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O3 is massively underwhelming and is obviously tuned to be sycophantic. Claude reigns supreme.
So, are we talking about OpenAI o3 model, right?
Where does this obsession over giving binary logic tasks to LLMs come from ? New LLM breakthroughs are about handling blurry logic, non precise requirements and spitting vague human realistic outputs. Who care how well it can add integers or solve chess puzzles ? We have decades of computer science on those topics already
So... it failed to solve the puzzle? That seems distinctly unimpressive, especially for a puzzle with a fixed start state and a limited set of possible moves.
I cannot understate how impressive this is to me, having been involved in ai research projects and robotics in years gone by.
This is a general purpose model, given an image and human written request that then step by step analyses the image, iterates through various options, tries to write code to solve the problem and then searches the internet for help. It reads multiple results and finds an answer, checks to validate it and then comes back to the user.
I had a robot that took ages to learn to plan tic tac toe by example and if the robot moved originally there was a solid chance it thought the entire world had changed and would freak out because it thought it might punch through the table.
This is also a chess puzzle marked as very hard that a person who is good at chess should give themselves fifteen minutes to solve. The author of the chess.com blog containing this puzzle only solved about half of them!
This is not an image analysis bot, it's not a chess bot, it's a general system I can throw bad english at.
So... it failed to solve the puzzle? That seems distinctly unimpressive, especially for a puzzle with a fixed start state and a limited set of possible moves.
> That seems distinctly unimpressive I cannot understate how impressive this is to me, having been involved in ai research projects and robotics in years gone by. This is a general purpose model, given an image and human written request that then step by step analyses the image, iterates through various options, tries to write code to solve the problem and then searches the internet for help. It reads multiple result…
Where does this obsession over giving binary logic tasks to LLMs come from ? New LLM breakthroughs are about handling blurry logic, non precise requirements and spitting vague human realistic outputs. Who care how well it can add integers or solve chess puzzles ? We have decades of computer science on those topics already
If we're going to call LLMs intelligent, they should be performant at these tasks as well.
But yeah calling them intelligent is a marketing trick that is very efficient