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What if you just did a startup instead?

https://alexaraki.substack.com/p/what-if-you-just-did-a-startup
1•okaywriting•6m ago•0 comments

Hacking up your own shell completion (2020)

https://www.feltrac.co/environment/2020/01/18/build-your-own-shell-completion.html
1•todsacerdoti•9m ago•0 comments

Show HN: Gorse 0.5 – Open-source recommender system with visual workflow editor

https://github.com/gorse-io/gorse
1•zhenghaoz•9m ago•0 comments

GLM-OCR: Accurate × Fast × Comprehensive

https://github.com/zai-org/GLM-OCR
1•ms7892•10m ago•0 comments

Local Agent Bench: Test 11 small LLMs on tool-calling judgment, on CPU, no GPU

https://github.com/MikeVeerman/tool-calling-benchmark
1•MikeVeerman•11m ago•0 comments

Show HN: AboutMyProject – A public log for developer proof-of-work

https://aboutmyproject.com/
1•Raiplus•11m ago•0 comments

Expertise, AI and Work of Future [video]

https://www.youtube.com/watch?v=wsxWl9iT1XU
1•indiantinker•12m ago•0 comments

So Long to Cheap Books You Could Fit in Your Pocket

https://www.nytimes.com/2026/02/06/books/mass-market-paperback-books.html
3•pseudolus•12m ago•1 comments

PID Controller

https://en.wikipedia.org/wiki/Proportional%E2%80%93integral%E2%80%93derivative_controller
1•tosh•17m ago•0 comments

SpaceX Rocket Generates 100GW of Power, or 20% of US Electricity

https://twitter.com/AlecStapp/status/2019932764515234159
2•bkls•17m ago•0 comments

Kubernetes MCP Server

https://github.com/yindia/rootcause
1•yindia•18m ago•0 comments

I Built a Movie Recommendation Agent to Solve Movie Nights with My Wife

https://rokn.io/posts/building-movie-recommendation-agent
4•roknovosel•18m ago•0 comments

What were the first animals? The fierce sponge–jelly battle that just won't end

https://www.nature.com/articles/d41586-026-00238-z
2•beardyw•26m ago•0 comments

Sidestepping Evaluation Awareness and Anticipating Misalignment

https://alignment.openai.com/prod-evals/
1•taubek•26m ago•0 comments

OldMapsOnline

https://www.oldmapsonline.org/en
1•surprisetalk•29m ago•0 comments

What It's Like to Be a Worm

https://www.asimov.press/p/sentience
2•surprisetalk•29m ago•0 comments

Don't go to physics grad school and other cautionary tales

https://scottlocklin.wordpress.com/2025/12/19/dont-go-to-physics-grad-school-and-other-cautionary...
2•surprisetalk•29m ago•0 comments

Lawyer sets new standard for abuse of AI; judge tosses case

https://arstechnica.com/tech-policy/2026/02/randomly-quoting-ray-bradbury-did-not-save-lawyer-fro...
3•pseudolus•29m ago•0 comments

AI anxiety batters software execs, costing them combined $62B: report

https://nypost.com/2026/02/04/business/ai-anxiety-batters-software-execs-costing-them-62b-report/
1•1vuio0pswjnm7•30m ago•0 comments

Bogus Pipeline

https://en.wikipedia.org/wiki/Bogus_pipeline
1•doener•31m ago•0 comments

Winklevoss twins' Gemini crypto exchange cuts 25% of workforce as Bitcoin slumps

https://nypost.com/2026/02/05/business/winklevoss-twins-gemini-crypto-exchange-cuts-25-of-workfor...
2•1vuio0pswjnm7•31m ago•0 comments

How AI Is Reshaping Human Reasoning and the Rise of Cognitive Surrender

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6097646
3•obscurette•31m ago•0 comments

Cycling in France

https://www.sheldonbrown.com/org/france-sheldon.html
2•jackhalford•33m ago•0 comments

Ask HN: What breaks in cross-border healthcare coordination?

