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I've been waiting for someone to say this. An agent will generally produce far more code than technically necessary for the task. It's a kind of over engineering which makes it increasingly harder to wrap your head around the codebase.


Over engineered implies the codebase was inflated with some kind of rationale by the AI, but there is none. It's just code vomit with duct tape


The issue is provenance. We need cameras and phones to digitally sign photos so we can easily verify an unadulterated image.

You also want to be able chain signing so that for example a news reporter could take a photo, then the news outlet could attest its authenticity by adding their signature on top.

Same principle could be applied to video and text.


Signing something doesn't verify that it's real, it just verifies that you claimed that it was real, which everyone was already aware of. You can either hack a camera, or use an unhacked camera to take a picture of a fake picture.


I'd it's processed in 2 seconds, why not just process it immediately in memory?


Because they are serverless, so there's currently no memory for it to be processed in at the point of upload


Maybe there are too many requests, so they have to offload the videos to s3.


That's not the reason. And furthermore any buffer/re-try mechanism should be done at the edge (on the camera).


It's all jit context


It looks like true 0-temperature (i.e. determinism) will happen. Here's some good context: https://thinkingmachines.ai/blog/defeating-nondeterminism-in...



But 0 temp is much less "Creative" and may not be conducive to showing off the AI's latest tricks


True. It depends on the feature you're demoing...but determinism is a VERY DESIRABLE feature for giving demos.


You can just call yourself a reasoning model now


This is written by someone who has no idea how transformers actually work


Contra: The piece’s first line cites OpenAI directly https://openai.com/index/why-language-models-hallucinate/


It could be that nobody knows how transformers actually work.


Furthermore, if you simply try to push certain safety topics, you can see how actually can reduce hallucinations or at least make certain topics a hard line. They simply don't because agreeing with your pie-in-the-sky plans and giving you vague directions encourages users to engage and use the chatbot.

If people got discouraged with answers like "it would take at least a decade of expertise..." or other realistic answers they wouldn't waste time fantasizing plans.


> The way language models respond to queries – by predicting one word at a time in a sentence, based on probabilities

Kinda tells all you need to know about the author in this regard.


I don't know what to make of it. The author looks prolific in the field of ML, with 8 published articles (and 3 preprints) in 2025, but only one on LLMs specficially. https://scholar.google.com/citations?hl=en&user=AB5z_AkAAAAJ...


I think you've nailed it there. OpenAI are at a point where the risk of continuing to hedge on mcp outweighs the risk of mcp calls doing damage.


Once you notice characters aren't eating, you'll never not see it again.

Related, where they're drinking coffee from a disposable cup, you can almost always tell it's empty by how they handle it.


> Related, where they're drinking coffee from a disposable cup, you can almost always tell it's empty by how they handle it.

NCIS has a running gag about that. In the show they invariably drink... some mysterious caffeinated product, I don't know if I'd call it coffee, with a straw. It always makes a slurping sound like the cup is nearly empty. Even when just handed a fresh cup.

That show is often lampooned for the silly "two idiots one keyboard" scene, but I am convinced they are doing dumb stuff like that on purpose.


This is true for all crime.


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