Comments URL: https://news.ycombinator.com/item?id=49046110

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I assume that in addition to the significant memory savings, this should also lead to much simpler matrix multiplication operations? Could models like these run on CPU's efficiently, or does the geometry of the compute mean GPU's are still a better choice?

- crushing

- breaking down with powerful solutions

- blasting

And a self-replicating probe will (initially at least) be a low energy system. I eventually decided that the pathway with the most likelihood of success would be some kind of very slow crushing/grinding machine that can break down ore into separable components, but then you get into a kind of Darwinist explosive combinatorics research rabbit hole: which crusher/grinder, what kind of machine, how to make something that works on different ore types, what mechanical pressure is better?

Conceptualizing something that can sinter and assemble PV cells was pretty easy, there are broad families of chemistries that work and they mainly differ on input temperatures and output efficiencies. Fairly tractable. But mineral extraction... yeesh, it's extremely difficult.

FWIW on the original article: I think the jump from "insulating wires" to "semiconductor fabs" was kind of obtuse. You don't necessarily need Turing complete PCBs or microchips for most (any?) of this.

"Status:

pgrust is not production-ready yet. It is not performance optimized yet."

The maintainer is not suggesting you use this for anything yourself. So why do you care about spf or (lol) his "discipline in creating the project"?

It's not better at reasoning on complex coding tasks, Claude Opus is still ahead there, but not by a lot.

IMO that's exactly why it's a bit better at actual problem solving.

You absolutely do not "always have to correct" Codex. I'm not sure what you're doing, but I'd say 80-90% of its edits on my side it doesn't need any revisions.

I do almost all my regular coding tasks with Codex 5.5 on medium. Sometimes for niche edge cases, or when I run out of tokens on my Codex sub, I'll switch to Claude. Some recent examples where Claude was able to solve things Codex couldn't:

- 3D gamedev layout: I asked Codex to render a solar system in a certain camera positioning, saying it needed to fit the planets of the system to the viewport. Codex just couldn't do it, even on high reasoning: Claude Opus did it first attempt.

- Tricky Tiptap image drag-n-drop layout implementation: Codex failed this after numerous iterations. Claude Opus also struggled mightily to get it to work, but I think around 3 attempts it nailed it. Both of them ended up grepping the Tiptap code from node_modules - that's the kind of task it was.

But these are really isolated examples. Across all my projects (I have many; mostly TypeScript, but also things like C#), Codex "Just Works" (tm), with minimal prompting effort from me.

But what has happened is the models have gotten better - which OpenAI is making explicit for some cases in this release. You need that stuff less and less as they become more human and better at inferring what's required implicitly.

You still do need to be explicit, and you probably always will, but you don't need as much "engineering" of the way you're asking for things with more recent models.

"Meta knew what it was doing"

In December 2015, CEO Zuckerberg listed as one of Meta’s goals for 2016: “Time spent [on the Platorms] increase by 12%” over the following three years. And as of November 2016, Meta’s “overall goal remain[ed] total teen time spent … with some specific efforts (Instagram) taking on tighter focused goals like U.S. teen total time spent.”

Between October 2022 and April 2023, Meta’s own internal metrics show that an average of 208,000 Mississippi young adults used Instagram daily and 345,000 used it monthly. In fact, Meta monitored key metrics for Mississippi, including:

• Ratio of teen daily active users to monthly active users: 0.72

• Increase in monthly active users over a two-month period: 7,894

• By 2020, Meta estimated 100% of MS teens were monthly active users of Instagram

A 97-page internal presentation, “Teen Fundamentals,” in May 2020, described its goal as to “look … to biological factors that are relatively consistent across adolescent development and gain valuable unchanging insights to inform product strategy….”

That presentation conceded, “due to the immature brain they have a much harder time stopping even though they want to – our own product foundation research has shown teens are unhappy with the amount of time they spend on our app.”

One internal communication noted that Meta could “[l]everage teens’ higher tolerance for notifications to push retention and engagement,” while another noted that some users are “overloaded because they are inherently more susceptible to notification dependency.”

As it noted in its 2019 internal presentation, “Teen Mental Health Deep Dive,” “Young people are acutely aware that Instagram can be bad for their mental health, yet are compelled to spend time on the app for fear of missing out on cultural and social trends.”

In another internal presentation, Meta employees express concerns about “content on IG triggering negative emotions among tweens and impacting their mental well-being (and) our ranking algorithms taking into negative spirals & feedback loops that are hard to exit from.”

> China’s Ministry of Commerce has led meetings over the past month with major AI companies, including Alibaba, ByteDance, and http://z.ai/, to discuss measures that would restrict overseas access to cutting-edge AI models, including models that have not yet been released.

> The discussions reportedly include not only closed-source models but also open-weight models.

> Future regulations could take the form of a tiered framework based on technological capability. Basic open-source AI models may be managed through a filing system, high-performance models may be subject to security reviews, and the most sensitive frontier models may be banned from public release or restricted to use within China

https://www.reuters.com/world/beijing-is-looking-curbing-ove...