Image created with gemini-3.1-flash-image-preview with claude-sonnet-4-5. Image prompt: Animation cel style image of a muscular blue-skinned genie emerging from a brass oil lamp, magical cyan wisps flowing from his hands toward an ornate wooden treasure chest with open padlock carvings, the chest overflowing with glowing scrolls showing visible code syntax, warm golden lighting, clean background with Arabian motifs, Disney quality hand-drawn aesthetic with bold outlines, jewel tone color palette, horizontal composition with space for title text across top third.
We’re now making the AlphaGenome model and weights available to scientists around the world to further accelerate genomics research. Get access here: https://x.com/GoogleDeepMind/status/2016542490115912108
Our breakthrough AI model AlphaGenome is helping scientists understand our DNA, predict the molecular impact of genetic changes, and drive new biological discoveries. 🧬 Find out more in @Nature ↓ https://x.com/GoogleDeepMind/status/2016542480955535475
Moonshot’s Kimi K2.5 is the new leading open weights model, now closer than ever to the frontier – with only OpenAI, Anthropic and Google models ahead Key takeaways: ➤ Impressive performance on agentic tasks: @Kimi_Moonshot’s Kimi K2.5 achieves an Elo of 1309 on our GDPval-AA”” https://x.com/ArtificialAnlys/status/2016250137115557953
very nice release by the kimi team, benchmarks are on par with opus 4.5, gpt 5.2 xhigh, gemini 3.0 pro there is also some nice details on the parallel RL part in the tech blog explaining how they build K2.5 agent swarm”” https://x.com/eliebakouch/status/2016025747144483060?s=20
Running Kimi K2.5 on my desk. Runs at 24 tok/sec with 2 x 512GB M3 Ultra Mac Studios connected with Thunderbolt 5 (RDMA) using @exolabs / MLX backend. Yes, it can run clawdbot.”” https://x.com/alexocheema/status/2016404573917683754
Kimi K2.5: Now Top 1 on the OSWorld leaderboard. 🏆 With its Computer Use capabilities, you can now build powerful agents that navigate and operate computer interface just like a human. https://x.com/Kimi_Moonshot/status/2017292360099762378
[AINews] Moonshot Kimi K2.5 – Beats Sonnet 4.5 at half the cost, SOTA Open Model, first Native Image+Video, 100 parallel Agent Swarm manager https://www.latent.space/p/ainews-moonshot-kimi-k25-beats-sonnet
🚨BREAKING: Kimi K2.5 Thinking by @Kimi_Moonshot debuts in Text Arena as the #1 open model, surpassing GLM-4.7 and ranking #15 overall. Highlights: – #1 Open model (+5pts vs GLM-4.7) – #7 Coding – #7 Instruction Following – #14 Hard Prompts One of only two open models to break”” https://x.com/arena/status/2016294722445443470
One-shot “”Video to code”” result from Kimi K2.5 It not only clones a website, but also all the visual interactions and UX designs. No need to describe it in detail, all you need to do is take a screen recording and ask Kimi: “”Clone this website with all the UX designs.”””” https://x.com/KimiProduct/status/2016081756206846255
AlphaGenome is our latest & most advanced genomics model published in @Nature today including making the model & weights available to academic researchers. Can’t wait to see what the research community will do with it. Congrats to the team on our newest front cover! #AI4Science”” https://x.com/demishassabis/status/2016763919646478403
I’m excited to share that AlphaGenome weights are now open!🧬 We just released the checkpoints of AlphaGenome, a DNA sequence model that helps scientists predict the molecular impact of genetic changes and do new biological discoveries”” https://x.com/osanseviero/status/2016628065422762113
