blobbers

Okay, I skimmed the article.

Is creatine safe to supplement for children?

Just pay your bill Elon.

Do you feel like lobste.rs is a better version of HackerNews?

I'm talking about the Watts used to power the GPUs, not the GPUs themselves.

No, the public utilities aren't the ones taking the debt to fund the power generation for some direct data centers.

Companies like Bloom Energy are putting up power plants right next to DCs. If datacenter power demand then these companies will sell back to the grid creating an oversupply.

If the debt load is too high they're need to declare bankruptcy, at which point the bond holders will lose their capital, not the public.

At least if the datacenters usage crashes, we'll have cheap power from all the infra that got built.

I am have an old Pentium 4 with RDRAM, think I could sell it to them? I think it has like 256MB. Haven't turned it on in awhile. Hope the first 640KB still work.

I never played this game! I didn't realize there was a RTS after Crescent Hawk's revenge. I'm looking at the MC2 source code now... it looks like there is a Linux port, meaning could probably get it working for Apple using Fable 5, AI haters, I will challenge you to a batchall.

madwifi lives on...

How does llama.cpp use the GPU efficiently as opposed to MLX?

Is there any way to use MLX and GPU at the same time? Or does memory become a big problem?

TBH, I never understood Apple hyping these neural cores because I didn't think anyone actually uses them except maybe certain photo/video editing software.

If I can generate voice at the same time as video, that would be useful.

What happens when you find the models are terrible? The claimed results don't match? My dev cycle tends to be write a test for blah blah, add feature to satisfy test, make sure tests pass.

Great, and here I thought my job was safe.

As someone currently exploring grid searches of encodings + compressor combos, and currently looking at neural compressors that reduce size almost half that of a traditional compressor yet take order from ms -> minutes to operate in either direction, I appreciate a good compression post!

If Apple knows it's been overpaying, you can be sure that they will leverage that in future negotiations.

Yes it did, but you are not your job. Your current state may be based on a fraud, but the fraud is not you.

What for... ?

The Homer.

https://www.youtube.com/watch?v=gRBDLE06qNY&t=210

"What does this monstrosity cost?"

...

Matt is a great guy to explain this kind of stuff. He's very helpful.

Tech companies have basically just milked advertising dollars from trad media, and centralized malls into websites.

Now we have dystopian warehouses and cars driving all over.

We get more, but we do less.

We interact with more of the world, but we interact with people less.

It makes us unhappy.

Have you tried optimizing for MLX? It seems like a waste to have neural cores and not use them.

I've often wondered why the hype around apple neural core when 99% of software doesn't use them.

Free is a pretty good deal if you can onboard 2 million users.

uhh isn't it basically free access to API if your apps are less than 2 million downloads?

I'm not sure if I trust the S&P 500. There are much better ways to build indices than the one they've built.

People speak about "diversification" without truly understanding why they're diversifying or what the covariance of their portfolio is, and then just cite statistics about how "on average".

It's a lot harder to walk the walk when your entire portfolio has been underwater for 7 years without sign of coming back; loose money has prevented that but the grifts are starting to get to the end of their strings.

Good. Financial grift needs to end. Passive investment has become slightly too passive. S&P saved us. We weren't so lucky when they were rating bonds before the GFC. Glad they seem to have grown some ethics and are not bending the knee to the rocketman.

I think the main thing companies should try to understand is avoiding the use of 'claude -p'.

I definitely have written a goal file, and then just ran claude in a loop over the goal in order to 'token max'... why not? I'm doing research and have some clear KPIs where research into all kinds of techniques / tuning can improve the results. I can spend my budget on a "experiment with blah blah blah to improve blah blah" or give it a list of things to try that I know will take awhile.

Its no problem hitting hundreds of $ of API spend while sitting at a computer with 3 monitors have 6 windows of useful claude code interactive sessions, while working on 2 or 3 projects and using worktrees, and it's a little weird when you hit your limit by 2 o'clock and have to wait for token budgets to reset; god forbid, I manually edit code... which I did do for the first time in months.

You can also start to generate a lot of token spend if you do something like "hey make me a stylized slide deck using internal skill / agent XYZ based on commits A through C", which as an engineer, makes presentations building much less painful.

This uber limit is not high compared to the big SV companies.

I would suggest you examine current harness memory persistence. Any reprimand you give your model will be remembered, in the same way a puppy that has a bad social experience will become more shy.

They will not save you from every pitfall, but that isn't the point; engineers walk into pitfalls all the time. This can get you in, and out, much much quicker.

I think they have the capabilities to execute a well defined plan. If you truly don't believe that, then you I suspect any work you do as a programmer will not survive the coming changes.

It's not exactly what it is; they now model an incredibly complex markov process, and harnesses that control how that thinking is done.

Is this any different than how a PM gets a programmer to work on a project? They think, then they deliver. If given more time, maybe they deliver something better. Maybe they consult some text and try to apply a design pattern.

The LLM in this use case is perfect because almost everything involved is text based, and the model is able to take in all the expressive that is language.

I don't think LeCun is saying they won't be able to program. I think he says we won't hit AGI. Programming does not require AGI; it's a pretty specific skill!

-- I think this article is COPE, if I'm being quite honest. I thought of putting cute analogies, like the C programmers saying the Python and Javascript programmers are not "hardcore" enough... but the truth should be obvious to anyone using LLMs effectively.

-- Current AI is a much better programmer than 100% of people and when directed by someone in that top 10%, it's a force majeur.

Okay, but I think the realistic thing is * burns 18000 tokens thinking of the solution * outputs 1000 tokens of code

So you can easily follow the 1000 tokens of code, and the 18000 tokens of thinking is you sitting around waiting for your GPU to process the LLM.