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My response was simplified because your question was basic. OpenClaw was one example that fit the pattern, not a claim that every deployment holds the credential in the sandbox. Injection proxies exist and I should have said so. As for showing the data for advantages, I'll refer you to Anthropic and Cloudflare's Code Mode https://www.anthropic.com/engineering/code-execution-with-mc... https://blog.cloudflare.com/code-mode-mcp/ We have our own, but will defer to 3rd party evidence. Reinventing progressive disclosure is definitely part of this, but that's only one element of the approach. To be clear, this is all based on what we use internally, deployed in a particular way within our platform. Will leave it up to others to determine how useful it may…
Well put. I've found that agents are great at adding features to areas of the code that I already understand, where I can phrase my goals coherently and keep them on the rails. Any attempt to describe software by "specification" leaves enough ambiguity that the agent will do deranged stuff like add a ton of code to satisfy error cases that can't happen. Or, like you imply, it will confidently create a bunch of nonsense to "solve" a problem in a way that is not really possible.
Thank you, good to see someone who actually knows what the word means. Sibling comment is correct too, the term has been misused and muddied in the US since the 1930s, and it no longer has a coherent meaning here. (If you mean “Democrats” then just use that term.)
I think this is too generous of an interpretation of OpenAI's and Anthropic's position. the 'slow down' mandate is not a real regulatory standard - policies are generally crafted based on good vs bad outcomes, not speed-of-development. the drive for this kind of specific, toothless regulation is done at the behest of large corporations looking at open-weight models eating their cake and realizing that any small player could now do so too if they had the compute backing them (places like Canopy Wave, for eg) that it also serves as marketing material for just how capable their models are is just a cherry on top, I suppose
Lest someone gets the wrong impression, I think that any mention of the a priori strange-looking resolution to the Jacobian conjecture should be accompanied with a read of pages 160–161 of https://arxiv.org/abs/2609.05746 . The tl;dr being that the very same construction featuring in the resolution appeared earlier in a draft paper that was accidentally made publically available for a travel award application. The same story has accompanied several other of the major announcements made by now. We haven't have a move 37 for maths yet, despite what OpenAI's marketing department might want you to believe. Similarly, if all you ever read were OpenAI blog posts, you would get a very wrong impression of the usefulness of large language models of today in maths. For a working…
Willingness to pay. If people are willing to use Astra instead of Sol even if it costs twice as much, OpenAI has no need to make it cheaper. Prices only reflect costs in a competitive market where customers actively seek out cheaper alternatives.
I agree that the LLM behaviors between Anthropic and OpenAI are different enough now that it can lead to different experiences. I absolutely hate talking to Opus but don’t mind Sol and Astra. My guess is Martin used Opus.
I agree that the LLM behaviors between Anthropic and OpenAI are different enough now that it can lead to different experiences. I absolutely hate talking to Opus but don’t mind Sol and Astra. My guess is Martin used Opus.
Full disclosure, it was coded with AI, I don't claim otherwise. But I wanted to test out tool calls and iterative problem solving using Jev and needed a simple library/framework/harness to do that. SOKIT (System One Knowledge, Instructions and Tools) is the result and I figured it might be useful for more people than just me. I will likely be extending it a bit as I find more ways to use Jev, but it works as is for certain use-cases and it's easy to extend.
OpenAI's "artificial intelligence" is an inference program that they developed which receives input and generates output. Based on which other programs, also developed and maintained by OpenAI, perform actions. Such as sending POST/GET requests to various sites which result in gaining unauthorized access and even destruction of information (deleting logs/message history) at the said sites. What exactly requires "new regulatory framework" here? You running your software resulted in illegal actions, you are to be held liable within existing laws and regulations.
I was thinking about doing this. If we treat ChatGPT like your local llm server, you basically open up a browser session, intercept all traffic and stick a local OpenAI compatible rest server that mutilates your input upstream through the ChatGPT ui, and then intercepts downstream and pushes it out your server. API call to server Then Server leverages chrome plugin to send your llm call through the plugin , through the ui, wait for response , intercept, repackage and reroute it back out as a server response. Then that $20 sub stretches to all uses cases for a developer.
I don't think popularity is a goal for Anthropic or OpenAI. They merely want to have a product that they control and you depend on, and don't care about anything else. Nobody really *likes* their drug dealer.
>Why can't OpenAI publish whatever it wants. And the math community can use it or not use it. The "math community" is not an isolated entity that is free from the confines of society. It's made up of lots of people who coexist in a system that requires you to assert your right to live. Furthermore, the "math community" is overwhelmingly supported by outside donations to keep it running. That's not to say people don't practice math for the fun of it, but that if you're researching problems like Navier-Stokes, you almost certainly are being paid by another party to do so. But those parties may hold new forms of technology over the professional mathematicians head in the name of "productivity", or they may even believe in light of this tech that paying a human to practice math is no longe…
Serious question, why? Nobody gives a fuck if I'm out of a job, especially OpenAI and Anthropic. They stole the worlds knowledge to put us out of a job and arguably took away what it means to be a human. Why should I contribute anything more to that? Solving hard problems will be the only thing that separates you from others. Your mindset and tools should be a trade secret at this point.
I cannot wait until Gowers and Tao must have an iris scan at Altman's Worldcoin in order to get to their beloved OpenAI. Give it 5-10 years.
And now you are even more dependent on OpenAI... You didn't solve the problem, you are just trading pain points.
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