ducktective

Still, one thing should not be forgotten, those who fail to adapt eventually fall behind.

Adapt to what? Current LLM endgame is "wished-spec => code". Where do you fit in this? You are fighting for the last 10%, 1%, 0.1% contribution in this march of the 9s game.

Thanks for the summary!

Does anyone happen to know how to make a Windows machine, the extended display of a Linux machine? Both machines are on the same network.

I'm looking to use a Windows laptop as a mere HDMI monitor for the Linux laptop. I don't need gaming/streaming requirements. Like, can anyone list our options in 2026 as the parent comment did?

I assume one can use this Moonshine on the server (Linux laptop) and run Moonlight on the client (windows laptop)?

Not even that, libssh2 vul. that "scp"s malware from cloud to your machine...

Before the advent of LLMs, ML was used in upscaling the assets and pre-rendered backgrounds of the first 3 classic Resident Evil games: https://www.reshdp.com

Makes one wonder, why should anyone embark on learning this intricate and time-consuming art of reverse engineering when LLMs are on their way to automate it in seconds...

It's not just corpo talk. The ultimate goal in LLM and AI progress is "replacement" of professional knowledge workers. In the march of the 9s of the accuracy of the generated LLM output, the engineers role would matter less and less.

It's asking engineers to "adapt" to being efficient in filling out the last 10% then 1% then 0.1% then 0.01%.

Please explain this "adapting". The LLM sellers' holygrail is * you just need to crank our model bro *. With this mindset, there is no adaptation needed, save a couple of weeks of getting up to speed with nuances of using the models, the / commands and integration of their APIs into your workflow.

Are off-shelf GPUs (like one 3090) suitable for modern academic research on current AI advancements or is it better to rent some cloud compute?

Does anyone have rough numbers (max daily users etc) on viability of SQLite vs PostgreSQL for a typical user-facing webapp or e-commerce application?

I know due to some recent update, SQLite can support concurrent reads but still only a single writer. For which cases this would be a problem?

Some recommend it's better to start with postgres anyway if you have any remote thoughts of scaling in mind....

Like imagine editor is on ws2, you open a terminal to /tmp/ to check something quick, it scrolls to the right, then jump to ws3 for your file manager and other stuff and go back to your editor.

Now you want to access that terminal on /tmp/ again. Where was it?

In i3, I just spam-switch workspaces in this case, but at least I can find them. With scrollable wms, every ws can potentially hold that target app.

Yes, still on each workspace, everything is visible on i3. I wonder how scroll to the right differs from i3's tabbed panes.

One of the advantages of tilling wm are that every window that is run, is visible too. Nothing invisible exists.

But in this "endless horizontal tilling" scheme, the above principle would no longer hold, right?

So if one wants to open-source his project and sell it :

- Licence as AGPL

- Mention that commercial use (without having to open source the derivative work) is available

Did I get it right?

1- Is this solution useful for subscription-based contract too?

2- Does it make a difference if the product is a app, library or hardware device?

Keep up the good work! There are satisfied but silent, Matrix users too.

Would the "LLM era" revitalize languages like Ada and Haskell into mainstream?

Didn't Google say that they're gonna provide an escape hatch for students and hobbyists? So, best case scenario, we just need to tap some label 5 times to enable side-loading again.

Awesome tech!

It's not possible to run an android VM on QEMU right? As in, is it officially supported? (I know about Waydroid)

"I can't belllieeeve RMDNZ preferred L-Johnson's card to mine"

Very simple question:

How do people trust the output of LLMs? In the fields I know about, sometimes the answers are impressive, sometimes totally wrong (hallucinations). When the answer is correct, I always feel like I could have simply googled the issue and some variation of the answer lies deep in some pages of some forum or stack exchange or reddit.

However, in the fields I'm not familiar with, I'm clueless how much I can trust the answer.

Wasn't the model winning gold in IMO result of a breakthrough? I doubt an stochastic parrot can solve math at IMO level...

Well, what would you want to be? Frontend dev? Mobile dev? Script writer? Logo designer? Junior lawyer?

Let's see Paul Allen's card: https://youtu.be/E1nSwpxRuJo

Hey Veo, guess what? New plot for another Black Mirror episode just dropped

So there is no issue here at all.

  $ cat mass-marketer.py
  from openai.gpt.agents import browserDriver

LLMs are Markov Chains on steroids?

By the way, does anyone know which model or type of model was used in winning gold in IMO?

It's a great tutor for things it knows

Things well-represented in its training datasets. Basically React todo list, bootstrap form, tic-tac-toe in vue

I can't fathom why more people aren't talking about the IMO story. Apparently the model they used is not just an LLM but some RL are involved too. If a model wins gold at IMO, is it still merely a "statistical parrot"?

The year is 2035

Still talking about writing slack bots and APIs

Brother, in 2025, we are faced with two models achieving gold medal in IMO. I don't know why more people aren't talking about this. It's way waaay more serious than vibing up a React form.

At this point, I'm not even sure whether these models are simply "statistical parrots" or not. But the output of these systems or the supposed systems in 2035 having vulnerabilities that run-of-the-mill LLMs could exploit is a farfetched idea, that much I know.

I think you are very experienced in this subject. Can you explain what's wrong with WebGPU? Doesn't it utilize like 80% of the cool features of the modern GPUs? Games and ambitious graphics-hungry applications aside, why aren't we seeing more tech built on top of WebGPU like GUI stacks? Why aren't we seeing browsers and web apps using it?

Do you recommended learning it (considering all the things worth learning nowadays and rise of LLMs)

I think WebGPU is a like a minimum common API. Zed editor for Mac has targeted Metal directly.

Also, people have different opinions on what "common" should mean. OpenGL vs Vulkan. Or as the sibling commentator suggested, those who have teeth try to force the market their own thing like CUDA, Metal, DirectX