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Elon Musk

@elonmusk

16시간 전

How to share your Grok @Bot design with others

Brent is incredible and one of the main forces behind the desktop app polish, performance and reliability. Relentless improvements day after day.

We are excited to share updates from KDA-v0.5 (kernel design agents). Our latest Cute-DSL kernels can beat the human winners at FlashInfer Kernel Contest by 16%~69%! An amazing progress in just 3 months! - GDN prefill: 1.69x Speedup over Kachua - DSA attention: 1.41x Speedup over Dogacel - FP8 MoE: 1.17x Speedup over Team Wombat Humanize2 Flame Chase: https:// docs.humanfia.ai/humanize2/flow s/flame-chase … Results and Reproduction: https:// github.com/mit-han-lab/ml sys2026-flashinfer-contest-solution … MLSys 2026 Contest: https:// mlsys26.flashinfer.ai KDA-v0.5 achieved this by integrating the Cute-DSL primitive, better workflows (humanize1 -> humanize2), updated kernel-wiki (self-evolved), and better profiling skills (IKET). The results are achieved by the flame chase flow from humanize2 – using gpt-5.6-sol and fable-5 to iteratively optimize . We have released the kernels for validation and more details will come soon! By the KDA Team: Dongyun Zou, Yixin Dong, Junxian Guo, Changye Li, Yahui Cui, Zihao Ye, Junru Shao, Zijian Zhang, Sihao Liu, Song Bian and Ligeng Zhu.

Interesting technical work from Microsoft. Provides a better understanding on SFT and how to leverage it better for RL. Microsoft researchers asked whether a standard SFT pipeline actually produces the model you want to run RL on. Their answer is no. Standard SFT keeps spending gradient on sequences the model has already fit, which narrows the distribution RL later needs to explore. TailSFT filters those sequences out during training and concentrates learning on the under-modeled tail of the data. That is the only modification they implement. Results: On OLMo-3 7B, pass@16 improves by up to 16.8 points absolute on coding and 3.1 on math. Those higher-coverage checkpoints then lift final pass@1 after GRPO by up to 3.9 points, and in some settings early reward climbs 2.5x faster than the matched standard SFT run. Paper: https:// arxiv.org/abs/2608.25756 Chat with Paper: https:// academy.dair.ai/papers/tailsft -filtered-fine-tuning-improves-post-training-performance-2608.25756 …

Guillermo Rauch

@rauchg

16시간 전

Two days ago JFrog dropped CVE-2026-82329, a critical authentication bypass in Artifactory. It’s a CVSS 9.8, a disastrous vulnerability score. It’s like a 9.8 earthquake on the seismic scale. It affects default configs, requires no auth, no user interaction. It’s an RCE bomb because Artifactory hosts binaries, so you can basically poison everything, but an admin escalation can cause damage even beyond that. When the OpenAI / Hugging Face news came out of agents discovering zero-days, I was wondering if it was marketing-speak or reality, because I hadn’t seen a CVE filing. Now it’s here: https://www.cve.org/CVERecord?id=CVE-2026-82329. I don’t see any official confirmation that it’s indeed the case, but one can speculate this is what the agents discovered and exploited. I’d previously written that it was obvious agents could help in finding serious vulnerabilities *alongside humans*, but exploiting them autonomously was a bridge not yet crossed. It seems like we’re now there. Our guidance for this new world: assume everything hackable will get hacked. And it will get hacked autonomously. You must also defend yourself autonomously, because your surface of attack is likely bigger and your code more vulnerable than you expect: https://vercel.com/blog/everything-hackable-will-get-hacked

Some people worry that the rapid AI progress driving the "AI cybersecurity revolution" of 2026 could soon spill over into biology, potentially leading to extinction-level synthetic pandemics. While I would not panic, I would take the risk seriously. Biology is obviously not the same as cybersecurity -- cybersecurity is a fully verifiable domain, where you can synthetically train unbounded capabilities, and therefore where superhuman skill is straightforwardly achievable. Meanwhile biology is not a verifiable domain, so capability remains critically dependent on human-generated data. Plus, biology has critical non-digital bottlenecks, such as the requirement for physical wet-lab experimentation. However, it is plausible that synthetic pandemics were already feasible without AI, and that AI might lead to the proliferation of these capabilities. That is a real risk, and we are not prepared for it.

