proud unix tradition.

oops I meant age 18 birthday as date of installation.

Put default birthday as date of installation. Proper verified claim. Problem solved.

Needs a blanket fort from head to screen.

I think the argument is full code sharing with web apps. Does desktop app not use crossplatform terminal APIs, instead of JS?

For my language, J, I can’t get autocomplete.

Even though J is a functional language (on extreme end), it also supports fortran/verbose python style, which LLMs will write. I don’t have the problem of understanding the code it generates, and it provides useful boilerplate, with perhaps too many intermediate variables, but with the advantage that it tends to be more readable.

Instead of code complete, I get to use the generation to copy and paste into shorter performant tacit code. What is bad, is that the models lose all understanding of the code transformation, and don’t understand J’s threading model. The changes I make means it loses all reasoning ability about the code, and to refactor anything later. Excessive comments helps, including using comments as places to fix/generate code sections.

So, I get the warning about “code you don’t understand” (but that can still happen later with code you write), and comment system helps. The other thing he got wrong is “prompt complexity/coaxing”. It is actually never necessary to add “You are a senior software…”. Doing so only changes the explanation level for any modern model, and opencode type tools don’t or separate off the explanation section.

LLM’s still have extreme flaws, but article didn’t resonate on the big ones, for me.

this week‑long autonomous browser experiment consumed in the order of 10-20 trillion tokens

at $60/m, that is $600M to $1.2B in full price cost, but 1/4 this is current standard pricing. Still, even if a buggy piece of shit, a 1-3m line code project in a week is impressive. OTOH, netscape 1.0 cost $4M to develop, with the advantage of working (though other advantage that it was your web page’s fault for not working).

They set a very challenging experiment. There is a reason for chromium being a popular base for a browser. The more interesting experiment result is if it is ever usable. Are the bugs solvable by AI.

well, all y’all’s comment karma is going to the moon, and so that proves the strategy is unstoppable!!! I too will post Nvidia if you give me that sweet.

OpenAI issued press release for hiring an ethics/guardrails officer. But the real job will be to validate fuckery, as the billionaire family member hired to pull the plug, will actually be there to prevent anyone from pulling the plug.

did it update ubuntu base version?

edit: yes. this means support for deskflow (mouse sharing)

was a decent post. A lot of time went into developing it, and @calliope@retrolemmy.com 's link isn’t fluff, and better background of the project.

returnPercentComplete =: 99 minimum lastTimeAsked + 1

an npm library to right pad strings is somewhere in there.

ok sign with middle finger…

my more practical finger binary system would have op show 6 beers. 3 beers would be thumb and forefinger. System is digits forward to enemy have missing fingers be 0, raised 1.

One of the worst things about having DST at all is that it is not standardized through world. North America has not switched yet, and people making these announcements make me think my phone is broken.

There are a lot of videos on this renaissance. Maybe an advance in electronics will make it worthwhile in hardware.

One area ternary is investigated is LLMs/classification. Bitnet was the pioneer model…

All of these datacenter deals are announced in GW. not in gpu units or gpu maker revenue. It’s part of the fuckery in deal disclosure, as definitely the GPU provider DGAFs about any of our power problems, and certainly some price per GPU is what they negotiate on.

AMD knows the bubble is going to burst

definitely not it. Anyone making better GPUs should be able to sell them at a price=performance level. LLMs themselves are forever. Running them on consumer level hardware with privacy is an attractive alternative to US military/Skynet allied OpenAI datacenters. That does mean smaller models than “skynet frontier”.

Reaching for other explantions.

CIA allied bankster money to keep OpenAI solvent with some side deal for AMD.

AMD needed a desperate deal to have lead Skynet developer use some of its GPUs instead of only Nvidia. For all the OpenAI committments, there is both massive risk of OpenAI bankruptcy, but also no matter how good other frontier models are/can be, waiting for OpenAI bankruptcy, and buying their datacenters, makes more sense than adding your own 20.5GW (with Oracle) of GPU/power demand, and outbidding OpenAI for GPUs from non-China sources. But its not as though MSFT/GOOG/META can’t outbid for GPUs, or not make better frontier or smaller open models. I could include mechaHitler for Skynet, but the funding pockets though large, seem as though its a marketing/investment headwind for whatever good technical achievements the mechaHitler models have done. MechaHitler AI has its own financing fuckery valuations with Elon share swaps.

Already Mac M3 ultra 512gb is a great LLM machine for very large LLMs (quantized frontier models). Nvidia and AMD will have larger vram consumer GPUs soon enough. Smarter competitors than OpenAI exist in the space, and smartness goes for better cost per benchmark point and per token.

GPT 5 pro is most expensive model in the world at $150/Mtokens output. A $2000 5090 will output the same tokens/cost in 90 days. With privacy or something you can rent to others without Skynet oppression data concerns. On an open small model that you can posttrain to be better at the domain you are interested in than GPT5 behemoth, and rentals that use whatever domain tailored model they want. But US mega corporations already offer 10x

OpenAI losses are accelerating, and expected 2023-2028 total of $45B, with (banskter/OPenAI optimistic) breakeven in 2029. Skynet military contracts of $1T is the prize. Competition to OpenAI can be forced to provide value through smaller model performance boosts that China (Mistral from France too) already actually has the best real world value models. The previous 5090 token output comparison, gets worse on 100x cheaper small open models that exist, but the privacy and posttraining benefits, priceless.

The common weak link in all of these circular financing deals is OpenAI. Except on this one, where AMD is the weaker side. Of course this makes the banksters pump AMD stock. People like to shout AI/LLM bubble, but OpenAI and MechaHitler going for Skynet is going to get a lot of powerful sustain. Still, Skynet ambition is opposite of best path to making money/useful models until US/Israel military payday.

That’s what I meant, though specs look great, and so “unconfident in execution of future roadmap” or cost/yield issues, but tsmc has history of success in new tech generations. OTOH, Rubin is sticking with 3nm as AMD goes for 2nm on the critical part.

Something is very wrong with this deal. Can know this without knowing any specifics of what’s wrong.