2 gut feeling concerns:

- Strict subset of go might be confusing to an agent actually (trying to use unavailable go features)

- So -> c11 source to source compile loop might be confusing to agent: if So compiles to c11 does it guarantee c11 program compiles. If runtime exception (segfault etc), is it going to be easy for agent to map that back to original So code?

> "They’re not capable of understanding a brilliant language but we want to use them to build good software. So, the language that we give them has to be easy for them to understand and easy to adopt."

This makes it a great language not just for young Googlers programmers, but also for LLM Agents!

IMO, the next big language will be similar philosophy, but without garbage collection. (is Zig the closest to filling that niche?)

Comments URL: https://news.ycombinator.com/item?id=49048742

Points: 2

# Comments: 0

Not anymore, OpenAI did sign it:

https://www.microsoft.com/en-us/corporate-responsibility/top...

Comments URL: https://news.ycombinator.com/item?id=48878666

Points: 23

# Comments: 10

Some models I tried (Mistral I think) had better tok/s, and roughly same billion parameters / scores on various benchmark... But they were _so_ verbose, that they generated many more tokens compared to a Qwen model of same caliber to answer the same thing.

So even though it had better generated tok/s, because so many more were generated, the clock time was longer.

And this compounds over mutli-turns: more generated token means more context used in the next turn (until some compaction or something runs)

>

> --jinja for tool calling support

Pretty sure this flag hasn't done anything for a while. It's enabled by default since ~November of last year

This is cool concept, would love a positive/negative sentiment computed for each comment that refers to a given word, so you can see trends of "cloudflare (positive)" vs "cloudflare (negative)" where first one counts comments only if sentiment confidence is greater than say 0.6 and the other one counts comments only if sentiment is less than 0.4 (assuming [0,1] sentiment score)

Comments URL: https://news.ycombinator.com/item?id=48576233

Points: 2

# Comments: 0

I do use it the same way as you're describing on personal projects at home, in a very crude manner (pasting code snippets in llama server web UI prompt. Next will attempt OpenCode)

At work I use it in similar manner with more mature tools, but the vast majority of token spend comes from a totally different workflow: "pretend the AI is a fleet of junior/intern engineer you're delegating work to", where the agent will on its own do the implementation, commit the changes etc.

It does indeed spend a lot of tokens wandering the codebase, talking to MCPs, loading skills etc.

Curious if you can share the prefill speed too?

I run locally on a crappy desktop (some AMD iGPU with Vulkan llama.cpp, 32 GB DDR4 RAM) for experimentation. I get 15 tok/s on generation for the qwen & gemma4 MoE models. I get around 150 tok/s prefill speed.

Reason I'm asking about the prefill is looking at my stats at work, I use between 20M to peaks of 300M input tokens daily. Some of those token are cached but in general, I seem to have roughly 500x more input tokens than output. So interested in prefill tok/s stats.

Huge Thank you for llama.cpp btw!!

Since you're running quantized (at UD-Q4_K_XL) , check out the "qat" models (unsloth/gemma-4-26B-A4B-it-qat-GGUF) !

- https://huggingface.co/unsloth/gemma-4-26B-A4B-it-qat-GGUF (With "Jun 9 Update: Added MTP support.")

- https://blog.google/innovation-and-ai/technology/developers-...

In ~2015 got an Xbox one, as a media center it was an awesome experience:

Kinect voice control to play/pause and other things way before Google home/Amazon echo ecosystem were mature.

Free OTA channels via TV tuner and well designed OneGuide (with ability to pause and rewind).

And of course all the Netflix and other apps, Plex server etc.

But strategically it seems Microsoft decided they wanted to look more like Playstation, focused on gaming (at that time paid Xbox live subscription vs free Playstation)

And as gaws points out, they seem to recently announce to double down on the gaming stuff.

So when they discontinued OneGuide. I picked Roku since they seem to be focused on the media experience primarily... but unsure how I feel about this acquisition news.

Negative externalities are hard to figure out.

Since parent mentions "toxic byproduct": Say you're the company that invented Teflon pans. you made billions. You saved billions in time for all the users of the pans... A true entrepreneurial success.

But, by how many billions did you fuck up the environment, people's health etc with the spread of PFAS everywhere?

Comments URL: https://news.ycombinator.com/item?id=48195291

Points: 19

# Comments: 1

You think you know how deep it is under because you've taken that road many times before (or in your case you have historical laser measurement)

But you don't know:

- Maybe the road under fully collapsed

- Maybe the flow of water is extremely strong, so you need to accurately estimate that too.

Right, that's just a description of the https://en.wikipedia.org/wiki/Baumol_effect

- Speculative multi threading

- Data Value Speculation

- Speculative Memory Disambiguation

- Runahead Execution

- Speculative Prefetching

- Multi-path (Dual-path) Execution (goes beyond branch prediction by computing both paths)

- Optimistic Concurrency Control (for database transactions etc)

- tech apps starting with infinite scroll (facebook, 9gag, Instagram, etc.)

- media/tech shortened content: shorter tv shows, short video content, etc.

(Tiktok is the "state of the art" of those 2 trends pushed to the max)

Specifically, we're getting more & more addicted to things that increase the dopamine spikes frequency, making it increasingly difficult to go in deep focus work.