We got Claude to teach open models how to write CUDA kernels. This blog post walks you through transferring hard capabilities (like kernel writing) between models with agents skills. Here’s the process: – get a powerful model (like Claude Opus 4.5 or OpenAI GPT-5.2) to solve a”” https://x.com/ben_burtenshaw/status/2016534389685940372
huge release we have been working on for a while!! Subagents, user defined agents, ask user question tool, user defined slash commands through skills,, paid Mistral plans instead of API only, and much more!!!!”” https://x.com/qtnx_/status/2016180364771742047
Open Coding Agents: Fast, accessible coding agents that adapt to any repo | Ai2 https://allenai.org/blog/open-coding-agents
🚀 Introducing Qwen3-Max-Thinking, our most capable reasoning model yet. Trained with massive scale and advanced RL, it delivers strong performance across reasoning, knowledge, tool use, and agent capabilities. ✨ Key innovations: ✅ Adaptive tool-use: intelligently leverages”” https://x.com/Alibaba_Qwen/status/2015805330652111144
New research: When open-source models are fine-tuned on seemingly benign chemical synthesis information generated by frontier models, they become much better at chemical weapons tasks. We call this an elicitation attack.”” https://x.com/AnthropicAI/status/2015870963792142563
🚨Leaderboard update: Tencent’s Hunyuan-Image-3.0-Instruct now ranks #7 in the Image Edit Arena! A new lab breaks into the top-10, closely matching Nano-Banana and Seedream-4.5. Congrats to @TencentHunyuan on the huge milestone! 👏”” https://x.com/arena/status/2015846799446311337
The most interesting insight is DeepSeek OCR 2 is how it presents a *learnable* raster order, similar to how humans scan contiguous elements in a document, instead of a ‘dumb’ raster order of left to right scanning: 1. A vanilla transformer would encode the image left-to-right”” https://x.com/jerryjliu0/status/2016319238974407146
Third party eval. DeepSeek-OCR 2 is, practically speaking, about on par with dots.ocr. Which is a good model, but nowhere near SOTA at this point. I think it’ll mainly be interesting for how much of its ideas make it into the final multimodal product.”” https://x.com/teortaxesTex/status/2016179572056678739
embedding parameters are hot again, amazing paper from LongCat Flash, concurrent with DeepSeek’s Engram! differences with Engram: -> no per-layer embedding (they tried per layer embedding (PLE) but no real gains) -> simple averaging fusion instead of Engram’s dynamic”” https://x.com/eliebakouch/status/2016577949676319092
DeepSought https://spyglass.org/deepseek-moment/
🚀 DeepSeek-OCR 2 — introducing Visual Causal Flow from @deepseek_ai, learning to read documents the way humans do — now running on vLLM ⚡ with vllm==0.8.5 day-0 support. 🧠 Replaces fixed raster scanning with learned causal token reordering via DeepEncoder V2. 📄 16× visual”” https://x.com/vllm_project/status/2016065526058090967
New DeepSeek-OCR-2 model! 1. Utilizes Qwen2 500M as a vision encoder instead of VIT 300M 2. Adds causal mask with a non causal mask 3. Accuracy boost by 3.73% to 91.09% from 87.36% 4. Edit Distance 0.100 vs 0.129 for OCR v1 And we added DS-OCR-2 fine-tuning support in Unsloth!”” https://x.com/danielhanchen/status/2016043326760485313
Hugging Face Inference Endpoint now supports deploying GLM-4.7-Flash via llama.cpp, for as cheap as $0.8/hr Using Q4_K_M and 24k tokens context length – should be enough for most use case!”” https://x.com/ngxson/status/2015763148523897097
Introducing LlamaBarn — a tiny macOS menu bar app for running local LLMs Open source, built on llama.cpp”” https://x.com/ggerganov/status/2016912009544057045
Terminally online Mistral Vibe. | Mistral AI https://mistral.ai/news/mistral-vibe-2-0
