infocollector

This is pretty remarkable, IF someone can understand it :)

This might be reflected in upcoming metrics reported on Friday if the IPO goes through. It seems aligned with improving subscriber growth metrics, smoothing out upfront hardware costs into predictable monthly revenue, and generally increasing adoption by lowering the barrier to entry. Curious if anyone closely following the IPO story has more context on this.

I think they accidentally left out “standard data-center GPUs” from the title. That probably needs fixing. My “standard” GPU is still a 3090

Does anyone know what cards these guys are running it?

Where did you migrate out to?

This is what my default grep is. You probably want to update your comment to reflect the correct name. (ugrep)

I’ve been using AirPods Max since they first launched, and over the years I’ve tried several times to switch to Bose.

However, the Bose headphones just haven’t worked as smoothly for me from a software and integration standpoint. I tend to run into more glitches and small issues compared to the AirPods Max. I’m not sure whether that’s primarily a Bose issue or something related to Apple’s ecosystem, but my guess is that other high-end headphones probably face similar integration challenges when paired with an iPhone.

On the bright side, Max is very reliable.

Does anyone know where the STL/OBJ files for the 3d models are at?

Maybe someone here has tackled this before. I’m trying to connect Antigravity or Cursor with GLM/Qwen coding models, but haven’t had any luck so far. I can easily run Open-WebUI + LLaMA on my 5090 Ubuntu box without issues. However, when I try to point Antigravity or Cursor to those models, they don’t seem to recognize or access them. Has anyone successfully set this up?

https://learn.cisecurity.org/benchmarks - this seems broken at least right now. Are these benchmarks on github so that I can download and run it on a linux box?

It’s misleading to cite two government-funded supercomputers as evidence that NVIDIA lacks monopoly power in HPC and AI:

- Government-funded outliers don’t disprove monopoly behavior. The two AMD-powered systems on the TOP500 list—both U.S. government funded—are exceptions driven by procurement constraints, not market dynamics. NVIDIA’s pricing is often prohibitive, and its dominance gives it the power to walk away from bids that don’t meet its margins. That’s not competition—it’s monopoly leverage.

- Market power isn't disproven by isolated wins. Monopoly status isn’t defined by having every win, but by the lack of viable alternatives in most of the market. In commercial AI, research, and enterprise HPC workloads, NVIDIA owns an overwhelming share—often >90%. That kind of dominance is monopoly-level control.

- AMD’s affordability is a symptom, not a sign of strength. AMD's lower pricing reflects its underdog status in a market it struggles to compete in—largely because NVIDIA has cornered not just the hardware but the entire CUDA software stack, developer ecosystem, and AI model compatibility. You don't need 100% market share to be a monopoly—you need control. NVIDIA has it.

In short: pointing to a couple of symbolic exceptions doesn’t change the fact that NVIDIA’s grip on the GPU compute stack—from software to hardware to developer mindshare—is monopolistic in practice.

The problem I see with investing in such technologies:

  1. Satellites are too far to fight anything on ground (Power per unit area (i.e., intensity) decreases as the square of the distance)
  2. If the Satellites are relaying to things on the ground, they are also relaying their location (easy adversarial targets)
  3. In a war (they mention Ukraine in the article), first thing that is toast is these satellites.

I don't think this is the right replacement for GPS. Perhaps someone here can correct me if I am wrong?

Looks like openrouter api can be self-hosted, which means you should be able to run this locally. If anyone is able to run this with ollama, please do post how you did that? :)

The lack of a readily available, installable package (pip install pygraph - has no relation to this paper as far as i can tell) makes it difficult to fully assess the reproducibility and practical applicability of the work.

I actually agree with the article, but this piece feels like a conflict of interest — a library conducting research on how libraries improve everything.

I believe there's a balance to be struck between writing your own code and relying on dependencies. If Armin (the author of this post) is the one writing the code, I would highly recommend using that dependency!

Does anyone know - Is there a guide like this that does this with Python instead of the C Socket API?

Bug fix request: On the webpage (https://shapecatcher.com/unicodefonts.html) - the download links for the fonts is broken. Perhaps fix? Also, does it make sense to combine the OTF files into a single file that shows the match you make instead of having it broken down into multiple files?

A different perspective from the outside: Nvidia's journey features three pivotal milestones that shaped its success:

- First, the 2006 acquisition of ATI by AMD solidified Nvidia's position as a dominant player in the industry.

- Second, Geoffrey Hinton's groundbreaking work on deep learning over 25 years laid the foundation for AI advancements that aligned perfectly with Nvidia's GPU capabilities.

- Third, Nvidia's recognition of its leadership in AI has propelled it to the forefront of the technology revolution.

Impressive! Does anyone know if this is open source? Or perhaps can be run locally as a server?

Trump seems to be good for coin. He did promise to help deregulate crypto by firing the SEC chair.

- https://www.axios.com/2024/07/27/trump-bitcoin-strategic-res...

I am not sure I buy this argument that Nvidia management was complicit, but it does need investigation.

Quick question: What does DataDog's ddtrace do in the opensource version?

I've used Scalene at various times in the past few years, and always liked using it when I want to dig deeper compared to cProfile/profile. You might also want to look at:

1] https://github.com/joerick/pyinstrument

2] https://github.com/benfred/py-spy

3] https://github.com/P403n1x87/austin

4] https://github.com/bloomberg/memray

5] https://github.com/pyutils/line_profiler

Summary: Hetzner does offer reliable and cheap machines compared to AWS/Azure/GCP.

The pricing is more on par with Digital Ocean/Linode.

Can you please link me to a raised issue for this? This sounds concerning.

Perhaps you are suggesting trying to Unionize? In most public sector unions, the politicians hold all the cards of a union (Example: http://tiny.cc/b7xnzz). I wonder any checks on Amazon type companies is possible in the US, even if employees were successful in forming a union.

Thanks for writing this! This nicely breaks it down into boxes that OpenAPI deals with.

I still think OpenAPI usage is a bit confusing in general. For example, I am still waiting for a better explanation of this diagram with relation to a choice of backend (Python WSGI) + frontend (JS) combinations. Perhaps someone here has a pointer for me to read?