the speed at which @Kimi_Moonshot shipped KimiClaw is impressive!
→ View original post on X — @soumithchintala, 2026-02-16 21:45 UTC
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the speed at which @Kimi_Moonshot shipped KimiClaw is impressive!
→ View original post on X — @soumithchintala, 2026-02-16 21:45 UTC
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You can do pretty much EVERYTHING you can do with Open Claw with Abacus AI Deep Agent Today Yes, you can also set up a telegram bot that you can send messages too…

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Get hands-on with MCP. MCP Academy is a practical, half-day training for developers building AI agents. Brought to you by Databricks and @StackLokHQ
, you’ll learn how to build secure MCP servers, curate trusted registries, and use MCP skills to expand what your agents can do.

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GroqCloud is scaling fast. 3.5M+ developers and growing. Our UK data center is now live with Equinix, bringing low-latency, deterministic inference closer to teams across Europe. 👇

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There’s no “best” AI. ChatGPT = generalist
Gemini = Google-native workflows
Claude = deep reasoning & long docs
Grok = real-time social insight
Perplexity = cited research Winners don’t pick one.
They orchestrate all.
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Paper: https://
arxiv.org/abs/2510.08191
v1
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Code: https://
github.com/TencentCloudAD
P/youtu-agent/tree/training_free_GRPO
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Which exporential are you trying to ride right now?
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I want you to spend your next 24 hours being 10x more vigilant on the things around you that AI is not amazing at today (and/or would be hard or expensive to overhaul in process improvements). Why? There are still (at least in the short-term) whitespace revenue opportunities in

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Our team is heading to India this week for the AI Impact Summit & Expo Stop by the Meta booth (Exhibition Hall 3, Booth No. 3.7) to meet our team and experience: Demos of research, including Omnilingual Automatic Speech Recognition (ASR) and SeamlessExpressive
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Great work by @FEijkelboom et al Floor Eijkelboom (@FEijkelboom) Discrete diffusion — but fast? ⚡️ Test-time inference — but for discrete data? 🧠 Categorical Flow Maps: continuous transport toward the simplex, turning discrete generation into a single-step problem. Built on Variational FM (CatFlow), we obtain (self-)distillation from scratch. Language, molecules, and test-time steering — one framework. Scaling to LLMs and foundation models next. Watch this space 👀 — https://nitter.net/FEijkelboom/status/2023412552294686734#m
→ View original post on X — @wellingmax, 2026-02-16 15:38 UTC