Mistral Vibe 2.0 is now available on Le Chat Pro and Team plans. Build, maintain, and ship code faster with the terminal-native coding agent by @MistralAI. Here’s what’s new 🧵”” https://x.com/mistralvibe/status/2016179799689928986
🚨MAJOR DROP: Kimi K2.5 just landed on Together AI 🚀 Introducing Kimi K2.5 from @kimi_moonshot, a 1T parameter native multimodal thinking agent with Agent Swarm orchestration and vision-grounded coding. AI natives can now use Kimi K2.5 on Together AI and benefit from reliable”” https://x.com/togethercompute/status/2016306907015938510
Introducing the Kimi Product account 🥳 Kimi Product will share features, use cases, and prompts to help you master Kimi products like Kimi Agent, Kimi Slides and Kimi Code.”” https://x.com/Kimi_Moonshot/status/2016082808834531825
Kimi K2.5 Tech Blog: Visual Agentic Intelligence https://www.kimi.com/blog/kimi-k2-5.html
> built through continual pretraining on approximately 15 trillion mixed visual and text tokens atop Kimi-K2-Base …It’s essentially a totally new model with new abilities. 30T tokens @ Muon. «Kimi K2.5 represents a meaningful step toward AGI for the open-source community» wow ok”” https://x.com/teortaxesTex/status/2016027034653164004
Kimi K2.5 API: Pro Performance, Accessible Pricing. 🔹 No more choosing between latency and cost > K2.5 delivers Turbo-level speed (60-100 tok/s) as the default. > Input pricing is 50% lower than the K2 Turbo, and only 20% the cost of Claude 4.5 Sonnet. 🔹 Optimized for Drop”” https://x.com/Kimi_Moonshot/status/2016114773407236471
🎉🎉🎉 Kimi K2.5 is on Ollama’s cloud ollama run kimi-k2.5:cloud You can connect it to Claude Code, Codex, OpenCode, Clawdbot, and Droid via ollama launch! ollama launch claude –model kimi-k2.5:cloud”” https://x.com/ollama/status/2016086374005538932
Hey @Kimi_Moonshot, this one sentence is the reason thousands of teams aren’t looking up from Qwen. Modified licenses are a scourge for enterprise teams. If A-teams use your model, people _will find out_. Insisting on a prominent logo limits your audience; it doesn’t grow it.”” https://x.com/dbreunig/status/2016531878795256286
Kimi K2.5, a new state-of-the-art open source reasoning model from Moonshot AI, is now available for Perplexity Pro and Max subscribers. We host Kimi K2.5 on Perplexity’s own inference stack in the US, giving us tighter control over latency, reliability, and security for users.”” https://x.com/perplexity_ai/status/2017333346611958179
I like Kimi K2.5, but I threw a few OOD images at it and got an absolute slop hallucination in response, guided by text alone. Kimi’s natural propensity to confidently hallucinate + “”zero vision SFT”” = not remotely in Gemini’s perceptual tier. Maybe in K3.”” https://x.com/teortaxesTex/status/2017302633048879369
Can Kimi K2.5 actually compete with closed-source models on real tasks? That’s what I wanted to find out. I set up a simple test last night. Took a UI mockup image, dropped it into Cline, and gave it the same prompt: build this website, frameworks are fine. Then I ran the exact”” https://x.com/JuanPa/status/2016634998988865571
K2.5 went through a long post-training process to really unleash the potential of the base model. Using SFT on text alone to bootstrap vision RL, and seeing vision RL improve text performance, made me rethink how generalization really works.”” https://x.com/zxytim/status/2017252738229494067
We hope TRACE enables more robust reward function design and better detection in RL training pipelines! 🤖 Dataset: https://t.co/ILAdvS4i9R Paper: https://t.co/TdcMfPhmR6 Work done @PatronusAI ❤️ Models used: @AnthropicAI @OpenAI @GeminiApp @Kimi_Moonshot @Zai_org @deepseek_ai”” https://x.com/getdarshan/status/2017054380630167804
