0G-Labs builds a modular AI chain for blockchain and Web3 apps. It helps developers and enterprises add AI features to smart contracts and Dapps by using a programmable data availability layer that lowers storage and retrieval costs, enabling real-time on-chain data access. The platform also supports embedding machine learning models directly on the blockchain, allowing more autonomous and dynamic smart contracts. Unlike general blockchain layers, 0G-Labs focuses on scalable, cost-efficient data availability and AI integration to reduce latency and increase efficiency for decentralized applications. Its business model charges service fees for data storage, retrieval, and premium features, targeting developers who want scalable, secure AI-enabled Dapps and enterprise-grade APIs.
Work here?Claim your company
Industries
Company Size
51-200
Company Stage
ICO
Total Funding
$580M
Headquarters
San Francisco, California
Founded
2023
See people who can refer or advise you
Help us improve and share your feedback! Did you find this helpful?
Total Funding
$580M
Above
Industry Average
Funded Over
4 Rounds
Gym Membership
0G picks Singapore as global base, expands AI research into badminton. The AI infrastructure company is using Singapore as a launchpad for research, enterprise products and sports-focused real-world applications 5 Oct, 2026 For most artificial intelligence companies, Singapore is either a regional sales base or a policy-friendly testbed. For Zero Gravity, better known as 0G, the city-state is now becoming something more central: its global headquarters. The AI infrastructure company said it will invest about US$15.4 million in Singapore over the next five years, using the country as a base to grow its operations, research partnerships and developer ecosystem. The announcement was made at 0G Dev Day Singapore 2026 at the National Gallery Singapore, where close to 3,000 participants registered, including developers, researchers, businesses, investors and members of the wider technology community. The move places 0G in a country that has been working to position itself as a trusted AI hub for Southeast Asia and beyond. Singapore's National AI Strategy 2.0 has put emphasis on talent, compute access, governance and practical adoption, while the city's regulators have tried to balance innovation with safety. For companies building AI infrastructure, that mix is attractive: Singapore offers proximity to regional markets, deep pools of capital and a government keen to shape global AI standards. Senior Minister of State for Digital Development and Information and Health Tan Kiat How, who delivered the keynote at the event, framed Singapore as a place where AI products can be deployed, adapted and scaled. That message fits neatly with 0G's own pitch: build in Singapore, then export globally. Michael Heinrich, CEO and co-founder of 0G, said the company's commitment is "not simply about opening an office" but about "research, talent, innovation and long-term investment". He added: "We see Singapore not as a final destination, but really as a launchpad for the rest of the world." A headquarters play, not just an office opening. Of the planned US$15.4 million investment, around US$7.7 million will go towards establishing Singapore as 0G's global headquarters, building operations, growing the team and developing its ecosystem. The company has already committed about US$3.9 million to a four-year research collaboration with Nanyang Technological University (NTU), focused on decentralised AI and blockchain-based infrastructure. It plans to commit another US$3.1 million to research collaborations with other universities and academic partners. A further US$770,000 will support AI and badminton research with NTU and YB Badminton Academy. 0G's first physical office globally is also in Singapore, at Stamford Place. The location is symbolically convenient: the building formerly housed Singapore's National Heritage Board, a detail Heinrich has used to position the company as one building future infrastructure from a site linked to the country's past. At a practical level, the decision reflects a broader pattern in Southeast Asia's tech ecosystem. Singapore continues to attract regional headquarters for startups, fintech firms, AI companies and crypto-related infrastructure players, even when their markets, users and developer communities are spread across Indonesia, Vietnam, the Philippines, India and beyond. Its strengths lie less in domestic market size and more in regulation, talent mobility, institutional partnerships and investor access. Taking decentralised AI from lab to court. The more unusual part of 0G's announcement is not the headquarters plan, but where some of its research is going next: badminton. At Dev Day, Zero Gravity Labs and NTU formalised the next phase of their existing US$3.9 million research collaboration, expanding work in decentralised AI towards real-world applications. Sports will be an initial focus, with badminton as the starting point. The partnership, established in 2025, has been working on decentralised AI training, model alignment and