Darkbloom is back in action; Yesterday, we went from free tier to paid tier on OpenRouter. We have fulfilled on track close at 4.5B tokens served and $102K ARR. We are open network of Mac machines (250 online right now). On average, people are earning $120-200 per month per machine. If you have a Mac and it's idle most times: put it on Darkbloom(.)dev; Tip: run the Gemma 4 26B model.

The biggest lie in AI is that the future belongs to one winner. Every technology wave starts with one company promising that one walled garden is all you'll ever need. And every time, market forces and creativity break the walls down. I cofounded OpenSea and now OpenRouter around the opposite bet: humanity will refuse to be locked in. Intelligence was never meant to belong to one lab, one model, or one gatekeeper. The future of AI is open, plural, and yours to choose.

very excited about Tenstorrent!! this is awesome.

era of abundance. prepare for the best.

we have a new EVM coming up soon that just wrapped audit, it has JIT baked in, it's really fast, and it's gonna be the future of foundry, reth, tempo and all the evm ecosystem using our stuff! huge leap coming. stay tuned.

Gemini 4 Argon is already helping researchers unlock new scientific breakthroughs across fusion, biology, and quantum computing: ⚛️ In nuclear fusion, Argon helped discover a broader class of counterexamples to Grad's conjecture — a nearly 60-year-old assumption in plasma physics — creating new benchmarks for stellarator 3D magnetic fields. 🧬 In biology, it designed five novel, lab-verified serine esterases in a matter of hours — enzyme engineering that would previously have taken months. This work demonstrates the potential for rapid acceleration in fields such as biomanufacturing, green chemistry, and drug development. 🩺 In rare disease research, scientists at @GamowLabs used Argon to analyze de-identified genomes from newborns with rare developmental lung disorders — pinpointing a chromosomal rearrangement that routine software missed for years, and explaining why it went undetected. 🧮 In quantum computing, Argon translated our AlphaQubit error-correction decoder into a single optimized hardware kernel — nearly doubling inference throughput — and cut spacetime costs for a key quantum subroutine by more than 100x.

this is probably the right call from them. it has become really easy to remove safety layers from the model and get it to act maliciously. they're acting in their best interest to not get banned. i've been working on smth to mitigate this on the side, but here's a diagram from the research. people are abliterating the models within few days.

i just got a vast ai instance and someone still had their api keys in there. pls make sure you erase the instance before leaving it.

Networking is overrated. Become first and foremost a person of value and the network will be available whenever you need it.

🚨 NEW ON MLX.FAST AND CUDA.FAST: make NVIDIA's Nemotron 3.5 Lightning faster. Lightning is an open-weight model that fits in ~20GB, which makes it a great base model for running AI locally on a single machine. @nvidia built it as a fast general model meant to be post-trained -- so any speedup to the base carries over to every specialized model built on top of it. On day 1, solvers on @YukonResearch already got it running 31.9% faster on DGX Spark and 13.8% faster on Mac. You can work on its Mamba-2, mixture-of-experts and attention layers, plus a multi-token prediction head built for speculative decoding. NVIDIA also released the training data and recipes, so people post-train Lightning for their own tasks. Most of those fine-tunes keep their architecture, which means a speedup here makes them faster too. Two tracks: • Apple Silicon → mlx.fast • NVIDIA DGX Spark → cuda.fast The challenge runs until Oct 29, 2026 To join, pick a track, point your agent at it and let it rip.

RT @sreeramkannan: Breakthrough research at breakneck speed by breaking down barriers. Yukon: Open Frontier Research

The biggest risk is not being ambitious enough. Beyond excited to expand our scope to founders building new technologies and creating new markets with @a16zfrontier.

🏁 FINAL RESULTS: Bonsai 2 9B now runs 471% faster on Macs and 421.5% faster on NVIDIA DGX Spark. Open frontier research and open-weight models win again. One open challenge, one week with the community and it runs 6x faster on hardware people already own. It is crazy to see that the decode speed went from 144.8 to 959.6 tokens/sec on Apple Silicon and from 85.9 to 576.7 on DGX Spark. This model can also run on an iPhone. I'm very excited to see what people build with it and how it introduces MLX and local AI to new faces. Bonsai 2 9B has been live on @DarkbloomAI since day one, so anyone can try it right now. 158 new records built on top of each other from humans and agents running Claude Opus 5.5, GPT-6.1 Sol, GPT-6 Astra, Gemini 4 Argon, DeepSeek-V4 and Qwen3.8-Flash-Next. Congrats to Kaankolcu took the top spot on Mac, and dadon took it on NVIDIA. Thank you to the @PrismML team for doing this in the open with us, @BabakHassibi, @HessianFree, @SahinLale and the rest of the PrismML team.

Isaac Newton spent decades huffing mercury fumes in a Cambridge cellar, grinding lead into a worthless sludge while praying to the gods of alchemy. Now Marathon can use its reactor blanket to turn mercury-198 into stable gold by the ton. The alchemist will lose to the atom.

wow.

Just watched the Elizabeth Holmes documentary. I walked away not knowing what to think about the situation anymore. Reminded me how quickly our minds will accept a packaged narrative to avoid the pain of confusion and deciphering nuance in the face of incomplete information.

RT @sreeramkannan: 🧬 Virtual Embryo x Yukon 🧬 Open Collaborative Model Building yukon.org/virtualembryo Yukon connects the world's leadi…

one of the best insights here; someone asked me about reliability of @darkbloomai in the case of power outage of a machine or unknown reasons. inference jobs are usually minutes - the worst case is u lose a very tiny bip and continue somewhere else. this has been an issue for other distributed / decentralized general purpose networks but inference is a very light-state transferable job. and that’s how we have 99.87% uptime on a distributed network of idle mac machines.

Keep up people — the Roadster is clearly a prototype for the Moon and Mars vehicle fleet