Be wary of OpenAI's tactics. Test their new model on unsolved problems, not known problems. It's known that AI vendors are training on many prewritten solutions from paid labor. OpenAI states it is "a new training dataset specifically tailored for it" openai.com/index/introduc…
Other studies have shown that models will be okay if they retain the older data set within their training. I'd say that "model collapse" would appear more like bias, not nonsense.
theregister.com/2024/07/25/ai_…
Be wary of AI benchmarks. AI vendors are paying people to fine tune their models to target common benchmarks and make their product more appealing. I personally got an offer on Upwork to solve programming problems for AI. It's not real-world work.
Before reading an article, scroll to the bottom and look for a section titled "Conclusion". If you see that, don't read it. People are trashing the internet with output from AI for a quick buck, and that will hurt AI's future. Don't give attention to these careless people.
LLMs are a "generalization of everything". A major caveat to this is that they can't be clever, and there are many parallels between different topics that it will incidentally align. theguardian.com/technology/art…
A software engineer's discipline is all about achieving correctness. It's hard to picture a future where this mentally intense discipline is done automatically by technology that, by principle, has correctness problems. qit.software/will-software-…
Unfortunately there is no regulation of content pollution. Everyone wants "in" and it's going to contribute to potential model collapse. pymnts.com/artificial-int…
The profitable use is obvious: information discovery. Use AI to find things. Let your customers find things on their own, just the same as your employees. There are other uses, but this easy value should be in every business by now.
news.slashdot.org/story/24/07/11…
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