day, but it holds great value, so make sure you do it.
With a chance to win a super car, vehicle discounts, expensive mystery prizes (which also can be vehicles), and a lot of cash and chips, the expected return on a single spin is around $100,000 in value.
So don't forget your daily spin, it's definitely worth your time.
2020 Update:
As of the Diamond Casino Heist update, the Inside Track horse racing is confirmed to still be as profitable as outlined above.The only thing that seems to be changed, is that you can't refresh the field anymore by backing out of the screen. This does affect your hourly rate in a negative way, but does not change the fact that this game has a huge positive expected return, and should be your go-to when you're trying to take money from the house, without having Lester's nagging voice in your ear. That should also be worth something.
And with that, I conclude my 5,000 word essay on gambling in GTA. Questions, comments, feel free to add your input to this guide.
Cliffs:
-Gambling games should only be played for fun, not for big money. You should expect to lose in the long run. The house always wins.
-A casino game doesn't have a memory, and betting systems don't work.
-Set your limits before you start, how much you are willing to lose or win, and then walk away when you get there.
-Don't play slots, roulette, or three card poker.
-Only play blackjack following a basic strategy chart (https://prnt.sc/olct6g).
-Inside Track betting can be played profitably, if you only bet on fields WITHOUT a heavy favorite.
-Wheel of Fortune is always your best bet, because it's a free bet.
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