verifiable AI systems. Researchers from 0G and NTU have had three collaborative research papers accepted at NeurIPS and one at ICML, two of the most closely watched machine learning conferences globally. Badminton is not a random choice. In Southeast Asia, the sport has deep cultural and competitive significance, particularly in Indonesia, Malaysia, Thailand and Singapore. Singapore's Loh Kean Yew, a former world champion, has also helped raise the sport's profile locally, while his Asian Games silver added further momentum. For AI researchers, badminton offers dense and fast-moving data. A single rally can involve rapid changes in body position, shuttle trajectory, footwork, shot selection, fatigue and tactical decision-making. Much of that is hard to capture in one clean dataset. Working with NTU and YB Badminton Academy, 0G plans to explore a badminton foundation model that combines data from players, movement, video, training and competition. Foundation models are AI systems trained on broad datasets and then adapted for specific tasks. In this case, possible uses include helping coaches spot movement patterns that are difficult to see in real time, identifying training loads that may increase injury risk, and supporting young players with more personalised feedback. "Badminton brings together frontier AI research, real-world data and a very human outcome: helping people perform better and stay healthier over time," Heinrich said. 0G Singapore also signed a three-year memorandum of understanding with YB Events and Sports for Project New Frontiers: Bringing Badminton to New Horizons. Under the partnership, 0G Singapore will commit about US$204,000 annually for three years to support youth badminton development, international competition and the exploration of AI and emerging technologies in sport. The trust layer question. Beyond sport, 0G is pitching itself as part of the infrastructure stack needed for safer AI adoption. The company describes its mission as building the "trust layer for AI", with decentralised infrastructure designed to make AI more private, verifiable, sovereign and open. At Dev Day, it showcased 0G Private Computer, a product aimed at bringing privacy and verification to sensitive AI workloads. Heinrich said the system is designed so that sensitive workloads can remain private, including from 0G itself. The broader idea is to give organisations more confidence over how data is handled and how AI workloads are processed, especially when proprietary information is involved. The company also introduced BestCEO, a ready-to-use AI solution aimed at making advanced AI capabilities accessible to businesses, including small and medium-sized enterprises, without requiring them to build AI infrastructure or applications from scratch. This is a relevant angle for Southeast Asia, where SMEs make up the backbone of most economies but often lack the technical teams or budgets to adopt AI meaningfully. The region's AI opportunity is not only about large enterprises deploying copilots, but also about whether smaller companies can use the technology without handing over sensitive data or depending entirely on foreign platforms. Rivals in a crowded AI infrastructure race. 0G is entering a crowded and fast-shifting market. In decentralised AI and compute, it sits alongside global projects such as Bittensor, Gensyn, Akash Network, Render Network and Aethir, all of which are trying to rethink how AI models, compute resources and data networks are coordinated. It also competes indirectly with hyperscale cloud providers such as Amazon Web Services, Microsoft Azure and Google Cloud, which remain the default infrastructure providers for most AI companies. The key question for 0G is whether developers and enterprises will see decentralisation and verifiability as must-have infrastructure, rather than a technically elegant alternative to existing cloud systems. Community as a test of accessibility. 0G is also trying to position AI access as a community issue, not just an enterprise problem. At its first community AI workshop in Singapore, 70 residents, including many seniors, learned about AI and built websites and applications on 0G over two days. One senior participant built a website to help people understand which health screenings they should consider at different ages, including reminders for women about mammograms. That example is small, but it points to the broader challenge around AI adoption in the region. For AI to move beyond boardrooms and developer conferences, it must become useful to ordinary users, schools, coaches, seniors and small businesses. As 0G plants its headquarters in Singapore, the company is making a familiar but ambitious bet: that the city-state can serve as a neutral, trusted base for technologies meant to travel far beyond its borders. The harder test will be whether its infrastructure can move as smoothly from research papers to badminton courts, SMEs and real-world AI systems. Editor, e27
NeoSoul closes $11M pre-Series A round backed by 0G Foundation, Amber Group, and ArkStream Capital to build AI agent trading infrastructure.
