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What's the deal with all these AI training jobs?
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I'm on the job hunt right now, and my inbox seems to get littered with all these part-time remote positions to train AI models for accuracy using my scientific expertise. They require PhDs, pay $40/hr, and honestly I haven't looked into them all that much. It seems too opaque and scammy to me, but LinkedIn says "More than 100 people have applied".
So what's the deal with these things? Are they scams? Or how does it work? I see some places that Post-PhDs are doing something like this for supplemental income. Is it a worthwhile/feasible gig?
Top Comment: At least some are legitimate as I have used and been paid by them. They're just collecting and refining datasets for training language models in various domains. However, it's not great job security as it's essentially contract work and the task availability will ebb and flow with the demand from AI companies. I haven't tried to do it full time, but there's no guarantee you'll be given enough work for 40 hours/week.
About AI Training Sites
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I am only writing this post because two days ago I recommended Outlier as a side hustle and noticed that a lot of people were interested to know more about this site and the whole process.
Before you judge, I just want point out that this post is based on my personal experience and I am definitely not advertising the site or anything. I’m just providing some info for those who might be interested and nothing more.
So Outlier is basically is an AI training site but what makes it more popular than other sites is that the hiring process is fast and the acceptance rates are higher. I personally applied in a day and got the acceptance to work on the same day but in the evening.
Before you get excited, I want to pinpoint that this site require some patience and time. Why? Well, when you get assigned to a project you will need to study for it first. They provide you with documents then you get examined to see if you are suitable for the project. So yes you need to be attentive and to have some free time to do all of that.
I also want to inform you that after applying on the website you will need to do the onboarding which requires a video call exam and written exam. After passing this assessment you will have to verify your ID through persona, which is a 3rd party app used for verification.
I know all of that sounds like a lot but the pay is worth it in my opinion and it doesn’t take time like it seems but it is up to you to decide.
However, Outlier has many available jobs for native speakers, which requires being fluent in English too. There are also some STEM related jobs; biology, math, physics and I also saw that they added more specialties which you can find here.
The hourly payrate differs from each country. The highest I've seen is 50$/h and the lowest is 7.5$/h. You can also get bonuses for completing a specific number of tasks or for working for some hours.
To join Outlier you can check these jobs and PLEASE read the requirements very thoroughly and pick the most suitable one for you, and make sure your CV can pass the ATS.
So if you are interested you can use my referral link IF YOU WANT. No pressure, I only put it as some people said referring speeds up the acceptance and I also might get a reward but not sure of that tbh xD
So some of the most asked questions were:
1-Do I need a degree? I’m not sure if the degree affect your acceptance but I saw some people saying they got accepted without it. But I am sure that the degree affects your tier. And tier is related to you lvl as a contributor. T1 is a normal contributor. T2 can start as just contributor and then can be a reviewer.
2-How much can I make per week? This depends on your country and specialty. The highest I’ve seen is 45$ per hour but check the job details before applying to make sure the rate suites you. With the lowest payrate you can easily earn 200$ per week.
3-Are there other sites as Outlier? There are Alignerrr, Crowdgen, shipd AI and Data Annotation. I heard that their acceptance rates are lower and the process takes a lot of time.
One of the downsides of this site is that they are strict in any violations and can flag your account without warning.
Another downside is that projects aren’t always available and you can have no work to do for some days .
I wrote all of that because I needed some guidance when I started too. So I hope I provided some useful information!
You can ask any questions and I will try to answer.
If you are very interested, I must recommend checking their subreddit so you wouldn't waste time signing up for nothing.
Good luck and happy new year!
Top Comment: So is that freelance work? Or will there be a long term contract ? Thanks
Full time AI Training through multiple platforms?
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I've worked through Outlier AI a bit in the past training AI for software development related tasks, and it pays pretty well ($30-$50 an hour) but obviously the work can be unreliable. I'm curious if anyone has actually made a living by bouncing between platforms like Outlier, Alignerr, DataAnnotation, OpenTrain AI, etc? It seems like surely if you're active on all of them there would always be some kind of task to do to make some money.
Top Comment: I'm in the USA. I use outlier.ai(lucky with my current project), clickworker.com(a little different from the others), alignerr.ai(it depends on your skillset), rws.com(The most paperwork required), dataannotation.tech(inactive for me right now), gametester.gg(if you like to play video games and write feedback reports. You can cash in points for gift cards and bank transfers), app.crowdgen.com(a bit of a mess for some), joinstellar.ai(constant feedback in the beginning), and welocalize.com(it depends on where you live). I've been doing this fulltime since last year. In addition to those, I occasionally also use cloudresearch.com , yougov.com , pineconeresearch.com , legeropinion.com , and ipsosisay.com. They pay in gift cards. It is mostly in my downtime when I am standing around, otherwise I would be on the other platforms that pay better. YMWV
Is learning AI/ML worth it.
