This is who you’re competing against, Chinese fruit seller and chip designer. Yea, you’re cooked:

You can now run 70B LLMs on a 4GB GPU. AirLLM just made massive models usable on low-memory hardware. 𝗪𝗵𝗮𝘁 𝗷𝘂𝘀𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝗲𝗱 AirLLM released memory-optimized inference for large language models. It runs 70B models on 4GB VRAM. It can even run 405B Llama 3.1 on 8GB VRAM. 𝗛𝗼𝘄 𝗶𝘁 𝘄𝗼𝗿𝗸𝘀 AirLLM loads models one layer at a time. Instead of loading everything: → Load a layer → Run computation → Free memory → Load the next layer This keeps GPU memory usage extremely low. 𝗞𝗲𝘆 𝗱𝗲𝘁𝗮𝗶𝗹𝘀 • No quantization required by default • Optional 4-bit or 8-bit weight compression • Same API as Hugging Face Transformers • Supports CPU and GPU inference • Works on Linux and macOS Apple Silicon 𝗪𝗵𝗮𝘁 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗱𝗼 • Run Llama, Qwen, Mistral, Mixtral locally • Test large models without cloud GPUs • Prototype agents on cheap hardware

NVIDIA just removed one of the biggest friction points in Voice AI. PersonaPlex-7B is an open-source, full-duplex conversational model. Free, open source (MIT), with open model weights on @huggingface 🤗 Links to repo and weights in 🧵↓ The traditional ASR → LLM → TTS pipeline forces rigid turn-taking. It’s efficient, but it never feels natural. PersonaPlex-7B changes that. This @nvidia model can listen and speak at the same time. It runs directly on continuous audio tokens with a dual-stream transformer, generating text and audio in parallel instead of passing control between components. That unlocks: → instant back-channel responses → interruptions that feel human → real conversational rhythm Persona control is fully zero-shot! If you’re building low-latency assistants or support agents, this is a big step forward 🔥

how my codebase written entirely with claude code runs

btw, this would be a better comparison

Just spotted this in London, are you guys hiring in Europe? @vercel @rauchg

the last months i've been working on 'self', a virtual machine with native AI integration at both the instruction-set level and the stdlib level. it has its own language, and the demo below takes under 30 lines to write. more details at selfvm.run/research

BREAKING: 🇨🇭🇺🇲 Switzerland REJECTS Palantir Software Palantir Software Poses Devastating Risks - Netz Politik After a risk assessment of the use of Palantir software in Switzerland, the US corporation was rejected, despite years of courting by authorities and the army. The Swiss consider the risks too great. The fear is that Palantir is handing over sensitive data to the US and from there to Israel.

Elon Musk fired 80% of Twitter (6500 people) and everyone thought that Twitter was doomed. He was right. Everyone was wrong. It’s the management masterclass of the decade and every entrepreneur must understand why it worked 🧵:

I’m working on a rust utility to remove all node_modules that may be present on a filesystem in a recursive way. It’s called antimodules. github.com/noreplydev/antimo…

On my way to move to Barcelona and start a new position as a software developer at Protofy 👨🏽‍💻

These days I have been working on this hompage for the new project of my current company Entrii.