0G Labs has partnered with MiniMax to bring the M3 model on-chain through privacy computing. By: rootdata | 2026/06/11 12:43:24 0G Labs announced a partnership with the AI company MiniMax, aiming to bring cutting-edge AI models on-chain through verifiable and privacy-preserving computing technology. It is reported that the core model integrated in this collaboration is MiniMax's M3 model, which currently ranks first on the open-source model list of Artificial Analysis and tops the OpenRouter trend list. The official statement indicated that to support the launch of this collaboration, a limited-time free operation service for the model will be available from June 15 to 18. - price.
0G trains 107B parameter decentralized model with China Mobile, a first for AI above 100 billion parameters. The DiLoCoX framework achieved 357x better communication efficiency than traditional methods, all over standard 1 Gbps network links. Just now ago Training a 107-billion-parameter AI model is hard enough when you have a warehouse full of cutting-edge GPUs connected by ultra-fast networking. Doing it across decentralized clusters on a standard 1 Gbps network? That's a fundamentally different engineering challenge. 0G Labs claims to have pulled it off. The project, completed in July 2025 in partnership with China Mobile, represents the first successful decentralized training of an AI model exceeding 100 billion parameters. The research paper detailing the methodology was published on arXiv on June 26, 2025, under the code arXiv:2506.21263. How DiLoCoX actually works. The standard approach, known as AllReduce, requires all nodes to constantly share gradient updates with each other. DiLoCoX instead lets clusters of NVIDIA A800 GPUs work semi-independently, synchronizing far less frequently. The framework employs several technical innovations to make this possible. Pipeline parallelism breaks the model into stages that can be processed sequentially across devices. A dual optimizer policy uses different optimization strategies for local and global training steps. One-step-delay overlap allows computation to continue while synchronization happens in the background. And adaptive gradient compression squeezes down the data that needs to travel between clusters. The result, according to 0G Labs, is a 357x improvement in communication efficiency compared to traditional AllReduce methods, without sacrificing model convergence. Why China Mobile matters here. China Mobile is the world's largest mobile network operator. Its involvement signals something broader than a one-off research collaboration, as telecom companies sit on vast distributed infrastructure including cell towers, edge data centers, and network backbone. If decentralized AI training can genuinely work over standard bandwidth links, telecom providers could become potential hosts for distributed training networks without the need for specialized high-bandwidth interconnects. 0G Labs CEO Michael Heinrich framed the achievement in democratization terms: "DiLoCoX marks a pivotal step in democratizing LLM training." What this means for the decentralized AI landscape. DiLoCoX challenges the concentration of AI training directly. Clusters of A800 GPUs, the export-compliant version of NVIDIA's A100 available in China, were coordinated across geographically distributed locations over 1 Gbps links to train a 100B+ parameter model. In March 2026, 0G Labs announced plans to publicly retrain the model with full transparency, with a commitment to open-source its technologies. That would allow independent verification of the efficiency claims and enable other teams to build on the methodology. The key risk is reproducibility. A 357x efficiency improvement is extraordinary. Independent teams will need to validate these results before the market should price in a paradigm shift. The arXiv paper provides a starting point for that scrutiny, and the planned open-source release will determine whether DiLoCoX becomes a building block for the broader ecosystem or remains an impressive but isolated demonstration. Disclosure: This article was edited by Editorial Team. For more information on how Cryptobriefing create and review content, see its Editorial Policy.
Investing.com -- AmericanFortress has closed an $8 million seed round to develop quantum-resistant blockchain technology, Investing.com has learned.
Find jobs on Simplify and start your career today
Industries
Company Size
51-200
Company Stage
ICO
Total Funding
$580M
Headquarters
San Francisco, California
Founded
2023
Find jobs on Simplify and start your career today