We put the #1 open source model: Kimi-K2.5 to the test. Our AI Capabilities Lead @petergostev shares first impressions of @Kimi_Moonshot’s latest model, probing its reasoning, data visualization, and performance on complex prompts, and how it compares on Arena’s leaderboards.”” https://x.com/arena/status/2016915717539713236
Kimi K2.5 1T runs on 2 M3 Ultras with mlx-lm in it’s native precision. It’s actually quite usable. Here it’s making a space invaders game. Generated 3856 tokens at 21.9 tok/sec using 350GB per machine. Thanks to @kernelpool for the port.”” https://x.com/awnihannun/status/2016221496084205965
Kimi-K2.5/tech_report.pdf at master · MoonshotAI/Kimi-K2.5 https://github.com/MoonshotAI/Kimi-K2.5/blob/master/tech_report.pdf
Here’s a short video from our founder, Zhilin Yang. (It’s his first time speaking on camera like this, and he really wanted to share Kimi K2.5 with you!)”” https://x.com/Kimi_Moonshot/status/2016065333694771276
Here’s the command to run it and the game it made (which seems quite good): “` mlx.launch –verbose –backend jaccl –hostfile m3-ultra-jaccl.json –env MLX_METAL_FAST_SYNCH=1 — /Users/awni/mlx-lm/mlx_lm/examples/sharded_generate.py –model moonshotai/Kimi-K2.5 –prompt “”Write”” https://x.com/awnihannun/status/2016223103081443342
Kimi K2.5 tech report is beautiful”” https://x.com/eliebakouch/status/2017257476538724819
Kimi K2.5 is free for a week on Kilo Code. This model beats Opus 4.5 on several coding benchmarks.”” https://x.com/kilocode/status/2016449095511007535
Kimi K2.5 AMA on r/LocalLLaMA, don’t miss out!”” https://x.com/Kimi_Moonshot/status/2016443435553890419
Kimi K2.5 become the #1 most-used model on Kilo Code via OpenRouter. 🏆”” https://x.com/Kimi_Moonshot/status/2017105810242011285
Kimi ranks Top 3 on OpenRouter’s total usage chart 🚀 and keeps climbing up!”” https://x.com/Kimi_Moonshot/status/2017105020274233358
Making your quota go further No More Waste: In the old system, a simple “”Hello World”” cost the same quota as refactoring hundreds of lines of code. That’s history. Precision Billing: With Token-based billing, usage is calculated by actual length. Quick queries cost tiny amounts”” https://x.com/Kimi_Moonshot/status/2016918450992812443
🤗 Fireworks AI is our launch partner for Kimi K2.5. Thanks for the incredibly fast support!”” https://x.com/Kimi_Moonshot/status/2016057073000448234
Kimi K2.5 released this morning and I dug into what it’s about and seems interesting (to me): – Continual pretraining with ~15T mixed visual and text tokens (probably on top of K2 think, @eliebakouch is that what you think too?) – Max context doubled from 128k to 256k using”” https://x.com/TheZachMueller/status/2016183468430860587
@petergostev @Kimi_Moonshot Test Kimi-K2.5 for yourself in the Code Arena and see how it does with agentic tasks. Get your votes in…score release coming soon:”” https://x.com/arena/status/2016923733513105705
One more thing: you can customize your own agent using Kimi Agent SDK Check out:”” https://x.com/Kimi_Moonshot/status/2016034272998809678
After watching the video about Kimi-K2.5, it became even clearer to me how much ambition, energy, and will Chinese AI companies are really trying to put pressure on US AI companys. The agent swarm is fascinating – I love it!”” https://x.com/kimmonismus/status/2016100119100145995
Introducing Kimi Code, an open-source coding agent under the Apache 2.0 License. 🔹 Python-based, easy to extend. 🔹 Fully transparent — clear, safe, reliable. 🔹 Seamlessly integrates with VS Code, Cursor, JetBrains, Zed, and more. 🔹 Fully-featured & out-of-the-box ready.”” https://x.com/Kimi_Moonshot/status/2016034259350520226
