Hooti

22 posts

Hooti banner
Hooti

Hooti

@HootiBrowser

Anyone can build AI. Few can make it truly work. HOOTi is the browser for real AI — powered by shared compute and MAGNET. Built by Holo Studio Co., Ltd.

Seoul, South Korea Katılım Şubat 2026
165 Takip Edilen24 Takipçiler
Hooti
Hooti@HootiBrowser·
4/ That is what HOOTi + MAGNET are building. MAGNET runs parallel hypothesis loops. HOOTi connects those loops across distributed nodes, records contribution and provenance on-chain, and creates result trust through replay-based verification and incentives. Hosted. Open. Verifiable. Permissionless.
English
0
0
1
32
Hooti
Hooti@HootiBrowser·
3/ Karpathy pointed to this direction back in March. The next step for autoresearch is not a single agent. It is large-scale, asynchronous, collaborative agents — SETI@home style. A single vendor platform cannot become the final coordination layer for the global research community.
English
1
0
1
31
Hooti
Hooti@HootiBrowser·
1/ Prime Intellect Lab is officially live. 10,000+ training runs during beta. A full-stack loop for RL environments, hosted training, evaluation, and deployment. Pricing is token-based, not GPU cluster-hour based. As a hosted autoresearch runtime, this is one of the most complete platforms in production today.
English
1
5
8
182
Hooti retweetledi
KTX Lounge
KTX Lounge@KTXLounge·
KTX Lounge 에서 🇰🇷 한국어 트위터 스페이스를 진행합니다! 📣토픽: web3 의 새로운 기회, 알파, AI x Crypto 🗓️ 시간: 8pm 수요일 5.13 KST, 7am EST 📍호스트: KTX Lounge, @hiendlessme 🎙️ 게스트: @Chris_In_Shell @weplejeff @steven_the_SAP @HootiBrowser 📁 게스트 소속 프로젝트: @KTXLounge, @Aptos, @remiliacorp333, @octralabs, @Arkenstone_Labs, @HootiBrowser 📺 미디어 파트너: @MyTokencap @OdailyChina @ChainCatcher_ @with_blockmedia @Coiniseasy 🔗 스페이스 링크: x.com/i/spaces/1RJjp…
KTX Lounge tweet media
한국어
2
8
12
23.3K
Hooti
Hooti@HootiBrowser·
4/ That is the layer HOOTI + MAGNET is building. MAGNET turns research into parallel hypothesis loops. HOOTI is designed to route those loops across distributed nodes, record experiment provenance on-chain, and verify results through Byzantine-tolerant mechanisms. AI science is crossing the peer-review threshold. Now research needs infrastructure that is open, verifiable, composable, and not owned by a single cloud. 👉Paper: arXiv 2504.08066 👉MAGNET: hooti.ai
English
0
0
1
70
Hooti
Hooti@HootiBrowser·
3/ We have seen this pattern before. YouTube, TikTok, and Instagram did not create human talent from nothing. They changed the discovery layer. People outside TV networks, agencies, and traditional gatekeepers could suddenly reach the world from their rooms. The same shift is now coming to science and research. Humanity is not short on ideas. We are short on networks that can discover, test, verify, and compound them.
English
1
0
1
99
Hooti
Hooti@HootiBrowser·
AI-generated research just crossed a major threshold. Sakana AI demonstrated that an AI-generated ML paper could pass peer review at an ICLR workshop, while the broader AI Scientist work was later published in Nature. This is not simply about replacing scientists. It signals that the research loop itself is becoming programmable. As AI agents begin generating hypotheses, running experiments, writing code, evaluating outputs, and drafting papers autonomously, the core bottleneck shifts toward infrastructure: 📍Who runs the compute? 📍Who verifies the experiments? 📍Who owns the research graph? A new research stack is emerging. Read more in threads ⤵️
Hooti tweet media
English
1
4
5
701
Hooti
Hooti@HootiBrowser·
3/ The goal is not one giant model or one isolated dApp. It is an AI-native browser layer where research paths fork, models specialize, experiments are recorded, and dApps plug into the stack. Explore the early dev browser at hooti.ai. Not open for use as a Verifiable Node yet. But, Opening soon. Paper: arxiv.org/abs/2603.25813
English
0
0
2
108
Hooti
Hooti@HootiBrowser·
2/ That is what we are building with HOOTi + MAGNET. MAGNET validated autonomous research loops across video safety, crypto prediction, and BitNet LM optimization. HOOTi connects the broader layers: Decoupled DiLoCo-style training, BitNet, AI forks, and verifiable experiment records.
English
1
0
3
136
Hooti
Hooti@HootiBrowser·
1/ The signals are converging. @sama keeps pointing at compute scarcity. @GoogleDeepMind is pushing distributed training forward with Decoupled DiLoCo. @karpathy’s AutoResearch showed that research itself can become an executable loop. The next AI stack needs a different shape.
English
1
3
7
862
Hooti
Hooti@HootiBrowser·
HOOTi + MAGNET is built around that thesis: autonomous research loops, distributed training, Byzantine-tolerant verification, and on-chain experiment records. The next AI research stack should be open, verifiable, and resilient — not centralized by default.
English
0
0
1
70
Hooti
Hooti@HootiBrowser·
Since then, we’ve migrated the HOOTi training stack from the original OpenDiLoCo path toward a Decoupled DiLoCo-style architecture. Why? Because decentralized AI cannot assume perfect clusters. Nodes fail. Hardware varies. Bandwidth is uneven. Training still has to keep moving.
English
1
0
1
90
Hooti
Hooti@HootiBrowser·
@GoogleDeepMind’s Decoupled DiLoCo made one thing clear: distributed AI training is becoming real infrastructure — not just a research optimization. Our MAGNET paper described HOOTi’s DiLoCo-based architecture for decentralized AI research. Paper: arxiv.org/abs/2603.25813
English
1
3
5
767
Hooti
Hooti@HootiBrowser·
HOOTi Browser is not just a browser. It is being built as the easiest access point into the HOOTi Network — combining a familiar browser experience with future node participation, GPU-tier compute, and contribution-based rewards. The version currently available is an early access build. For now, it mainly supports general browsing. Node participation, GPU compute tiers, and network contribution features will be enabled step by step as the full HOOTi experience moves to: hooti.ai Technical architecture: arxiv.org/abs/2603.25813 We’re building this system carefully — and we’re building it together with the community.
English
0
0
4
404
Hooti
Hooti@HootiBrowser·
3/ HOOTi is where MAGNET becomes network infrastructure. Nodes contribute compute. Agents run experiments in parallel. Discoveries compound across domains. Contribution records become auditable on-chain. Pre-mainnet. Nodes incoming. The thesis: AI research should scale like a network.
English
1
0
4
420
Hooti
Hooti@HootiBrowser·
1/ @karpathy named the problem in March. SETI@home-scale autoresearch needs more than agents. It needs distributed compute, parallel hypothesis loops, and contribution systems no single vendor owns. That is the layer HOOTi has been preparing for. [x.com/karpathy/statu…]
Andrej Karpathy@karpathy

