🇺🇦🇮🇱dmitriy samsonov

18.4K posts

🇺🇦🇮🇱dmitriy samsonov

🇺🇦🇮🇱dmitriy samsonov

@d0rc

programming since 1986

Milan, Lombardy Katılım Ocak 2011
2K Takip Edilen2.6K Takipçiler
Liza Rosen
Liza Rosen@LizaRosen0000·
Don’t look away! t.co/A7s0tYHcJC BREAKING: The Islamic regime in Iran has launched a mass execution campaign of innocent civilians, including women and minors, who protested against the regime. They are being executed on trumped-up charges. Some were inhumanely raped and tortured until they agreed to give false confessions on Iran’s state TV because they could no longer endure the pain and chose death over the most horrific torture possible, including sodomy, which often leads to death or suicide of many prisoners before they even receive a death sentence.
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Davis Brown
Davis Brown@davisbrownr·
Mathematicians use conjectures to point to important, open problems. We collect nearly a thousand (currently 890) recent conjectures from the math literature for a new dataset, OpenConjecture. On a subset, GPT-5.4 finds candidate proofs, and formalizes several in Lean.
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The Linux Foundation
The Linux Foundation@linuxfoundation·
Announcing the general availability of #Newton 1.0, the open-source, extensible physics engine for robot learning. Key features: • Stable articulated mechanism simulation • Hydroelastic contact modeling • Deformable body simulation (cables, cloth, rubber) • Accelerated robot learning at scale Netwon is a Linux Foundation project developed by Disney Research, Walt Disney Imagineering, @GoogleDeepMind and @nvidia Learn more: bit.ly/4cMm39x #NVIDIAGTC
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Unsloth AI
Unsloth AI@UnslothAI·
Introducing Unsloth Studio ✨ A new open-source web UI to train and run LLMs. • Run models locally on Mac, Windows, Linux • Train 500+ models 2x faster with 70% less VRAM • Supports GGUF, vision, audio, embedding models • Auto-create datasets from PDF, CSV, DOCX • Self-healing tool calling and code execution • Compare models side by side + export to GGUF GitHub: github.com/unslothai/unsl… Blog and Guide: unsloth.ai/docs/new/studio Available now on Hugging Face, NVIDIA, Docker and Colab.
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Allen Institute
Allen Institute@AllenInstitute·
The brain as it's never been seen before. Last year, scientists created the largest wiring diagram and functional map of a mammal brain to date. #BrainAwarenessWeek @dana_fdn
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abdel
abdel@AbdelStark·
Congrats to the @Kimi_Moonshot team! This is awesome. Great to see this level of research coming from open-source frontier model labs. I liked the paper so much I built a Rust implementation of it ;) Full AttnRes + Block AttnRes with two-phase inference, built using Burn (tensor library and Deep Learning Framework, in Rust, by @Tracel_AI). Runs on CPU, CUDA, Metal, wgpu. Includes an interactive TUI that trains a model live and visualizes depth attention evolving from uniform to selective in real time. Repo link and more on what is implemented in the comments.
Kimi.ai@Kimi_Moonshot

Introducing 𝑨𝒕𝒕𝒆𝒏𝒕𝒊𝒐𝒏 𝑹𝒆𝒔𝒊𝒅𝒖𝒂𝒍𝒔: Rethinking depth-wise aggregation. Residual connections have long relied on fixed, uniform accumulation. Inspired by the duality of time and depth, we introduce Attention Residuals, replacing standard depth-wise recurrence with learned, input-dependent attention over preceding layers. 🔹 Enables networks to selectively retrieve past representations, naturally mitigating dilution and hidden-state growth. 🔹 Introduces Block AttnRes, partitioning layers into compressed blocks to make cross-layer attention practical at scale. 🔹 Serves as an efficient drop-in replacement, demonstrating a 1.25x compute advantage with negligible (<2%) inference latency overhead. 🔹 Validated on the Kimi Linear architecture (48B total, 3B activated parameters), delivering consistent downstream performance gains. 🔗Full report: github.com/MoonshotAI/Att…

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φ
φ@QuanticASI·
why do we assume intelligence requires consciousness?
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Jonathan Gorard
Jonathan Gorard@getjonwithit·
I think, in hindsight, we will come to view the development of AI as more akin to a Eukaryotic Revolution than an Industrial one.
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Christos Tzamos
Christos Tzamos@ChristosTzamos·
3/4 Instead of using an external tool, the model executes the program directly via its transformer weights, producing an execution trace token by token and streaming results at more than 30k tokens/sec on a CPU. All computation is done autoregressively inside the transformer!
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Dr_Gingerballs
Dr_Gingerballs@Dr_Gingerballs·
Guys, it's time to have the conversation that @karpathy might be an idiot.
Kaito | 海斗@_kaitodev

5 minutes ago, @karpathy just dropped karpathy/jobs! he scraped every job in the US economy (342 occupations from BLS), scored each one's AI exposure 0-10 using an LLM, and visualized it as a treemap. if your whole job happens on a screen you're cooked. average score across all jobs is 5.3/10. software devs: 8-9. roofers: 0-1. medical transcriptionists: 10/10 💀 karpathy.ai/jobs

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Pedro Domingos
Pedro Domingos@pmddomingos·
When AI has made mathematicians irrelevant, they'll continue to do math like chess players continue to play chess.
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attentionmech
attentionmech@attentionmech·
Is there really a way to increase working memory for humans?
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🇺🇦🇮🇱dmitriy samsonov
@IlirAliu_ Why spend time talking about software skill issues speakers have..? Why not just use solid foundational frameworks for both research and production… sounds like pure personal marketing
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Ilir Aliu
Ilir Aliu@IlirAliu_·
The gripper misses by 2mm. Latency spikes kill your control loop. The sim-to-real gap eats weeks of engineering time you don’t have. Your model works in simulation. It even looks great in the demo. Then you deploy it… and everything breaks. Not a model, I t’s an infrastructure problem. Jensen Huang calls it the “Three Computer” challenge: The fact that Physical AI requires three fundamentally different compute workloads (simulation, training, inference) to work together seamlessly. Today, almost nobody has figured out how to connect them cleanly. At @nvidia ‘s GTC, @LightwheelAI Founder and CEO Steve Xie @bgxc , Ph.D., Ph.D. is joining Bill Vass, Evan Helda, @LerrelPinto, and Jon Quick to dig into exactly this! If you’re building robots and tired of duct-taping three disconnected workflows together, this one’s worth 40 minutes. 📍 March 16 · 4:00 PM PDT 🔗 nvidia.com/gtc/session-ca…
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bycloud
bycloud@bycloudai·
how big of a problem is this? > When backproping through the LM head, about 95-99% of the logit-gradient norm lies in directions that get projected away seems like the current workaround is just to use scaling to brute force it
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Jonathan Gorard
Jonathan Gorard@getjonwithit·
I think one of the conclusions we should draw from the tremendous success of LLMs is how much of human knowledge and society exists at very low levels of Kolmogorov complexity. We are entering an era where the minimal representation of a human cultural artifact... (1/12)
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NormaCore
NormaCore@norma_core_dev·
SO101 autocalibration 🪄✨ Software release is around the corner 👀
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