To this day frontier models think that A and not B means A and B when the sentence gets pushed far enough back in their context window. The context length that model can reason over without obvious errors is much smaller than the advertised context. Between a 1/4th to a 1/20th what is advertised on the tin.
Critiques like this tend to focus very hard on what models can't do. It's true, they have limitations.
But they're also superhuman in so many other ways. It's valid to point out limitations, but that doesn't support the conclusion that models are not incredibly powerful and capable of the functional equivalent of reasoning at human or superhuman levels in many scenarios.
Is that the same gap as what you’re responding to? To me, it seems his critique is about advertised capability and logical statements, and your rhetorical(?) question is about memory.
"If you have a question look in the specification for the answer and don't just guess" seems a fairly important thing to remember for more than a couple of minutes...
I had a coding session where I was doing stuff across two repositories. And CC forgot in exactly which repository a particular file was so it was grepping the parent directory. I just asked it to write all important key-value pairs which it thinks are important to a file and it never did parent directory grepping.
There is a movie, Gold (2016), about a fake gold mine. One of its founders is a true believer: he found a few chunks of gold and started digging for more. The other founder is a nihilist: he realised that there is no gold there, but who cares if he makes the investors believe? So he does, and almost sells the company for $300M.
In our story, investors are mining intelligence from GPUs, and they truly believe they are one inch from discovering the biggest goldmine in history. But GPUs, unlike a goldmine, cannot be inspected for traces of gold by independent contractors. To keep the hype up, the nihilists in our story dig up cheap gold-looking metals from time to time and tell investors that with a bit of alchemy - agentic workflows, etc. - those metals can be magically turned into gold.
Investors will keep digging until the end of the age, or until they run out of money.
There is now a trillion-dollar industry bent to the task of convincing people these things can think. It’s gonna cause some damage.
I don't think they think. I still use them a lot despite that, because they are very powerful parameterised code generators.
…but they reason well enough given enough context (using their matmuls).
To this day frontier models think that A and not B means A and B when the sentence gets pushed far enough back in their context window. The context length that model can reason over without obvious errors is much smaller than the advertised context. Between a 1/4th to a 1/20th what is advertised on the tin.
Critiques like this tend to focus very hard on what models can't do. It's true, they have limitations.
But they're also superhuman in so many other ways. It's valid to point out limitations, but that doesn't support the conclusion that models are not incredibly powerful and capable of the functional equivalent of reasoning at human or superhuman levels in many scenarios.
Do you also happen to remember what you ate last thrusday?
Is that the same gap as what you’re responding to? To me, it seems his critique is about advertised capability and logical statements, and your rhetorical(?) question is about memory.
"If you have a question look in the specification for the answer and don't just guess" seems a fairly important thing to remember for more than a couple of minutes...
I had a coding session where I was doing stuff across two repositories. And CC forgot in exactly which repository a particular file was so it was grepping the parent directory. I just asked it to write all important key-value pairs which it thinks are important to a file and it never did parent directory grepping.
There is a movie, Gold (2016), about a fake gold mine. One of its founders is a true believer: he found a few chunks of gold and started digging for more. The other founder is a nihilist: he realised that there is no gold there, but who cares if he makes the investors believe? So he does, and almost sells the company for $300M.
In our story, investors are mining intelligence from GPUs, and they truly believe they are one inch from discovering the biggest goldmine in history. But GPUs, unlike a goldmine, cannot be inspected for traces of gold by independent contractors. To keep the hype up, the nihilists in our story dig up cheap gold-looking metals from time to time and tell investors that with a bit of alchemy - agentic workflows, etc. - those metals can be magically turned into gold.
Investors will keep digging until the end of the age, or until they run out of money.