Power is becoming one of the biggest constraints on AI development. Intelligence can now be delivered in seconds, while the data centers and power infrastructure behind it can take years to bring online. Parallax is building a new generation of gas turbines designed specifically for AI data centers, for much faster manufacturing and deployment. We’re proud to lead Parallax’s Series A alongside @generalcatalyst and join seed investors @EclipseVentures , @Lux_Capital , @foundersfund and Valor Equity Partners in partnering with @CarlSchoeller and the Parallax team as they tackle one of the most important infrastructure challenges in AI. cc @SethGRosenberg

Excited for @GreylockVC to partner with @CarlSchoeller and the @parallax team to build the leading AI energy company @CarlSchoeller is on a relentless mission to build purpose built turbines that will power the next wave of intelligence

Proud to partner with you and the entire Parallax team! Let's build! 💪

Excited to be on @MTSlive in a bit!

Excited for @SnorkelAI to announce that they have raised $350M at a $3.5B valuation and have crossed $375M in annual revenue run rate. While AI has changed dramatically since Snorkel was founded in 2019 and we at Greylock led their Seed and Series A, Alex Ratner @ajratner and team have been consistent in their belief that data is the very core of AI. Spending years at Stanford, and then at Snorkel, pioneering a different approach to data: treating it as a product and technology problem, combining expert knowledge with deep technology to drive much higher quality data, significant technology leverage, and very attractive unit economics. Snorkel's approach is powering the agentic and RSI wave across the frontier labs, applied AI companies and large enterprises. On a personal note, I couldn't be more proud of Alex. He has navigated an industry that evolves at an extraordinary pace while maintaining unwavering focus on the company's north star and building tremendous business momentum. He is a very special leader. And as a fun relic of history: a photo of the original Snorkel team when they just got started building out of @GreylockVC's Menlo Park office :)

I'm excited to announce @SnorkelAI's $350M Series E at $3.5B, led by @insightpartners and @S32_VC. We've grown 18x+ in the last 12 months since launching our Data-as-a-Service offering, passing $375M ARRR this week. As AI advances to superhuman capabilities, AI data & environment development must advance with it - and basic staffing and crowdsourcing approaches are not enough. AI progress now requires deep research and technology work that combines human expertise with specialized AI in compounding ways. @SnorkelAI is building the RSI data engine and frontier data lab for this next phase. We're honored to have the support of existing investors Addition, @lightspeedvp, @GreylockVC, @GVteam, P7, Factory, @WellsFargo, Walden Catalyst Ventures, and new investors @ThirdPointLLC, @MarchCPs, @BlumbergCapital, @AllegisCapital, @Frontlinevc, and @standard_vc. – @SnorkelAI started as a research project a decade ago at @StanfordAILab. Our thesis was simple: AI progress would become increasingly data-centric – and therefore data development should be studied as a true research and technology problem, not just a staffing and crowdsourcing one. Today, as AI capabilities verge on superhuman, building the data and environments to safely measure and train AI is becoming too hard for even the smartest human experts to do alone. Only humans and AI agents, collaborating together in compounding ways, can meet the accelerating needs of the frontier, and keep humans in the driver’s seat of AI progress for decades to come. At @SnorkelAI, we are building the data lab to define the shape of this new “Data 2.0” frontier, and the new paradigms of human-computer interaction needed to advance it. Our key focus is building the RSI engine for data, where specialized AI models accelerate and improve human expert output, and in turn, scaled human supervision is used to continuously evaluate and improve these models – creating a powerful compounding loop to keep pace with an accelerating RSI frontier. With this round of funding, we are also doubling down on our commitments to support data development for open benchmarking and evaluation (more news here soon!); an increasingly diverse ecosystem of general and specialized intelligence; and a path to safe, well-aligned AI built on robust training and evaluation data. Data development will guide and drive the next stages of AI – and must do so in a human-centric, AI accelerated, open, diverse, and safe way. We are excited to support this mission in the next decade of research ahead at @SnorkelAI. More thoughts here: snorkel.ai/blog/data-2-0-and…

