utsav @ukrum

Introducing Kimi K3: Open Frontier Intelligence 🔹 2.8 Trillion Parameters, 1 Million Context, Native Multimodal 🔹 Kimi Delta Attention enables up to 6.3x faster decoding in million-token contexts 🔹 Attention Residuals deliver ~25% higher training efficiency at <2% additional cost 🔹 Built for long-horizon agentic coding and self-evolving workflows Kimi K3 is now live on on Kimi.com, Kimi Work, Kimi Code, and the Kimi API. Open Weights by July 27, 2026. 🔗 API: platform.kimi.ai 🔗 Tech blog: kimi.com/blog/kimi-k3

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utsav @ukrum

3 months ago

@thorstenball Haven't tried orb yet - will try it soon - loved most of what i saw (except for the few bits i didn't agree with)

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utsav @ukrum

3 months ago

1. not really - always thought tab completion was a temporary measure 1.1 yes, a bash tool can go very far on benchmarks but we still need a curated experience even if the tool set is minimal 2. to continue using my laptop, pc, all the awesome dev tools the community has built over the years - to be an active participant basically and not just be a consumer goes back to the same old debate of ends justify the means, love of the craft bla bla... kabir.au/blog/the-ctf-s…

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utsav @ukrum

5 months ago

@badlogicgames @0xblacklight I'm curious, who are the SWEs you look up to?

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utsav @ukrum

5 months ago

x algo is wilddd

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utsav @ukrum

5 months ago

miss the good old days of raymond hettinger's talks

Guido van Rossum @gvanrossum

5 months ago

PyCon US has started! So far I am very disappointed in the first keynote -- it's just a product pitch and the speaker isn't that engaging. Sorry.

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Mitchell Hashimoto @mitchellh

5 months ago

I strongly believe there are entire companies right now under heavy AI psychosis and its impossible to have rational conversations about it with them. I can't name any specific people because they include personal friends I deeply respect, but I worry about how this plays out. I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation. All those arguments are rearing their ugly heads again but now its... the whole software development industry (maybe the whole world, really). It's frightening, because the psychosis folks operate under an almost absolute "MTTR is all you need" mentality: "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" We learned in infrastructure that MTTR is great but you can't yeet resilient systems entirely. The main issue is I don't even know how to bring this up to people I know personally, because bringing this topic up leads to immediately dismissals like "no no, it has full test coverage" or "bug reports are going down" or something, which just don't paint the whole picture. We already learned this lesson once in infrastructure: you can automate yourself into a very resilient catastrophe machine. Systems can appear healthy by local metrics while globally becoming incomprehensible. Bug reports can go down while latent risk explodes. Test coverage can rise while semantic understanding falls. Changes happens so fast that nobody notices the underlying architecture decaying. I worry.

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utsav @ukrum

5 months ago

@VicVijayakumar holy c rewrite when?

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utsav @ukrum

6 months ago

lgtm

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Boaz Barak @boazbaraktcs

6 months ago

This is very cool! kyunghyuncho.me/teaching-funda…

Kyunghyun Cho @kchonyc

6 months ago

i just finished teaching <Fundamentals of Machine Learning> for computer science seniors. last time i taught this course, it was titled <Introduction to Machine Learning>, it was pre-ChatGPT and it was pre-pandemic. in other words, i taught this course in the old world, and i was

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utsav @ukrum

6 months ago

@GergelyOrosz @ashtom as long as one has their expectations in check stuff like "review is the bottleneck now" doesn't help when you are using a llm like a slot machine