Fugu stands shoulder-to-shoulder with leading models like Fable and Mythos across the industry's most rigorous engineering, scientific, and reasoning benchmarks. Read the full blog: sakana.ai/fugu-release Beyond Bigger Models: Why are Orchestration Models the Next Frontier Progress in AI has been driven largely by giant, monolithic models. But the most powerful systems of the future will be collaborative ecosystems. Today, this orchestration is no longer just a technical optimization. It has become a geopolitical and operational imperative. For an organization or a nation, relying on a single company's model for critical infrastructure, finance, or governance is a material vulnerability. This risk is no longer a hypothetical possibility, but a reality. As we have seen with recent export controls imposed on models like Fable and Mythos, access can disappear overnight. Collective intelligence is the practical hedge against this concentration of power. Because Fugu orchestrates an underlying pool of swappable agents, it simply routes around vendor restrictions. By orchestrating the world’s models, we are delivering the resilient blueprint required for true AI sovereignty.

I could be wrong. But I think at the earliest stages, 90% of VCs are passing because of the founder. But you can’t come back from “I’m not inspired by you as a person,” so you find a reason that’s less arguable / more opaque in case the founder pivots and proves exceptional.

Late 00s/early 10s in SF was a magical time. Get an apartment in North Beach in the same building as the few YC founders who decided to live in SF (can you even be successful if you aren't in Palo Alto?), share a cheap office with friends on 2nd and Howard, pay yourself $70k/yr. Play a weekly poker game where losing $20 is really painful. Meet kids with $100k/yr offers from Microsoft which seems like more money than any 22yo should ever make. Go out to Northstar, or Grant & Green, or Bus Stop, or bottomless mimosa brunch at Lime. Cram as many people as possible into a run down ski house in South Lake Tahoe in the winter, or play Settlers to see who gets their own bed in the most run down $40/nt motel in town with people whose companies will go public or be acquired for hundreds of millions later who are building because they love it and can't imagine doing anything else for any amount of money.

If you're a researcher looking to: → conduct rigorous studies on how multiple models can outperform the frontier → leverage data from the largest LLM marketplace (150 trillion tokens processed per month) ... DM me with your work! We have an exciting role coming in the future, but might fill it opportunistically.

Game theory from here is super interesting: Original Mags (Google, Amazon, Microsoft, Meta) now have a serious non-zero opportunity to tank the frontier labs. Go to the government, kneecap the labs’ motion of putting the latest models out in the wild, become the trusted gatekeeper between the labs and the public at large (including internationally) by having the labs go through their clouds (AWS, GCP, Azure) and implement strict KYC to seal the deal. The frontier labs should have seen this coming years ago and implemented a robust KYC for just this moment. The fact they didn’t is kind of concerning. Why did they not do it? Best guess is because it would have changed the run-rate revenues (downward) which would have then changed funding dynamics - lower valuations, more dilution, less secondary. A valuation reset may happen now anyways, except the labs may end up with less control and more restrictions at the end of it. At the same time, everyone is already clamoring about token prices of the old models from the labs anyways… This couldn’t be a better setup for open source and neoclouds. Big question is can they meet the moment? There are too few of them and their progress seems sporadic at best.

One piece of advice we got during YC was to explain our company using verbs instead of nouns. Early on, I walked into a meeting and did the opposite: “We’re building a cloud platform for AI” No one knew that that meant, their eyes glazed over. Then I started saying this instead: “We containerize your code and run it on GPUs in the cloud so you don’t have to manage the infra yourself” That clicked way more. Our brains understand verbs because they’re more concrete. If you describe your company using nouns, you risk people not understanding you. And no one buys or invests in things they don’t understand.

“don’t train your own model” is common ai advice. it's wrong. your token bill's the proof. today, we’re excited to launch castform into open preview. castform is the easiest way for you to train your own model, on your own data. open-weights models are performant and much cheaper. when trained on your task & proprietary data, they beat closed models. the thing standing between you and that was weeks of plumbing & years of ml expertise. with castform, model training is as simple as prompt engineering. @castformai bring your agent traces or raw corpora. castform turns it into training data, picks the right algorithmic recipes, manages gpus, and gives you an ide to watch and chat with your model as it learns. see what you can build with castform👇

We are incredibly excited to announce River AI. Our mission is to create personal AI that is owned and shaped by you. Today’s best AIs are controlled by a few large corporations. We are building the alternative: a new, personal stack for AI that works entirely for you, shares your values, and operates on your terms.

Co-sign.