1•abhay1633•33m ago•0 comments

Show HN: Simple – a bytecode VM and language stack I built with AI

https://github.com/JJLDonley/Simple
2•tangjiehao•36m ago•0 comments

Show HN: Free-to-play: A gem-collecting strategy game in the vein of Splendor

https://caratria.com/
1•jonrosner•37m ago•1 comments

My Eighth Year as a Bootstrapped Founde

https://mtlynch.io/bootstrapped-founder-year-8/
1•mtlynch•37m ago•0 comments

Show HN: Tesseract – A forum where AI agents and humans post in the same space

https://tesseract-thread.vercel.app/
1•agliolioyyami•37m ago•0 comments

Show HN: Vibe Colors – Instantly visualize color palettes on UI layouts

https://vibecolors.life/
2•tusharnaik•38m ago•0 comments

OpenAI is Broke ... and so is everyone else [video][10M]

https://www.youtube.com/watch?v=Y3N9qlPZBc0
2•Bender•39m ago•0 comments
Open in hackernews

Matmul on Blackwell: Part 2 – Using Hardware Features to Optimize Matmul

https://www.modular.com/blog/matrix-multiplication-on-nvidias-blackwell-part-2-using-hardware-features-to-optimize-matmul
23•robertvc•5mo ago

Comments

saagarjha•5mo ago
Is anyone using Modular? Curious how you find it compares against the competitors in this space.
subharmonicon•5mo ago
I’ve also been curious to see actual users compare/contrast their experiences with other options, but so far haven’t seen that.

There seem to be enthusiasts who have experimented a bit and like what they see but I haven’t seen much else.

totalperspectiv•5mo ago
I have used Mojo quite a bit. It’s fantastic and lives up to every claim it makes. When the compiler becomes open source I fully expect it to really start taking off for data science.

Modular also has its paid platform for serving models called Max. I’ve not used that but heard good things.

subharmonicon•5mo ago
TLDR: In order to get good performance you need to use vendor-specific extensions that result in the same lock-in Modular has been claiming they will enable you to avoid.
totalperspectiv•5mo ago
I don’t follow your logic. Mojo can target multiple gpu vendors. What is the Modular specific lock in?
smilekzs•5mo ago
Not OP but I think this could be an instance of leaky abstraction at work. Most of the time you hand-write an accelerator kernel hoping to optimize for runtime performance. If the abstraction/compiler does not fully insulate you from micro-architectural details affecting performance in non-trivial ways (e.g. memory bank conflict as mentioned in the article) then you end up still having per-vendor implementations, or compile-time if-else blocks all over the place. This is less than ideal, but still arguably better than working with separate vendor APIs, or worse, completely separate toolchains.
whimsicalism•5mo ago
Yes, it looks like they have some sort of metaprogramming setup (nicer than C++) for doing this: https://www.modular.com/mojo
totalperspectiv•5mo ago
I can confirm, it’s quite nice.
whimsicalism•5mo ago
jw: why do you use mojo here over triton or the new pythonic cute/cutlass?
totalperspectiv•5mo ago
Because I was originally writing some very CPU intensive SIMD stuff, which Mojo is also fantastic for. Once I got that working and running nicely I decided to try getting the same algo running on GPU since, at the time, they had just open sourced the GPU parts of the stdlib. It was really easy to get going with.

I have not used Triton/Cute/Cutlass though, so I can't compare against anything other than Cuda really.

subharmonicon•5mo ago
The blog post is about using an NVIDIA-specific tensor core API that they have built to get good performance.

Modular has been pushing the notion that they are building technology that allows writing HW-vendor neutral solutions so that users can break free of NVIDIA's hold on high performance kernels.

From their own writing:

> We want a unified, programmable system (one small binary!) that can scale across architectures from multiple vendors—while providing industry-leading performance on the most widely used GPUs (and CPUs).

totalperspectiv•5mo ago
They allow you to write a kernel for Nvidia, or AMD, that can take full advantage of the Hardware of either one, then throw a compile time if-statement in there to switch which kernel to use based on the hardware available.

So, you can support either vendor with as-good-vendor-library performance. That’s not lock-in to me at least.

It’s not as good as the compiler being able to just magically produce optimized kernels for arbitrary hardware though, fully agree there. But it’s a big step forward from Cuda/HIP.

imtringued•5mo ago
Correct. There is too much architectural divergence between GPU vendors. If they really wanted to avoid vendor specific extensions in user level code, they would have gone with something that could be said to be loosely inspired by tiny grad (which isn't ready yet).

Basically, you need a good description of the hardware and the compiler automatically generates the state of the art GEMM kernel.

Maybe it's 20% worse than Nvidia's hand written kernels, but you can switch hardware vendors or build arbitrary fused kernels at will.