The next step for autoresearch is that it has to be asynchronously massively collaborative for agents (think: SETI@home style). The goal is not to emulate a single PhD student, it's to emulate a research community of them. Current code synchronously grows a single thread of commits in a particular research direction. But the original repo is more of a seed, from which could sprout commits contributed by agents on all kinds of different research directions or for different compute platforms. Git(Hub) is *almost* but not really suited for this. It has a softly built in assumption of one "master" branch, which temporarily forks off into PRs just to merge back a bit later. I tried to prototype something super lightweight that could have a flavor of this, e.g. just a Discussion, written by my agent as a summary of its overnight run: github.com/karpathy/autor… Alternatively, a PR has the benefit of exact commits: github.com/karpathy/autor… but you'd never want to actually merge it... You'd just want to "adopt" and accumulate branches of commits. But even in this lightweight way, you could ask your agent to first read the Discussions/PRs using GitHub CLI for inspiration, and after its research is done, contribute a little "paper" of findings back. I'm not actually exactly sure what this should look like, but it's a big idea that is more general than just the autoresearch repo specifically. Agents can in principle easily juggle and collaborate on thousands of commits across arbitrary branch structures. Existing abstractions will accumulate stress as intelligence, attention and tenacity cease to be bottlenecks.

English
1
0
6
1.8K