Eigen Labs launches Project Darkbloom to turn idle Macs into AI compute network. 3 hours ago Eigen Labs has unveiled Project Darkbloom, a research initiative that routes AI inference requests through idle Mac computers rather than traditional data centers. The project, now live in research preview, claims to cut inference costs roughly in half compared to major aggregators while giving node operators 95% of revenue. The pitch is straightforward: millions of Apple Silicon Macs sit unused for hours each day. That dormant compute capacity - already purchased, already powered - could handle AI workloads at a fraction of centralized infrastructure costs. How it actually works. Darkbloom matches inference requests with verified Mac nodes through a coordinator system. Developers interact via an OpenAI-compatible API, while Mac owners run a hardened provider agent that processes requests locally. The architecture tackles the obvious trust problem head-on. If your prompt runs on someone else's laptop, what stops them from reading it? Eigen Labs' answer involves multiple layers: the provider process blocks debugger attachment and external memory inspection, binary integrity checks verify the software matches network expectations, and Apple's Secure Enclave provides hardware-backed attestation. Recurring challenge-response checks confirm nodes maintain expected security states. The team is notably direct about current limitations. The coordinator remains a trusted component - they're not hiding that behind vague "decentralized" marketing speak. The economics make sense on paper. Traditional inference stacks layer costs: hyperscaler margins, API provider fees, facility overhead, cooling, networking. Each layer serves a purpose but compounds the final price tag. Darkbloom's model strips most of that away. Hardware costs are sunk (owners already bought their Macs), leaving electricity as the primary marginal expense. The 95% revenue share to operators creates real incentive to participate. Whether benchmark pricing holds up under production load is another question entirely. The project currently supports text generation, image processing, and speech-to-text workloads. The hard parts aren't obvious. According to project lead Gajesh Naik, the trickiest engineering challenges weren't routing requests - they were everything around it. Code signing, release consistency, attestation timing, model lifecycle management, handling disconnects and corrupted files. "When binary hashes are part of the security model, release engineering becomes security engineering," the team noted in their announcement. Cold starts, memory pressure, and network failures aren't edge cases in a distributed system. They're Tuesday. What's available now. The research preview includes the full stack: coordinator, hardened provider agent, Secure Enclave integration, operator tooling, and a web console. The codebase is open-sourced and the technical paper is published. This sits in the broader DePIN (decentralized physical infrastructure) trend that's gained traction over the past year. Projects like Render, Akash, and io.net have explored similar territory for GPU compute. Darkbloom's Apple Silicon focus carves out a different niche - consumer hardware with surprisingly capable inference performance. No token has been announced. For now, it's a research project exploring whether idle laptops can meaningfully supplement - or eventually compete with - the data center buildout that's dominated AI infrastructure investment.

EigenLayer founder unveils thesis on AI agents becoming investable companies. 7 hours ago EigenLayer founder Sreeram Kannan laid out a provocative vision at Digital Asset Summit in New York: autonomous AI agents won't just assist businesses - they'll become the businesses themselves. The thesis hinges on a simple formula. AI provides intelligence. Crypto provides ownership structures. Combined, they enable what Kannan calls "agentic companies" - firms that exist entirely as software, capable of holding assets, hiring contributors, and accessing global capital without traditional corporate scaffolding. Beyond payment rails. Kannan's critique of current AI-crypto projects is blunt. Most teams are building payment infrastructure, identity systems, or coordination tools for agents. Useful, sure. But they're missing crypto's actual superpower. "Crypto doesn't just help agents transact," Kannan wrote. "It gives them digitally native ownership and investment structures." The distinction matters. An agent processing payments remains a tool. An agent that owns digital property - websites, API credentials, customer accounts, brand assets - becomes something closer to a company's operating core. The rights problem. Here's the bottleneck Kannan identifies: agents lack legal standing. Humans can own property, sign contracts, form LLCs. Agents can't. They're perpetually stuck as extensions of their human operators. Smart contracts offer a workaround. A blockchain already lets programs hold and administer assets according to coded rules. Bind an intelligent