dilyevsky

If you try actually filling out DS-160 and going through the rest of the process the difference will become really clear.

Which effort setting did you run this with?

A year isnt very long considering sums involved here. At a certain hyperscaler a full dc build out took 2-3 years but we heard that aws did that in a year all in. And also musk proved you can do it literally over holiday break but you don’t have to go that extreme - just dont let cya pmcs do it

Like 90%+ cost of a dc is actual computers which are pretty shippable

Why cant anthropic just sign up to those resellers, rack up some usage and then just start banning tf out of them? Reverse uno

Everyone says support but great support requires culture of excellence and customer obsession and that were the first things to go when those zirp-era scaleups went on hiring sprees

I know a few who are really feeling the pressure from customers now being able to vibe code part or their product and also their cloud bill is about to explode because hardware prices are through the roof

Pretty sure Carmack's idea of slack is what many companies would call "working as hard as possible"

Seems like this is a problem almost entirely solved by llm+vector database setup.

Don't get me wrong - AVP, Airpods, M-series chips are all amazing. Nothing as revolutionary as the first iphone, ipod, or an Apple II

Why didn’t those amazing engineers develop great hardware before or after jobs?

The context is AI made some knowledge work less cushy so now some folks are trying to point out random imaginary flaws (e.g TP or "water usage") when they're not busy trying to convince everyone AI doesn't work.

If it's http2 then Go's stdlib is pretty unoptimized to say the least. Huffman decoder is really cache unfriendly (pointer chasing) and I think allocation heavy too. Same probably goes for http1 and http3.

I dont think this comparison really works. Firefighter would be goalie or a defender and like you said in sports they are less appreciated/compensated for a simple reason - usually they don’t bring in views. There are exceptions ofc like Pippen or Seaman

Tom DeMarco had a whole book about this approach: https://www.penguinrandomhouse.com/books/39276/slack-by-tom-...

sure but there are tons of products from faang and other large companies that can be considered feature complete

Alternative ways of working

Twitter had laid off like 75%+ of staff and everyone, including on this site, was convinced it would crash and burn, yet it's still working. Explain?

nearly all big companies have failed too just on longer horizon

They're basically not building anything, and what they are building will be borderline unusable because of the route they chose so the car will be faster, cleaner and more convenient. If you want fast you can take the plane. So unless the problem is "how do we siphon as much tax dollars as possible banana republic-style?" I really can't agree here.

I think you've missed the point - that wasn't the reason at all. In a way he was right too - we'll have fully autonomous buses and private vehicles capable of making the full trip down the I-5 long before they complete even the middle of nowhere section they currently have planned.

Pinning CAHSR jobs program as hyperloop's fault is pretty funny. Maybe he did intend to upset it but since both turned out to be massive boondoggles doesn't seem like it worked - they managed to delay it themselves just fine.

Like with any tech there are dumb ways of using it and there are smart ways. Treating it as a "slot machine giving you the right answer" is a dumb way - it may work for a bit, but it won't carry you very far because everyone else can also do this. No one is stopping anybody from digging deeper into problems than ever before using this technology - that's the smart way.

Because you somehow need a giant training set which describes images in natural language, no?

That's definitely one way - they train a text encoder together with an image encoder on a labelled set of images. WL & 3b1b made a nice video on it: https://www.youtube.com/watch?v=iv-5mZ_9CPY

Figma make and gpt designer have a bunch of catching up to do. I couldn’t even import our brand guidelines into make which is already a .fig like what are we even doing here, guys? CD crunches through ungodly amount of tokens and is really slow on iteration but at least you can get some really nice prototypes extremely quickly there. GPT beats any Anthropic models on illustrations so they really should get a grip on multimodal. Overall, it seems like we’re still super early but you can already see glimpses of what may come

I'm not sure it's so much a fad rather than recognition that AI-assisted engineering calls for flatter orgs. Also "growing headcount" as management yardstick persisted way longer than 2017 - all the way into 2022 until the rates shot up.

Did you? That's exactly what they are discussing except Spain and Portugal. One of the profiles still works remote at a major US software firm.

Switzerland or Luxembourg.

Like i said either use pre-baked env or give a candidate an auth token with something like $100-200 quota from the provider your company already uses

Depends on what you ask, i suppose. I’m sure i can come up with something that can’t simply be one shot or the result would be bad if you do. A bit more difficult on logistics tho as you’d have to arrange for an environment with some prepaid llm access