hakmark

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hakmark

@hakmark_

Blockchain, AI, LLMs, etc...

Berlin, Germany Sumali Şubat 2014
1.1K Sinusundan629 Mga Tagasunod
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Harry Stebbings
Harry Stebbings@HarryStebbings·
Why a16z Should Back Every Single European Founder That Moves to the US: "We should back every single European founder who moves to the us, like we should just reflexively say yes. That's a combination of two things. 1. The raw level of talent that the great education system provides. 2. The move to the US indicates a willingness to seek risk and a greater level of achievement." @pmarca Love to hear your thoughts on this @t_blom @immad @dessaigne @Bandrew @joshbuckley @collinmathilde @maccaw @taavet
Harry Stebbings@HarryStebbings

This is for everyone who has a dream that simply seems out of reach. 11 years ago I started 20VC as an 18 year old in a bedroom in London. I didn’t know a single VC and had no money. I wrote down the names of three legends of the venture world. I have had two on the show previously and today I complete the list that 18 year old boy made. This was 11 years, 3,000 shows, 3,750 hours, in the making. Never give up, never doubt yourself, stay focused, row your own race. It will come through. Welcoming Marc Andreesen to 20VC today. (Links in comments)

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nic carter
nic carter@nic_carter·
Many are wondering "what Google saw" that caused them to revise their post-quantum cryptography transition deadline to 2029 last week. It was this: research.google/blog/safeguard…
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Theo - t3.gg
Theo - t3.gg@theo·
Axios just got pwn’d. This is really bad.
Feross@feross

🚨 CRITICAL: Active supply chain attack on axios -- one of npm's most depended-on packages. The latest axios@1.14.1 now pulls in plain-crypto-js@4.2.1, a package that did not exist before today. This is a live compromise. This is textbook supply chain installer malware. axios has 100M+ weekly downloads. Every npm install pulling the latest version is potentially compromised right now. Socket AI analysis confirms this is malware. plain-crypto-js is an obfuscated dropper/loader that: • Deobfuscates embedded payloads and operational strings at runtime • Dynamically loads fs, os, and execSync to evade static analysis • Executes decoded shell commands • Stages and copies payload files into OS temp and Windows ProgramData directories • Deletes and renames artifacts post-execution to destroy forensic evidence If you use axios, pin your version immediately and audit your lockfiles. Do not upgrade.