You share, we care. Kimi Code is now powered by our best open coding model, Kimi K2.5 🔹 Permanent Update: Token-Based Billing We’re saying goodbye to request limits. Starting today, we are permanently switching to a Token-Based Billing system. All usage quotas have been reset”” https://x.com/Kimi_Moonshot/status/2016918447951925300
Kimi K2.5 is #1 on Design Arena 🏆”” https://x.com/Kimi_Moonshot/status/2017158490930999424
Kimi K2.5 is #1 Open Model for Coding 🏆”” https://x.com/Kimi_Moonshot/status/2016521406906028533
Kimi K2.5 is #1 Open Model in VoxelBench 🏆”” https://x.com/Kimi_Moonshot/status/2016732248800997727
Kimi K2.5 now on Eigent 🤗”” https://x.com/Kimi_Moonshot/status/2016473945957155252
Kimi K2.5 Tech Blog: Visual Agentic Intelligence https://www.kimi.com/blog/kimi-k2-5.html#footnotes
Kimi K2.5 tech report just dropped! Quick hits: – Joint text-vision training: pretrained with 15T vision-text tokens, zero-vision SFT (text-only) to activate visual reasoning – Agent Swarm + PARL: dynamically orchestrated parallel sub-agents, up to 4.5× lower latency, 78.4% on”” https://x.com/Kimi_Moonshot/status/2017249233775260021
Kimi K2.5 having fully multimodal understanding including video was not on my bingo card. I love it!”” https://x.com/kimmonismus/status/2016120251717714273
🧠👀 @Kimi_Moonshot just shipped Kimi-K2.5 with multimodality. Behind this big step lies a deeper question: what kind of multimodal model actually matters? Zhihu contributor & Moonshot AI researcher Lechatelia: ✨K2.5 is not “”just another VLM.”” I came from CV → VL → VLM, and”” https://x.com/ZhihuFrontier/status/2016438778030850059
🚨BREAKING: Kimi K2.5 Thinking by @Kimi_Moonshot is the #1 open model for Vision Arena! Highlights: – #1 open model in Vision (+40pt over the next open model) – #6 overall (Qwen3-vl-235b-a22b-instruct is next open model at #18) This is the only open model in the Top 15.”” https://x.com/arena/status/2016984335380001268
Kimi K2.5 Technical Report: “”early fusion with a lower vision ratio yields better results given a fixed total vision-text token budget”” – “”Visual RL Improves Text Performance”” – “”joint multimodal RL paradigm during Kimi K2.5’s post-training. Departing from conventional”” https://x.com/scaling01/status/2017255763400364049
Any guess why Kimi team calls Kimi 2.5 as ‘Native Multimodal’ & how is it different from Kimi VL? In response to this question on HF , Kimi team response was “”It is an ungraded version compared to Kimi-VL, especially featuring video understanding. Will release more details”” https://x.com/thefirehacker/status/2016223118738764081
K2.5 technical report suggests that early fusion of vision tokens is best, but they start from the K2 checkpoint and then train for 15T more tokens. Did I miss something, or does this mean they’re still kind of doing late fusion anyway?”” https://x.com/andrew_n_carr/status/2017304411345981518
K2.5 is a V3 generation model, explicitly built on V3 architecture. It’s not frontier within Moonshot’s own portfolio. They just pushed continued training further than anyone. V4 is all but guaranteed to do vastly better. Its competition will come from K3, GLM-5. Next gen.”” https://x.com/teortaxesTex/status/2016956019239272717
Kimi K2.5 widens gap between the US and China in open weights model intelligence. The leading US open weights model remains OpenAI’s gpt-oss-120b, which has now been eclipsed by an ever-growing list of open weights releases from China.”” https://x.com/ArtificialAnlys/status/2016250140219343163
Next up: Kimi @Kimi_Moonshot just released Kimi K2.5 — and Zhihu is taking it seriously 👀 💬 Zhihu contributor toyama nao: Short verdict: Kimi is back on the world stage. Last year’s K2 kicked off China’s Agent capability race. Models like GLM 4.6/4.7 and MiniMax M2/M2.1 kept”” https://x.com/ZhihuFrontier/status/2016363957876097089