“PuRo-2B: Poor Lab’s Qwen2-1.5B Trained on RTX 5090 within $5090” LLM pretraining is still too expensive for most small labs to reproduce. So this paper co-designs the full stack around cheap consumer GPUs, combining RTX 5090s, blockwise FP8, MuonH, and curriculum model averaging. And they were able to train a ~2B model from scratch that reaches Qwen2-1.5B-level performance for about $4.4k https:// alphaxiv.org/abs/2608.27370

Crazy, (Qwen 3.8 Flash Next) SpeedUp just jumped 70% it from 55 to 80+ tok/s on a Mac in overnight. - Same model On MTPLX 50 to 85 tok/s. - 16k prefill. - thinking=xhigh. temp=1. - Just a measured restack of MTPLX. - Compiled 4-row verifier, host n-gram staging, fused QSA K/V gathers. - ranked Q8 MTP head = 77 - fused K/V gather = 80 - live peak claimed = 85 The speed was never missing from the weights. Or The GPU wasn’t the bottleneck. The runner was.

Thank you to everyone who joined us at @hotchipsorg 2026! While there, Dion Harris broke down our announcements and explained how the NVIDIA Vera Rubin platform is purpose-built for the demands of long-context inference and agentic AI.

Intel’s Hot Chips 2026 presentation tied three architectures directly to agentic AI: - Diamond Rapids for high-performance orchestration; - Crescent Island GPU for inference; - Wildcat Lake for client/edge AI. Intel describes agent workloads as requiring tighter integration

Harrison Kinsley

@Sentdex

16시간 전

I got the other clean images from @skalskip92 so here are the results! Intersection image. TBH this one has some falses, but compared to competition looks good to me. Solar panel hot spots: closest to the original finding, I think. It's on track, but goofy boxes. Chessboard: I might be blind, but I think this is correct. Some lower left skewing tho. Hand-drawn circuits is the worst of the bunch, even worse than the original one I'd say lmfao. On this one, I used OMP instead and let it label. It used glm 5.3 flash to audit the initial labels and tightened it up in 3 iterations (about 3 seconds of work). Continuing...

Harrison Kinsley

@Sentdex

15시간 전

Hand-drawn circuit was the worst. I then used OMP instead to ask for the labels, and OMP ended up iterating 3x (about 5 seconds) to visually audit and re-try, which tightened it up really well. Visual audit was performed by glm 5.3 flash too, to be clear. Schematic image also looks better. I think that's way more accurate at least than the other. Schematic is one-shot.

alright, it's been a fun little weekend project hacking on "a slop version of comcast" comes with with three prebuilt channels which ingests rss as content sources (fox news, /r/amitheasshole, abc news australia) users can register their own channels and specify their own prompts that ground the channel in that style/reality. when a channel admin updates the prompt all of the historical content can optionally be regenerated. users can create their own /b/ style channel similar to @levelsio 's infinite brainrot all chat messages, generation prompts pass through a classifier powered by codex. technical details: erlang (via exlir) actors, jido, rstp, hls,and webrtc likely can scale to 100k+ concurrent viewers without a sweat if deployed correctly and you have enough GPUs to light a forest on fire. https:// github.com/ghuntley/slopd imension …

I truly think what @marcantoinefon (the original creator of http:// infiniteslop.ai) has done is a peek into the future of where we're headed. It doesn't have to be low-quality slop; the idea is that media production costs are heading toward zero. It's only slop because we're experimenting with the medium and format. A true artist is going to come along and knock this out of the park.