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Ronin
Ronin@DeRonin_·
Somebody just mapped the ENTIRE Hermes Agent ecosystem 40+ skills, tools, integrations, and resources for @NousResearch's agent, all in one curated list highlights: ▫️ skills that upgrade themselves after every run ▫️ 734 security playbooks, ready to deploy ▫️ visual UI for memory, sessions, and skills ▫️ remote control your Android from your agent ▫️ Claude Code -> Hermes task handoffs ▫️ full OpenClaw migration in one command ▫️ AI council that debates before executing every entry has a real editorial description, not just a link the ecosystem most people don't know exists yet github.com/0xNyk/awesome-… [ BOOKMARK ]
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Peter Steinberger 🦞
MCPorter (MCP->CLI)🧳0.8.0 is out. - stronger OAuth handling for servers - valid JSON output on fallback paths - better mcporter call behavior and error handling - generated CLIs handle object-valued args better - keep-alive/daemon reliability github.com/steipete/mcpor…
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Matt Harrison
Matt Harrison@__mharrison__·
For my friends who are still using UV and might be a little weary about recent compromises to PyPi packages, stick this in your pyproject.toml. You can let all of those pip users find and report the compromises...
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Sharbel
Sharbel@sharbel·
the fastest growing GitHub projects this month: 1. openclaw/openclaw (122K stars) your own personal AI assistant, runs 24/7 on any OS (what I use to run all my agents) 2. obra/superpowers (30.7K stars) agentic skills framework. plug-and-play tools for AI agents 3. ruvnet/RuView (30.4K stars) turns regular WiFi signals into real-time human pose detection no cameras. no sensors. just WiFi. 4. 666ghj/MiroFish (17K stars) swarm intelligence engine that predicts anything 5. moeru-ai/airi (16K stars) self-hosted AI companion with real-time voice chat runs on your own machine. you own it. 6. shanraisshan/claude-code-best-practice (11.8K stars) the best practices repo for building with Claude Code 7. badlogic/pi-mono (11.8K stars) full AI agent toolkit: CLI, unified LLM API, web UI, Slack bot 8. bytedance/deer-flow (10.4K stars) ByteDance's open-source SuperAgent. researches, codes, creates on its own 9. shareAI-lab/learn-claude-code (9K stars) build a Claude Code clone from scratch. bash is all you need. 10. p-e-w/heretic (7.6K stars) removes guardrails from any language model automatically the pace of AI right now is insane. bookmark this. next month's list will look completely different.
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Jacob Creech
Jacob Creech@jacobvcreech·
P-Token, SIMD-266, has been approved 🎉🎉🎉 This change will drastically reduce token transfer costs and in turn increase the capacity of the network ETA to mainnet - April
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Cryptoyorman.sol |📱👾
Cryptoyorman.sol |📱👾@cryptoyormansol·
gSeek 📱 We woke up feeling generous today, so leave your .SKR and you might receive a 🎁🐼👀 👇👇👇
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Tancrede
Tancrede@Tancrededib·
A map of SF investors by stage. Curated from recommendations by SF founders, investors, and operators. Talent-first / pre-idea / pre-company >Entrepreneurs First >1517 Fund >Bloomberg Beta >Human Capital Pre-seed / pre-product / first believers >Afore Capital >Abstract Ventures >Amity Ventures >Cambrian Ventures >Caffeinated Capital >Conviction >Cowboy Ventures >Forum Ventures >Hustle Fund >Pear VC >Precursor Ventures >SV Angel >Uncork Capital >Unusual VC Seed-first / early-stage generalists >Accel >Acme Capital >Acrew Capital >Battery Ventures >Benchmark >Bessemer Venture Partners >Blumberg Capital >Bullpen Capital >Costanoa Ventures >Craft Ventures >CRV >Defy VC >Felicis >First Round >Floodgate >Forerunner Ventures >Foundation Capital >Greylock Partners >Headline >Initialized Capital >Kindred Ventures >Menlo Ventures >Redpoint Ventures >Spark Capital >Susa Ventures >True Ventures >Upfront Ventures Multi-stage / large platform firms >8VC >a16z >Bain Capital Ventures >Base10 Partners >Coatue >Francisco Partners >General Catalyst >Google Ventures >Greenoaks >Greycroft >Index Ventures >Khosla Ventures >Kleiner Perkins >Lightspeed >NEA >Norwest Venture Partners >S32 >Sapphire Ventures >Sequoia Sector-focused / thesis-driven >Abad Capital >Atomic VC >Better Tomorrow Ventures >Builders VC >Commerce Ventures >Delphi Ventures >Fifty Years >Gradient Ventures >GSV Ventures >Infinity Ventures >Lux Capital >NFX >Obvious Ventures >Patron >Ribbit Capital Broad early-stage >Draper Associates >Founders Fund >Renegade Partners >SignalFire Platform / accelerator-style >Plug and Play >Y Combinator
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Guri Singh
Guri Singh@heygurisingh·
Holy shit... Microsoft open sourced an inference framework that runs a 100B parameter LLM on a single CPU. It's called BitNet. And it does what was supposed to be impossible. No GPU. No cloud. No $10K hardware setup. Just your laptop running a 100-billion parameter model at human reading speed. Here's how it works: Every other LLM stores weights in 32-bit or 16-bit floats. BitNet uses 1.58 bits. Weights are ternary just -1, 0, or +1. That's it. No floats. No expensive matrix math. Pure integer operations your CPU was already built for. The result: - 100B model runs on a single CPU at 5-7 tokens/second - 2.37x to 6.17x faster than llama.cpp on x86 - 82% lower energy consumption on x86 CPUs - 1.37x to 5.07x speedup on ARM (your MacBook) - Memory drops by 16-32x vs full-precision models The wildest part: Accuracy barely moves. BitNet b1.58 2B4T their flagship model was trained on 4 trillion tokens and benchmarks competitively against full-precision models of the same size. The quantization isn't destroying quality. It's just removing the bloat. What this actually means: - Run AI completely offline. Your data never leaves your machine - Deploy LLMs on phones, IoT devices, edge hardware - No more cloud API bills for inference - AI in regions with no reliable internet The model supports ARM and x86. Works on your MacBook, your Linux box, your Windows machine. 27.4K GitHub stars. 2.2K forks. Built by Microsoft Research. 100% Open Source. MIT License.
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christina
christina@cszhu·
prizes: $80k+ USD, free airfare/hotel/ticket to @GoogleCloud next (las vegas this year!), also, I will personally buy you tacos from tacos el gordo from the strip.
Google for Developers@googledevs

Stop typing, start interacting! The Gemini Live Agent Challenge is here. ✨ Build the next generation of interactive agents using Gemini and @GoogleCloud. Win big prizes and a trip to Google Cloud Next '26! ✈️ Register by March 16: 👉 goo.gle/4uk4VOR #GeminiLiveAgentChallenge

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Superteam Germany
Superteam Germany@SuperteamDE·
We told you something massive is coming this summer .. Interact with this tweet, we'll be watching 👀
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Denis
Denis@ImDenixSol·
Who wants some $SKR? Drop your .skr below An airdrop might land in your wallet
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Michelle Fang 🌁
Michelle Fang 🌁@michelleefang·
If you're new or looking to get more connected to SF tech: bookmark these 62+ irl events 🗓️ A list of what's happening this week (March 9 - March 16) ⬇️
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Jeddi
Jeddi@antinertia·
soon, every startup will raise $10M for 10% in their first round and hitting $50M ARR in 12 months won’t be impressive anymore the new playbook: - build with Claude Code & Codex - distribute via creators + Meta ads - and add enterprise motion with autonomous GTM engineering (hi openclaw) that's it
Dalton Caldwell@daltonc

A message for YC W26 founders

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cherry.fun
cherry.fun@cherrydotfun·
Another Seeker-only airdrop is coming 👀 We're hosting a sponsored drop exclusive to Seeker owners. ✅ Join the Seeker Club on Cherry ✅ Turn notifications on ✅ Stay tuned for the announcement Drop your .skr 👇
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LangChain
LangChain@LangChain·
🚀 New LangChain Academy Course: Building Reliable Agents 🚀 Shipping agents to production is hard. Traditional software is deterministic – when something breaks, you check the logs and fix the code. But agents rely on non-deterministic models. Add multi-step reasoning, tool use, and real user traffic, and building reliable agents becomes far more complex than traditional system design. The goal of this course is to teach you how to take an agent from first run to production-ready system through iterative cycles of improvement. You’ll learn how to do this with LangSmith, our agent engineering platform for observing, evaluating, and deploying agents. Enroll for free ➡️ academy.langchain.com/courses/buildi…
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