Congratulations to @howardting and the @opal_sec team on today’s launch of Opal Zero, an end-to-end access governance platform for AI agents AI agents are forcing companies to rethink the basic unit of enterprise access and the architecture built around it. Howard and I discussed why inventory alone won’t be enough, why human approval processes cannot keep up, and how Opal is approaching the problem. - Agents are becoming some of the most powerful and least governed identities in the enterprise. Few teams can say what a given agent has accessed, who owns it, or why it has that access. - Howard estimates that once permissions are scoped to each task, agents could generate millions of access decisions for every employee. - Today, teams face a bad tradeoff: give agents broad access so they can work, or lock them down until they’re useless. Neither approach works at agent scale. - Opal Zero is built to close the gap between inventory and governance. It finds agents and their credentials, ties each one to an owner and purpose, and gives them scoped access for each task. Full conversation in the comments.

You want your AI agents to run fast. But as you scale, managing their permissions turns into a million micro-decisions. Introducing Opal Zero. The end-to-end access governance platform purpose-built for AI agents. How it works: AI-driven contextual decisions, evaluating intent, ownership, and purpose Dynamic, just-in-time access (scoped to exactly what the agent needs). Enforces security decisions across your existing MCP gateways 0 standing permissions, 0 human toil, 0 friction Let your agents run, safely.

Thank you @GoldmanSachs for having us on the VC Panel! @glennsolomon @guruchahal @saranormous

The supervisor layer Watches the full trajectory over time. Catches dangerous patterns that individual actions can miss.

The inline layer Checks each action before it happens. Fast, cheap, and focused on clear violations.

Yesterday, in the wake of our Series A announcement, Antioch co-founder @HarryMellsop went on @tbpn to discuss how simulation accelerates physical AI development, and what the future of the industry holds. Take a watch!

Today we're announcing @lightfld's $47M Series A led by @a16z to reimagine CRM as a world model of a business. For agents to do customer-facing work, they need to understand how your business actually works. Salesforce wasn't designed for this. It was built 20+ years ago for humans to update records. Layer agentic processes on top and you get low quality output, because the underlying data is incomplete and lacks the structure agents need. @lightfld updates itself from every interaction, forming a trustworthy model of your business for people and agents. Since launching last November, 5,000+ companies have signed up - and we're ripping out legacy CRM at mature organizations with hundreds of users. Companies on Lightfield grow faster than their competitors. It finds prospects that look like your best customers and books meetings with them. It captures commitments from every conversation and automates follow-ups. It diagnoses weaknesses in your funnel and learns from your best sellers to codify what works. The companies of the future will run on a business world model, not a Salesforce-era database. Our mission is to put that capability in the hands of every employee, and every agent, at every company.

Beyond excited to share that @highstock_x has raised a $30M Series A led by @a16z with participation from @GreylockVC, @AbstractVC, @Daybreak_Fund, and angels. We are doubling down on our mission of creating value for brands with unproductive inventory. With this raise, we are expanding our team and building on our success in beauty to unlock a new category: apparel. @omooretweets, @venturetwins and @jeff_jordan are the right partners to take this company to new heights - they've invested in great marketplaces like Instacart (I may be biased :) ), and have studied how AI will scale marketplace models that were previously too labor intensive to be financially viable. Thank you to our angels: @Max, @lennysan, JJ Zhuang (Instacart) and John Adams (Instacart). Most of all, thank you to our customers and team. We would not be here without you. Read my reflections on our journey below.

Modern cybersecurity has an architectural problem. The organizations with the most to protect get the least protection. Their data cannot leave their control, and the industry’s best tools live in a cloud they cannot use. So they make do with less. Less data, less AI, less defense. We are rebuilding the entire cybersecurity stack to end that dilemma, starting the other way: your requirements, your premises, your data going nowhere. A complete cybersecurity platform that runs all cybersecurity functions, hardware included. Today, we raised another $245 million to keep building, with participation from @lightspeedvp, Picture Capital, and @Redpoint. Read the announcement: cylake.com/resources/cylake-…