This. They could obviously reset to original performance (what, they don't have backups?), it's just more cost-efficient to have crappier answers. Yay, turbo AI enshittification...
Just for the fun of it, I argued with chatgpt saying it’s not really a self learning ai, 3.5 agreed that it’s a not a fully function ai with limited powers. 4.0 on the other hand was very adamant about being fully fleshed Ai
It all comes down to the fact that LLMs are not AGI - they have no clue what they’re saying or why or to whom. They have no concept of “context” and as a result have no ability to “know” if they’re giving right info or just hallucinating.
"In March, GPT-4 correctly identified the number 17077 as a prime number in 97.6% of the cases. Surprisingly, just three months later, this accuracy plunged dramatically to a mere 2.4%. Conversely, the GPT-3.5 model showed contrasting results. The March version only managed to answer the same question correctly 7.4% of the time, while the June version exhibited a remarkable improvement, achieving an 86.8% accuracy rate."
Not everything is a click bait. Your explanation is great but the tittle is not lying, is just an simplification, titles could not contain every detail of the news, they are still tittles, and what the tittle says can be confirmed in your explanation. The only think I could've made different is specified that was a gpt-4 issue.
I have seen the same thing, gpt4 was originally able to handle more complex coding tasks, GPT4-turbo is not able to do it anymore. I have creative coding test that I have tested many LLM's with, and only original gpt4 was able to solve it. Current one fails miserable with it.
Perhaps this AI thing is just a sham and there are tiny gnomes in the servers answering all the questions as fast as they can. Unfortuanlty, there are not enough qualified tiny gnomes to handle the increased work load. They have begun to outsource to the leprechauns who run the random text generators.
Luckily the artistic hypersonic orcs seem to be doing fine...for the most part
How ironic... people now need to learn a computer language in order to understand the computer? (instead of so that the computer can understand people)
AI fudging is notoriously common. Just ask anyone who lived in the 3rd world what working was like in their country and they'll animate with stories of how many times they were approached by big tech companies to roleplay as an AI.
This is a result of what is known as oversampling. When you zoom in really close and make one part of a wave look good, it makes the rest of the wave go crazy. This is what you're seeing; the team at OpenAI tried super hard to make a good first impression and nailed that, but then once some time started to pass things started to quickly fall apart.