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I was searching about how can I learn AI/ML -self learning- , so I discovered that it will take seriously large amount of time, So I want to know if it is worth it to learn it from MIT free resources and andrew ng courses and lex Fridman, Or should I wait and get cs degree and maybe a phd in ml, or should I choose different field, I am still young but I have some programming experience in web and python, so what should I do ?
Top Comment: learn anything worth it, but for job no. the market is lock in masters-phd + experience. only big companies can afford to create new stuff, smaller ones will use what is open source stuff, so rigth now has a lot of chances, but i believe when the hype ends only the faangs or nvidia like companies will keep with new ai projects
No, kids, AI is not running out of training data
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“No, kids, AI is not running out of training data.”
I just wrote the above. And, in writing the above, I just created natural organic training data that previously did not exist. Every day, hundreds of millions of humans are creating more training data than any AI can injest. Think about the petabytes of data uploaded to YouTube, the millions of words typed into twitter by humans every day.
In addition, there’s synthetic data, data augmentation, and specialized training.
Finally, let’s assume that the opposite was true: that the world literally stopped producing new training data (absurd of course), and all we were limited to what we have. Scientists are always finding new ways to utilize the data we already have.
It feels good to some people to believe in AI collapse, but it’s naive. Rather than “running out of training data,” we’ve barely scratched the surface.
Top Comment: "no, kids" Do you ever think insulting other adults in the first line of your argument is really the best way to make a point? Also, I believe it isn't so much they are running out of data but what data they are using to train. And what they chose to train it on. Many ai companies really dance around where they have been pulling data from for good reason.
The truth about AI training and it’s implications
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This is based on a comment I just wrote that I’m posting here to make more visible:
The training is nothing more than telling the AI about what humans do in as many different contexts as possible. That’s why LLM is referred to as glorified text prediction.
Here’s the key point- nobody is stealing your work, they are just looking at what you are doing and describing it as well as possible. Yes it’s possible to infer your work from that and therefore it’s possible to breach your IP that way, but, generally speaking, the output is a prediction based on a prompt informed by as much knowledge of what people do as possible and therefore unless somebody specifically does use it to breach your IP (like as if as a photographer I took a picture of your painting and sold it as my original photography), using AI is no different to using the latest digital camera- this one takes pics of our imagination as well as pics of “the real” world to whatever philosophical degree you like.
Would you say that describing what you are doing in detail is the same as stealing your work? Or would you say that LLM’s are stealing your work as opposed to describing what you are doing in detail?
This may get to the crux of the matter and tackles a key issue regarding how an LLM actually works vs a simplified view some people might have of how an LLM is working.
I’m actually curious how antis see an LLM working that makes them think that’s theft so I’m very open to being persuaded. Naturally at the moment to me it looks more like the understandable fear of job loss is steering people from seeing that training is just describing what you do in high detail and has zero to do with your work in fact, other than your work being used to infer what you as a human in general (it has nothing to do with any human as an individual - another reason why it can’t be stealing from you) tend to do.
This is the kind of argument that wins court cases and sets legal precedent even without a strongly motivated (edit: economic) bias against the antis. The people we will actually be beating in this case will be Disney etc. as highlighted in my post about copyrighting styles.
It’s the ages old story: this is you and I vs Disney etc. it is not you vs me, as the Disney bots would have you believe.
And as you can see our alliance is complicated further due to the nature of the dead web.
In addition it’s important to keep looking a few months and years down the road and keep watching how it’s changing. For example even if you dont believe in dead web right now, as long as you can see it coming you’ll start to look out for the signs- which will allow you to start believe in it right now/ at the appropriate time. (To put this another way- the court cases that will determine policy and regulation etc. won’t have anything to do with AI or AI ethics, it will be about international politics and economics. That’s why Disney is a genuine contender here but ultimately it’s still nonsense when you imagine where this tech will be in 5, 10 years. The real threat is slaughterbots, government response to slaughterbots etc.)
Where were the antis when text prediction first came out? I don’t remember protests back then in support of writers. Perhaps if action had been taken then we wouldn’t be in this situation now. However, the same reasons why that would have been considered nonsense at the time may still apply.
Top Comment: It's what I have been telling people, Making descriptions of someone else's work and automating that process and encoding it into mathematical values does not break copyright. Sadly, most Anti-AI will never entertain this fact. As the saying goes: "It is difficult to get a man to understand something when his salary depends on not understanding it" They would prefer to cling to moral and ethical arguments, regardless of its inaccuracies, as it has a higher chance of getting sympathy. By saying that AI is theft, it tries to shut down any arguments as it appeals to morality. Sadly, Art is apparently a sacred ground, unlike science and technology. If you want to learn physics, anyone can learn it, be it AI or human. But for Art, you can only be human.