Artificial intelligence systems like ChatGPT could soon run out of what keeps making them smarter — the tens of trillions of words people have written and shared online.
A new study released Thursday by research group Epoch AI projects that tech companies will exhaust the supply of publicly available training data for AI language models by roughly the turn of the decade – sometime between 2026 and 2032.
Comparing it to a “literal gold rush” that depletes finite natural resources, Tamay Besiroglu, an author of the study, said the AI field might face challenges in maintaining its current pace of progress once it drains the reserves of human-generated writing.
In the short term, tech companies like ChatGPT-maker OpenAI and Google are racing to secure and sometimes pay for high-quality data sources to train their AI large language models – for instance, by signing deals to tap into the steady flow of sentences coming out of Reddit forums and news media outlets.
In the longer term, there won’t be enough new blogs, news articles and social media commentary to sustain the current trajectory of AI development, putting pressure on companies to tap into sensitive data now considered private — such as emails or text messages — or relying on less-reliable “synthetic data” spit out by the chatbots themselves.
Good critique.
Well, for one, the whole publishing industry is struggling and writers in general are struggling to make money. They could start financing the arts they’re ostensibly taking so much from to train their models. In doing so they could create an explosion of new, quality literature and journalism. It could change the face of a dying industry and revitalize and reshape it. However, it would require the “benevolence” (*slight retch) of tech moguls to accept that perhaps the people producing the content they train their AI on should be properly compensated.
The reason to pay a special rate would be to support the arts and produce new, quality text of all varieties to train on. Available internet training data is easily and cheaply accessible, but less quality, and quickly being diluted by websites auto-generated by AI, causing AI to be trained on AI. By “financing the arts” you would produce quality PR for your company as well as making a short pathway to a constant churn of new content for your models. You could even extend this to scientific publishing, to go beyond the arts and into financing science publishing.
Especially considering there are many continued lawsuits about abuse of copyright to train the models. Everyone knew where the books3 corpus came from, it was known from the beginning that it was all pirated books from Bibliotik, all these groups really shot themselves in the foot by using a well-known pirated document of thousands of copyrighted books for training. They could make all those lawsuits go away with agreements with writers, journalists, and publishers and come out looking like heroes for saving the entire publishing industry and helping clean up the internet and publishing by prioritizing quality, well-written content.
This assumes that there is a general level of benevolence and altruism in tech companies. There might be some, but probably not enough.
I should say that I absolutely would love if your idea (or credit to the original creator) actually happen. It would be fantastic and I would much prefer that world to what I think we’re going to get.
I think my original two questions still stand:
Does journalism/arts/scientific publishing produce enough content and varied enough content to be sufficient to training the models? I doubt it because let’s say there are 500,000,000 (500M) authors/creators that could be supported by their efforts. That’s a small number compared to several billion people posting on social media, blogs, forums, etc. They also post on a much more broad set of topics. If the tech companies were benevolent and did pay for content, how many more authors and creators could they create? Let’s say they double it, that’s another 500M people (we’ll assume that many more people are even available for these professions). They all need salaries let’s say they each make 60000/year. That’s 30 trillion in expenses/salaries. Even playing with the numbers some, half the people, half the salary and the number is still in the trillions. And that’s probably still not enough content and isn’t even close to the output of several billion people. I think the actual solution would be to partner with social media companies (like they already are) to find ways of inticing more participation to get additional data, but even that probably isn’t enough if we believe the original study
Why partner with newspapers, scientific journals, whatever for likely pretty high fees? Currently, they can subscribe to all the journals, newspapers, etc for probably less than a million/year. That’s cheap for them, they probably already did it. They are probably paying reddit more than that alone. Right now, Facebook is probably negotiating on their treasure trove to get Zuckerberg his next billion dollar bonus.
Overall, I don’t think they are interested in quality data, I think they just want more. Pretty soon they will have consumed everything ever produced (that’s in a format that can be digested) and humanity it’s entirety will not be able to produce data fast enough. At that point, they will probably start producing their own content and asking humans what is valuable and what is not. By 2040, your favorite author may be a machine and the NY best sellers may be a way to determine which AI content is good enough to train the next Gen on.