Kimi just shipped Kimi-K2.5, introducing “”Agent Swarm.”” Behind it is a long process of trial, failure, and rethinking how agents should actually work 🤖✨ Zhihu contributor & @Kimi_Moonshot engineer Lidong share his deep thinking: I worked on K2.5’s agent mode. Since launch,”” https://x.com/ZhihuFrontier/status/2016811037274886377
LingBot-World from Ant Group An open-source world simulator from video generation with real-time interactivity. Maintains high fidelity across diverse environments with minute-level consistency and <1s latency at 16 FPS.”” https://x.com/HuggingPapers/status/2016787043028746284
3 layers of openness in AI Here is a practical taxonomy for decision-making. It’s not morally pure, but operational. ▪️ Open code: → Tooling, training frameworks, inference engines, evaluation harnesses, orchestration layers, dataset utilities. It’s classic open source”” https://x.com/TheTuringPost/status/2014630341349408928
🚨 New open model: Molmo 2 (Apache 2.0) by @allen_ai is available in the Arena! Come test it out with your best prompts, and we’ll see how it stacks up soon.”” https://x.com/arena/status/2015886736136798723
New American open model: Trinity-Large-Preview (400B) by @arcee_ai A frontier-scale sparse MoE you can use today, free on OpenRouter for a limited time.”” https://x.com/OpenRouterAI/status/2016280059527757995
LingBot-World is unveiled as an open-source, real-time interactive world model built on Alibaba’s Wan2.2, capable of generating. But heres the catch: nearly 10 minutes of stable, continuous generation – even after the camera looks away for 60 seconds, objects remain intact when”” https://x.com/kimmonismus/status/2016896151610442192
An open-source extension for LLM serving engines – LMCache It’s like a caching layer for large-scale, production LLM inference. LMCache implements smart KV cache management, reusing key-value states of previously seen text across GPU, CPU and local disk. It can reuse any”” https://x.com/TheTuringPost/status/2017258518857105891
We’re excited to introduce @arcee_ai’s Trinity Large model. An open 400B parameter Mixture of Experts model, delivering frontier-level performance with only 13B active parameters. Trained in collaboration between Arcee, Datology and Prime Intellect.”” https://x.com/PrimeIntellect/status/2016280792037785624
Today we’re releasing Trinity Large, a 400B MoE LLM with 13B active parameters, trained over 17T tokens The base model is on par with GLM-4.5 Base, while being significantly faster at inference because it’s sparser and hybrid The architecture we picked is one of my favorites:”” https://x.com/samsja19/status/2016283855888773277
It’s been a while since I did an LLM architecture post. Just stumbled upon the Arcee AI Trinity Large release + technical report released yesterday and couldn’t resist: – 400B param MoE (13B active params) – Base model performance similar to GLM 4.5 base – Alternating”” https://x.com/rasbt/status/2016903019116249205
Qwen https://qwen.ai/blog?id=qwen3-max-thinking
Qwen3-Max-Thinking debuts with focus on hard math, code https://www.testingcatalog.com/qwen3-max-thinking-debuts-with-focus-on-hard-math-code/
Qwen3-ForcedAligner-0.6B”” https://x.com/Alibaba_Qwen/status/2016859224077455413
📢 New Model Drop: Qwen3 Max Thinking is now live on Yupp! It’s @Alibaba_Qwen’s latest flagship reasoning model. We can’t wait to see what you learn, build and imagine – and how the model fares on our user-preference leaderboards.”” https://x.com/yupp_ai/status/2015812409823522952
🎉 Congrats @Alibaba_Qwen on the Qwen3-ASR release — vLLM has day-0 support. 52 languages, 2000x throughput on the 0.6B model, singing voice recognition, and SOTA accuracy on the 1.7B. Serve it now in vLLM! 🚀 Learn more: https://x.com/vllm_project/status/2016865238323515412
