dgreensp

I can’t read the page, it just redirects me to about:blank (mobile Safari).

The declaration literally opens by writing that AI companies (or really anybody) saying, “Hey, let’s see if this powerful reasoning engine can solve an open problem in mathematics” is “detrimental” to the “science” of mathematics. Full stop. So I don’t think it’s being misrepresented. If it’s a science, why isn’t progress good in itself? You can’t have it both ways.

The online comments I’ve read that side with the letter explain that the problem is AI proofs are inscrutable and useless, but the reality is using computers to brute-force things has long been part of proofs in one way or another, and AI proofs range in legibility up to 100% (like pointing out a proof exists in a long-lost paper, or writing something that is basically correct and just needs a human reviewer to fix it up). People are probably defending the declaration inaccurately, but I think that’s because the real argument or arguments are unclear.

Is it that students won’t learn math if there’s ChatGPT? That could be discussed.

To a non-mathematician (MIT physics and CS ‘06), the letter sounds like, “We have a fun job. Sometimes there are no practical applications of the work, so it’s just kind of like a sport, er I mean science. If someone solves a problem that has stumped mathematicians for decades or centuries, we worship them as a great mathematician. It’s a status thing. So we don’t like some guy with a computer coming along and solving our problems. The way things unfold with all the ideas coming from humans, over time, maybe it’s slower, but it’s nice.”

I don’t think anyone can really stop someone from using a computer capable of solving unsolved problems to solve unsolved problems, and there are always going to be mathematicians who DO think it’s fun to try to figure out what a computer is doing (if the computer isn’t already explaining it in English, which it generally can), and make progress that way, and it obviously will lead to mathematical advances in human understanding, from my point of view. So the whole thing is a non-issue that no one can do anything about anyway.

This looks really interesting.

I feel like there is a lot of room to build great voice-based agents that don't exist right now.

I have found that ChatGPT voice mode is unusable (e.g. hallucinates me saying things); Claude voice mode is usable, but very buggy around tool calling, and it often mishears things. And it only supports Opus, not Fable (though it looks like you don't support either of those). But I use it anyway.

Question, do any of your TTS options support increasing the speaking speed?

Where do you see information about the efficiency gains over AV1?

This reveals a staggering level of incompetence, if that’s really all it is, and lack of transparency.

They don’t have ANY product-level quality tests that picked this up? Many users did their own tests and published them. It’s not hard. And these users’ complaints were initially dismissed.

I don’t think the high vs medium change is really on par with the others. That’s a setting you change in the UI, and depending on what you are doing, both effort levels are pretty capable, they just operate a bit differently. Unless I’m missing something and they are saying they were doing some kind of routing behind the scenes.

If they are constantly pushing major changes to the prompts and workings of the tool, without communicating about it, and without testing, it’s likely there are other bugs and quality-degrading changes beyond the ones in this article, which would make a lot of sense.

I agree with all this.

I came to Deno because I needed a break from Node/NPM. I don’t agree with all of Node’s decisions (particularly the ES module debacle), but Node/NPM have improved over the years.

A big problem with JSR was no private packages. All your code has to be open source. But JSR is the only way to get constraint solving in Deno, besides using NPM.

I find the irreverent tone refreshing, personally.

As a founder who built all my prototypes and side projects on Deno for two years, I personally think Deno’s execution was just horrible, and avoidably so. Head-scratchingly, bafflingly bad decision-making.

I was the first engineering hire at Meteor (2012-2016), and we made the mistake of thinking we could reinvent the whole app development ecosystem, and make money at it, so I have the benefit of that experience, but it is not really rocket science or some insight that I wouldn’t expect Ryan Dahl and team to have, in the 2020s.

They were stretched thin with too many projects, which they were always neglecting or rewriting, without a solid business case. They coupled together runtime, framework, linting, docs, hosting, and packaging, with almost all of these components being inferior to the usual tools. The package system became an absolute nightmare.

If the goal was to eventually replace Node and NPM with something where TypeScript was first-class, there was better security, etc, they could have done a classic “embrace and extend.”

This piece starts off making it sound like the computer is pretty much doing all the work, while the human maybe weighs in on a matter of taste once in a while, if they like, but by the end, the list of what the LLM can actually do is really short. Implementing a sorting algorithm for you, perhaps, but not necessarily one without “egregious flaws,” and really you should still use a library for that. Replacing high-quality libraries of mature software, that have tests, etc, is obviously one of the poorer uses of vibe-slop coding.

It comes down to “adding code” that attempts to, or seems to, achieve something.

I always interpreted cathedral vs bazaar as being about the architecture of large things. Do you build to a master plan? Or does everyone do whatever they want? (Within some kind of framework, of course.) Like the cathedral of the Java SDKs vs the flea market of NPM.

This author seems to have some kind of attitude about organization in general—anything with people and process, that happens to exist around some project, that might require at least a small commitment to be a part of. Like complaining that a flea market has a form to sign.

The ability for people to functionally collaborate, with some kind of structure, is the key thing that enables building large things together.

By that logic, Microsoft’s brand means nothing when OpenOffice is free.

A curly brace is multiple tokens? Even in models trained to read and write code? Even if true, I’m not sure how much that matters, but if it does, it can be fixed.

Imagine saying existing human languages like English are “inefficient” for LLMs so we need to invent a new language. The whole thing LLMs are good at is producing output that resembles their training data, right?

I ran into this, and there was a bizarre fix—I think having Adobe apps open in the background caused it, or something.

Upvoted because educational, despite the AI-ness and clickbait.

I’ve worked at orgs that used Postgres in production, but I’ve never been the one responsible for tuning/maintenance. I never knew that Postgres doesn’t merge pages or have a minimum page occupancy. I would have thought it’s not technically a B-tree if it doesn’t.

This is some of the best writing I've read in a while, and truly fascinating.

Radix sort is not a comparison-based sort and is not O(n log n).