extralongdivisi

The premise is fundamentally flawed.

Ask any AI/ML expert and they will tell you that the key to a well performing model is a clean dataset. The rise of AI will financially incentivize human input, and thus independent human thinking. Frontier model reliance on RAG proves this point. Assuming AI will do all the thinking for you is a recipe for financial ruin.

Two, the cost to run an AI service != the cost to use an AI service. Frontier companies cannot operate at a deficit forever. Even if their costs go down, end user prices will go up. Their profit margins will increase and history shows they will not pass those savings to the end user.

> go the extra 10 cm

Going to steal this

The generated confusion ironically supports OP's point

> I hadn't actually explained what the software would do.

I cannot tell you how many READMEs I've read that follow the pattern: "<uninformative-name> is a <buzzword> <buzzword> written in <language>." I only have some semblance of what it does after using/seeing a demo; too often one that isnt available through the README.

Long term support is not the Google way

Professionally, I'm forced to use CoPilot, which is so eager to please me that it's useless, and Claude which is fairly good at writing code but hallucinates data when I ask it to organize my notes.

Personally, I'm using Qwen, Phi, etc. to squeeze as much performance out of constrained hardware as possible. They're pretty good at searching my personal files which you mentioned in a previous comment.

edit: typos

> the best use, arguably, of an LLM is as a very fast search index for common information

I'd counter forming a rebuttal against a search result would be fairly trivial. I.e an AI summary for "are oranges poisonous" would say "Moms Against Big Citrus says oranges are poisonous, but the Association of Orange Groves says they are not." When used for search, LLMs are a source for sources instead of the source of truth itself. The user decides which source to believe instead of deciding to believe the LLM itself.

> you might be fortunate to be in a position where nobody is relying on your velocity to ship products at competitive speed.

Admittedly the biggest drawback. AI is pretty terrible at my profession (electrical engineering, regardless of recent demos that are horrendous when examined under a microscope), but the software engineers I know haven't hand written industry code in months.

1. I have never been to a library that has banned any class of people. Let alone specifically homeless people.

2. I don't know the laws of your jurisdiction, but banning a whole group of people from a public place would, by definition, not make it a public place.

3. The overwhelming majority of librarians view libraries as a service for everyone, including the homeless[0].

[0]: https://www.ala.org/sites/default/files/aboutala/content/olo...

You clearly do not live in an area with a large homeless population. Many libraries are effectively under-resourced homeless shelters. Yet, no requirement to have a library card to get in. Information is still open to the public.

I can walk into a library, pull a book from a shelf, sit down, and read it front to back. No library card needed. Only need one to take a book home. Completely different scenario.

Edit:clarification

> If its the difference between the information being available at all

That's the point. The solution should avoid information not being available. Requiring login will incentivize bots to create spam accounts and move the battle to a new frontier, hurting real people in the process.

Gatekeeping information is not the solution

Am i dense or is there very little concrete detail on how their agent runs the day-to-day?

1 hour 33 seconds long

Same.

Software moves so fast that its actually an anti feature. Libraries and SDKs measure lifetime support in years, but industrial hardware support *at minimum* is a decade. A lot of these new startups dont understand that established industry wont use them unless they known this shiny new system wont ve abandoned in a few years.

On the other hand, softwate devs trying to quickly make a product have something to get them going.

More reason to stick with my monitor and Kodi.

My most recent experiences have been those chips, yes. Re: my point about doing novel things.

Not necessarily true, most recently I was working with an USB 3.1 chip that anyone can buy off DigiKey, but I had to call contacts at 4 seperate companies just to get firmware to make superspeed work. We werr just too small of a fish to make the chip vender care.

This is becoming more true as a larger percentage of hardware infrastructure is occupied by the datacenter economy.

Very limited study.

A lot of datasheets are inaccessible without signing an NDA. Even if you're a VC-backed enterprise, some unnamed chip vendors will tell you to pound sand if you're less than 8 figures of annual revenue.

Worse, many recommendations in datasheets were written in the 80s, overkill for many applications, or completely wrong and won't be updated until an errata is published 6 months later. Given current workflows, I don't see how AI would help designing a PCB with an alpha chip that's doing anything remotely novel.

More to the articles point, AI designing ASICs or other Verilog/HDL defined components could be very interesting use case

Like the ethos but how is this different than Project Ocean or the Internet Archive?

It doesnt hurt to have multiple projects, im genuinely curious.

I'm trying to find your capabilities. I.e trace and space minimums, hole to edge minimums, min annular ring, etc. Are you not at that stage yet? Will you ever publish a standard spec?