Shivay Lamba✓

What an amazing day! Presented a poster at @PyTorch Conference: how we optimised the RLM paper with pre-fix caching & batched Sub calls with @vllm_project And a full house for our Pytorch Conference talk on running LLMs using Executorch on Android!

RT @claudeai: New in Claude for Legal: a gallery of ready-made artifacts for contract review, regulatory horizon scans, cite checks, and more. Start from the built-in example, add your own documents and connectors, and share it with anyone across the business.

RT @liquidai: Introducing 𝙻𝙵𝙼𝟹: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence. > 6 model instances, across text, audio, vision, and omni modalities, generative and decision models. > 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window. > 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding > 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages. > 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language. > 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input. > fine-tune on 1 GPU. > a new tri-hybrid architecture > architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs. > 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters. > 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒 Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device. 1/ 🧵

RT @tim_cook: We brought Touch to the Mac! From the all-new iPad mini to the 14-inch MacBook Pro and iMac... and now MacBook Pro with PROLED XDR Display and Touch, creators have new tools to do their best work yet.

RT @Astrodevil_: open models with 1M context are kind of wild for exploring codebases. gave it the whole hono repo, 467 files and 660K tokens, in one prompt to DeepSeek V4.1 Flash 1017 few seconds later it had a map of the framework and a tour of how a request finds its route, every step pointing at real lines. then i asked a question, a follow-up, and had it write docs for all 13 modules. ✅ basically gitdiagram + deepwiki + codetour + codeviz in one open source tool. whole session cost $0.63 on @nebiustf bring your own key. runs in one docker container, works on your local folders and PRs too

RT @GoogleDeepMind: Gemini 4 Carbon is our next frontier model. It’s state-of-the-art across cybersecurity and long-horizon capabilities.

RT @OfficialLoganK: Introducing Gemini 4 Carbon, it's a big jump over Argon which we released just 2 weeks ago. Gemini 4 Carbon is SOTA on cyber, long horizon tasks, ranks #1 on Artificial Analysis V5, significantly improves on usability in domains like coding, and is more aligned.

RT @sujee_dev: What actually happens when you call an LLM API? 🤔 I've been working on this visual explainer for a while, and I'm excited to finally share it! 🎬 Follow a single request from client → gateway → tokenizer → router → queue → GPU (prefill + decode) → streamed response. Along the way, explore optimizations like: KV caching / Prompt caching Cache-aware routing Continuous batching Disaggregated prefill/decode Speculative decoding I recently gave a talk on this at Hacktoberfest 2026, but here's the entire journey in just 5 minutes! Watch it and let me know what you think! 👇 Full talk and repo in the reply.

RT @Astrodevil_:

RT @reflection_ai: We ran ~1.3 billion sandboxes in our largest RL run for Beam - spanning RL training, evaluation, and ablations. With evals and other RL experiments running, the fleet peaked at 883,006 vCPUs (83% of allocatable) across 23 clusters on @googlecloud and @awscloud. We plan to use OpenEnv (now part of @AgenticAIFdn) for future runs, bringing our learnings to the open ecosystem.

RT @Prince_Canuma: Today we're coming out of stealth, introducing Neywa Labs 🚀 We built the infrastructure to build and deploy AI that runs on the devices people already own. Private, offline, unlimited. One mission: make AI available to everyone in the world.

RT @Astrodevil_: Post one backend role, get 400 applications. Half sent with one click, most submitted with Ai agents, so they all read the same 👀 So I built JobScreen, a resume score that shows its work: → Paste the job, get a scoring rubric → Drop the pile: PDFs, scans, Word files, ZIPs → Read the best first, with the resume lines behind every score → Hidden text, private or broken GitHub repos and dead links get flagged Runs on DeepSeek V4.1 Flash 1017 on @nebiustf Free and open source 🧾 Try and contribute more features👇

DeepSeek-V4.1-Flash-1017 is now available on Nebius Token Factory Stronger benchmark performance, faster task completion, and shorter outputs than the previous version, a Pareto improvement in performance and cost. try it out:

RT @coderabbitai: New in CodeRabbit Secure: Deep Scan now follows a vulnerability across your linked repos, then replays the exploit in a throwaway sandbox to prove it's real before it flags anything. Hendrik walks through this and everything else in the new update:

RT @ashtom: Agents reinvented how we produce code. It changed our tools and half of our workflow. It’s time for the other half to catch up. Today, we’re shipping Entire: the Git forge for agent-human collaboration. We’ve built @GoEntire using Entire. Now we want to see what you'll build with it. Here’s why and what’s different. 🧵

RT @Nandakishorm1: After one month of launching Laya decision model. The first open-source version of jev and first ever open-source implimentation of RLCD pipeline. Here are the numbers. And Vega U series are gradually disrupting the market for large context multimodal decision model with custom data fit and calibration without retaining

RT @jack: We believe voice is the most natural way to interact with intelligence, so we created Dessa, the most authentic full-duplex speech model ever built. Talking with it feels like talking with a person…full of emotion, nuance, pauses, and a natural cadence.

RT @trq212: I’ve left Anthropic after more than a year of working on Claude Code and seeing it scale larger than I ever imagined. I have really loved working at Ant and believe deeply in the mission, and most of all, the idea of a race to the top. The idea that if we work hard and responsibly, we can raise the bar and inspire others to great outcomes. And if we all push each other to be better, things can be radically good. I will carry the spirit of this with me forever. My colleagues at Anthropic are the most talented, thoughtful, competent, and earnest people I have ever met. I am glad they are at the wheel and trust them deeply. To the community on X, thank you for everything. You’ve made this the most fun (and sometimes stressful) job I’ve ever had. For me, it is time for a bit of a break before diving into something new. If you want more excellent Claude Code content, you should follow @addyosmani , @lydiahallie, @_catwu, @ClaudeDevs and of course @bcherny who started it all.

RT @nebiustf: Cached tokens are now live on Nebius Token Factory⚡ Reusing context across requests? Cached input can help reduce costs. See cached-token usage in API responses and billing, with pricing per model. More info:

RT @Arindam_1729:

RT @Kimi_Moonshot: Introducing Kimi K3.1 Pro: our most capable 3T-class open-weight model. 🔹 1M-token context, 2.8T total / 104B active params (MoE), Multimodal. 🔹 Full-project coding: games in Unreal, Unity & Godot. 🔹 Excels at parametric 3D modeling in Blender & CAD. 🔹 More reliable at finance work: Accurate modeling with hallucination down by 65%. 🔹 Matching the strongest proprietary models across coding, agentic and knowledge benchmarks. Kimi K3.1 Pro and K3.1 Pro Highspeed (2–3× faster) are now live on Kimi Work, Kimi Code, and the Kimi API. Open weights by Nov 4, 2026. 🔗 API: 🔗 Tech blog:

RT @reach_vb: past ~48 hours in security: > PHP: unauthenticated remote code execution > GitLab: CVSS 10.0 remote code execution > Node.js: Brotli decoder RCE + 9 other flaws > Chrome: 353 security fixes > Signal: a bug that can prevent calls fully ending > eMudhra: compromised CA keys > Oracle: 1,295 security patches > Fortinet: critical/high fixes > Atlassian: 176 vulnerability entries and that’s after the Linux VM escape disclosed last week. ask Codex / your agent to check your code, dependencies and infrastructure for exposure to these. set up automations to regularly check for newly disclosed vulnerabilities and flag what needs patching.

RT @Kimi_Moonshot: Meet Kimi K3.1 Pro, our most capable 3T-class model.