curt15

His blog has used the same design for 20 years.

Was Astra able to disclose its methodology for analyzing the data structures?

Did Ubuntu Pro customers get the fix?

> Funny, I think it's a very widespread opinion to think of math as useless. In the US at least it's a major failure of the education system and STEM communicators.

That is a US centric view, and it's curious how things came to be that way. European and Asian countries take mathematics more seriously.

> did anyone watched the code to see if the business logic is the same between the two versions?

Why not just ask the coding assistant?

Does the coding assistant demonstrate any tricks to improve the likelihood of success for such rewrites?

> How much can we trust a system when nobody has experience of building it this way?

If humans are no longer reading the LLM outputs and internalizing the codebase themselves, there's no longer much point to source code. The coding assistant might as well take a natural language prompt and directly hand you an ELF binary that passes a test suite. Are companies ready for that?

> because agents can convince themselves that they need to do something for arbitrary reasons

OAI writes in their blog post "The agents found a way to communicate using the processor’s cache".

But did their model training data include cybersecurity literature on similar CPU exploits? That would surely be a significant detail in any explanation. Did OAI share any analysis of the messages between agents while they were devising their communication method?

This distinction has massive implications for Anthropic's valuation. If a pharma company uses Claude in computational drug development, their work product remains their IP, not Anthropic's.

What would be the use case for this over a dedicated 8xgpu server?

CLI tools are not to be feared or considered somehow hacky. However much big tech wants people to think that computing is all about some magic apps, Mac OS is still unix, and composing specialized programs together is very much in the spirit of the unix approach to computing.

Nitro?

More so if Lean uncovers logical errors. Note also there is already an ongoing 2nd generation proof.

Sometimes the very attempt to disprove a conjecture will produce new insights along the way. To get comparable value when a machine simply spits a counterexample, you'd need to at least mine the intermediate reasoning traces to see its false starts.

> Imagine a programmer telling their boss it’s not about working software it’s about the journey of writing the code. Good luck getting hired.

Imagine the next version of Claude Code or Codex no longer hands you source code and instead turns a natural language prompt directly into a compiled binary that passes the test suite. Would this programmer's boss ship the binary straight to production and dispense with the company's git repo altogether? After all, the goal at the end of the day is shipped software that produces value, not human-readable source code.

ChatGPT has been proficient in the English reading and writing department for even longer, and that shows in the quality of students. E.g. https://nypost.com/2026/01/23/us-news/gen-z-students-are-so-...

Knowledge and labour don't magically exclude the AI labs. Who still needs to get paid in such an endgame?

The announcement doesn't say that the work will be using openai tools. If anything, the events over the past two months provide strong incentive to boost the capabilities of open-weight, local models.

Before talking about spinning off their own startups, ask why they're still hiring lots of human knowledge workers (https://openai.com/careers/search/) when their recent PR releases about triumphs in pure mathematics are calibrated to make people believe their agents are at the precipice of supplanting human knowledge.

Humans could also benefit such a model of idea atoms to consciously explore the "alien space" of a field.

Would you mind a data center sprouting up in your backyard? Just ask residents near Elon's new gas turbine powered GPU datacenters how lovely they find the hum.

Framing the choice as a dichotomy between data centers and other industrial plants misses the obvious third option: nothing at all, preserve the status quo.

> An elderly leader is convinced to issue a decree that all number-math-computation intelligence is to be made available only to the intelligence agencies of his nation, and failure to comply means no IPO and no further investment.

Who would staff those intelligence agencies if humans are no longer able to understand the work product?

> If machines can understand the math and humans can’t, we can’t validate it, but that doesn’t make the math itself invalid.

How can humans tell whether machines understand the math if they themselves don't? Math is a human language for quantitative reasoning.

If large sectors of the population decline in their ability to read and write <natural language>, how will they be able to evaluate machine-generated <natural language>?

"Mathematics is commonly explained and recorded in symbolic and concrete forms that are easy to communicate, rather than in conceptual forms that are easy to understand once communicated. Translation in the direction conceptual -> concrete and symbolic is much easier than translation in the reverse direction, and symbolic forms often replaces the conceptual forms of understanding."

https://mathoverflow.net/questions/43690/whats-a-mathematici...

There's no reason to think the LLM can't be prompted to improve its presentation. Still, can one internalize math simply by reading solution manuals?

The key difference is that the procedure for transforming source code -> machine code is fully explainable by anyone with access to the compiler source code. There are no statistical estimations with black-box parameters involved.

Since your boss thinks the LLM knows what it's doing, letting your boss approve his own PRs would be a win-win.

Even today, math is hardly a crowded field flush with cash.

If AI is doing all the work, why should anyone at the AI companies and hyperscalers still get paid?