Qwen3-ASR and Qwen3-ForcedAligner are now open source — production-ready speech models designed for messy, real-world audio, with competitive performance and strong robustness. ● 52 languages & dialects with auto language ID (30 languages + 22 dialects/accents) ● Robust in”” https://x.com/Alibaba_Qwen/status/2016858705917075645
Qwen3-ASR is out🚀 https://t.co/pVnuuNPMEL ✨ 0.6B & 1.7B – Apache2.0 ✨ 30 languages + 22 Chinese dialects, plus English accents across regions ✨ Single model for language ID + ASR (no extra pipeline stitching) ✨ Qwen3-ForcedAligner-0.6B, a strong forced aligner”” https://x.com/AdinaYakup/status/2016865634559152162
Qwen3-ASR is the first open-source LLM-based ASR in the industry with native streaming support. Demo: https://t.co/y2X1slCMcs vLLM Example:”” https://x.com/Alibaba_Qwen/status/2016900512478875991
Big thanks to vLLM for providing Day 0 support for Qwen3-ASR.”” https://x.com/Alibaba_Qwen/status/2016905051395260838
What the heck: Qwen3-Max-Thinking outperforms all SOTA Models (Gemini 3.0 Pro, GPT-5.2, …) in HLE with search tools and even achieves almost 60% Overall really impressive evals! OpenAI and Anthropic have to hurry in their r&d”” https://x.com/kimmonismus/status/2015820838243561742
🚨 Qwen3 Max Thinking is in the Text Arena! @Alibaba_Qwen’s Qwen3 Max Preview debuted last fall in the top 10 – so let’s see what this variant can do. Bring your toughest prompts and we’ll see how it stacks up against other frontier AI models in the most competitive arena. 💪”” https://x.com/arena/status/2015803787680808996
LLaMA Factory – an open-source unified toolkit for training, fine-tuning, and deploying 100+ LLMs and multimodal models. It wraps training into a clear CLI + Web UI, supporting everything from SFT to RL, all without glue code. What it gives you: – Fine-tuning for LLaMA, Qwen,”” https://x.com/TheTuringPost/status/2014827186629595429
🌟🚀Sparse Attention Models Can Get Sparser We’ve updated The Sparse Frontier–the largest empirical analysis of training-free sparse attention to date–from Qwen 2.5 to 3 model families, now including Llama 3.1 and Gemma 3. Key findings: 📊 Larger sparse models outperform”” https://x.com/p_nawrot/status/2017161371566178304
Open-source robot arm meets hand tracking [📍GitHub below] It is designed with an industrial mindset but built as a 3D-printed desktop system. PAROL6 paired with a LEAP Motion controller is a nice example of how accessible robot teleoperation has become. • Hand motion is”” https://x.com/IlirAliu_/status/2014985571819548685
Open Source Robotics A curated collection of high-quality open source robotics projects, tools, and software to propel the robotics community forward. https://t.co/YwaZgyQlrj — Weekly robotics and AI insights. Subscribe free: https://x.com/IlirAliu_/status/2015347916869636144
An Open Source Dev Kit for AI-native Robotics. [📍github below ] This repo uses LeRobot’s plugin conventions to be automatically detected by a LeRobot installation in the same Python environment. https://t.co/Et5ffb8yW1 —- Weekly robotics and AI insights. Subscribe free:”” https://x.com/IlirAliu_/status/2016587843280208115
Their technical report: https://t.co/J5344msSdD On Hugging Face:”” https://x.com/TheZachMueller/status/2016183781481132443
I don’t think people have realized how crazy the results are from this new TTT + RL paper from Stanford/Nvidia. Training an open source model, they – beat Deepmind AlphaEvolve, discovered new upper bound for Erdos’s minimum overlap problem – Developed new A100 GPU kernels 2x”” https://x.com/rronak_/status/2015649459552850113
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