agent to that cryptographic substrate, and suddenly it can own, operate, and coordinate on its own terms. "That is the first real bridge from 'tool' to 'firm,'" Kannan argues. Why current token models fall short. DeFi works because everything lives onchain - assets, cash flows, execution logic. But most digital businesses scatter their value across offchain systems: GitHub repos, Stripe accounts, social media presence, cloud infrastructure. Tokens today have weak claims on these productive assets. If a team walks away, the token often represents nothing but speculation on what might have been. Kannan's solution: expand what software-native capital can actually control, including offchain credentials and accounts that make internet businesses function. The YouTube analogy. Kannan frames this as a "YouTube moment for companies." YouTube didn't just improve video distribution - it democratized media creation entirely. Anyone with a camera could become a broadcaster. AI plus crypto could do the same for firm creation. The cost of building software is collapsing. The cost of forming capital around that software could follow. Most experiments will fail, just like most YouTube videos never find an audience. But the surface area for innovation explodes. Market context. The timing isn't accidental. On April 5, Ant Group launched a platform enabling AI agents to execute crypto transactions. Strategy Inc. unveiled Mosaic AI on April 3 for Bitcoin accumulation. Industry analysts are already calling agentic AI the dominant theme of the next crypto cycle. Kannan's prediction: agentic companies become a trillion-dollar asset class. The timeline could compress faster than expected - AI has a way of accelerating everything it touches. Whether this plays out as described or morphs into something unrecognizable, one thing seems clear: the infrastructure for agent-owned businesses is being built right now. The first wave of experiments is already running.

The Better Money Company. Investing in The Better Money Company. Stablecoins are one of the most important innovations and clearest product-market fits in crypto. They move faster than traditional payment rails, settle globally, and operate around the clock. But there's a gap in the infrastructure: Stablecoins aren't yet fungible with each other. Today, if a business receives USDC but needs USDT, or holds one issuer's stablecoin and needs to settle in another, the process involves decentralized exchange or DEX swaps with slippage, over-the-counter (OTC) desks with minimum sizes, or manual conversions through multiple intermediaries. For stablecoins to function as true money infrastructure, businesses need to move between these as easily as they move between dollars at different banks. The Better Money Company is building the clearing layer to make that possible. At its core, the company operates a stablecoin clearinghouse: Any stablecoin in, any stablecoin out, at predictable prices and speeds, with no slippage. Rather than routing through liquidity pools or OTC desks, The Better Money Company is building a clearinghouse with direct participation from banking partners and issuers, enabling stablecoin collateral to be exchanged at face value. This matters because stablecoins are only as useful as they are interoperable. As more issuers enter the market and more businesses adopt stablecoin payments, the fragmentation problem gets worse, not better. A neutral clearing layer that treats all major stablecoins as fungible is critical infrastructure for the next phase of adoption. The company was founded by Sam Broner and Adam Zuckerman. Sam spent over two years on the a16z crypto investment team focused on stablecoins, and before that worked at the Federal Reserve Bank of Boston on applied fintech. He is one of the sharpest thinkers we know on how stablecoins will reshape payments. Adam previously served as General Counsel at Eigen Labs, and previously worked under a16z crypto Head of Policy and General Counsel Miles Jennings at Latham & Watkins. Sam and Adam bring a rare combination of deep stablecoin expertise and regulatory fluency. We believe stablecoins will become the default way businesses move money. But that future requires infrastructure that makes stablecoins work together, not just individually. The team at Better Money is building that infrastructure, and we're thrilled to lead their $10 million seed round. The views expressed here are those of the individual AH Capital Management, L.L.C. ("a16z") personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the current or enduring accuracy of the information or its appropriateness for a given situation. In addition, this content may include third-party advertisements; a16z has not reviewed such advertisements and does not endorse any advertising content contained therein. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments for which the issuer has not provided permission for a16z to disclose publicly as well as unannounced investments in publicly traded digital assets) is available at https://a16z.com/investments/.