
He was studying how AI fails before most people believed it worked. Now he builds the guardrails that keep everyone else's models honest.
Cactus is a cross-platform, open-source AI inference engine built in C/C++ to run language, speech, and vision models directly on smartphones, laptops, wearables, and other low-power edge hardware. It gives mobile developers Flutter, React Native, Kotlin, and Swift SDKs to deploy quantized models on-device - cutting latency to under 100ms, keeping data private, working offline, and avoiding cloud API bills - with automatic cloud fallback for heavier tasks. A YC Summer 2025 company, Cactus already powers production apps serving 500,000+ weekly inference tasks.
Dillon Rolnick is the chief executive of Nous Research, an applied AI lab building open-source, human-centric language models and the decentralized Psyche training network. A Vanderbilt graduate who came up through quantitative FX trading at Effex Capital and founded the litigation-claims firm Crysknife Capital, he moved from finance into AI research leadership, helping steer Nous through a Paradigm-led $50M Series A and, by 2026, a reported $75M round near a $1.5B valuation. His focus is proving that world-class models can be trained openly and over the internet rather than behind the walls of a few large labs.
Nomic AI is a New York-based artificial intelligence company building tools to make large, unstructured datasets and AI models understandable and usable by everyone. It is best known for Atlas, a browser-based platform for visualizing and interacting with massive datasets; the open-source Nomic Embed family of text, code, and multimodal embedding models; and GPT4All, an ecosystem for running large language models privately on everyday hardware. Since 2025 the company has focused its platform on the architecture, engineering, and construction (AEC) sector, applying its embedding and retrieval technology to drawing review, code compliance, and document-heavy construction workflows.
Nous Research is an open-source AI lab founded in 2023 that builds world-class open-weight language models - most notably its Hermes family - and decentralized infrastructure for training them. Its Psyche network coordinates heterogeneous GPUs across the internet via the Solana blockchain, offering a community-driven, transparent alternative to closed labs like OpenAI. Backed by Paradigm and others, the company positions open, unrestricted models as a counterweight to centralized AI.
In episode 280 of the All-In Podcast, hosts Jason Calacanis, Chamath Palihapitiya and David Sacks are joined by 'bestie' Brad Gerstner (David Friedberg is on vacation) to unpack a trillion-dollar rush to the IPO exits led by SpaceX and expected to be followed by Anthropic and OpenAI. The group debates the sustainability of exploding AI token spend, the tug-of-war between frontier labs and cheap open-source models, sovereign AI ambitions, and whether enterprises can actually prove ROI. The emotional centerpiece is the launch of 'Trump Accounts' (the Invest America Act), a $1,000-at-birth investment account for every American child that Gerstner championed for four years, now live as the number-one app in the App Store, with billionaire philanthropists like Michael Dell and Gwynne Shotwell seeding accounts for lower-income kids.
Arcee AI is a San Francisco-based open intelligence lab that builds small, efficient, US-made language models enterprises can own, customize and run inside their own infrastructure. Founded in 2023 by former Hugging Face and Roboflow operators, the company pioneered practical techniques like model merging (via its acquisition of mergekit) and Spectrum training, and has expanded from small language models into its own open-weight Arcee Foundation Model family, the Trinity mixture-of-experts models, and agentic products such as Arcee Conductor and Arcee Orchestra. Its pitch: smaller, domain-adapted models that rival frontier systems at a fraction of the cost while keeping data private.
Featherless AI is a serverless inference platform that gives developers and enterprises a single API key to run more than 40,000 open-weight AI models across language, vision, audio and multimodal tasks - without provisioning or managing any GPUs. Founded in 2023 by the team behind the RWKV open-source model architecture, the company sells flat-rate subscriptions with unlimited tokens and positions itself as a neutral infrastructure layer for open-source AI, independent of the major cloud hyperscalers. It raised a $20M Series A in April 2026 co-led by AMD Ventures and Airbus Ventures, bringing total funding to about $25M.
Simular is a Palo Alto-based AI company building autonomous computer-use agents that operate desktops, browsers, and phones the way a person does - clicking, typing, and navigating graphical interfaces. Its open-source Agent S framework and its always-on assistant Sai use a neuro-symbolic approach that turns exploratory agent runs into deterministic, auditable code to reduce hallucinations. Founded in 2023 by former Google DeepMind researchers Ang Li and Jiachen Yang, Simular has raised about $26.5M and posts state-of-the-art results on computer-use benchmarks.
Cake is a New York-based startup that bundles the sprawling open-source AI stack into a single managed platform, so companies - especially in regulated industries like finance, insurance and healthcare - can deploy AI inside their own cloud without wiring together 100+ tools by hand. Founded in 2022 by Misha Herscu and Skyler Thomas and launched from stealth in December 2024 with a $13M seed led by Google's Gradient Ventures, Cake handles the integration, security, governance and cost-monitoring glue around open-source components like LangChain, Ray, MLflow and vector databases, all deployed inside a customer's own VPC so data never leaves.
Deep Cogito is a San Francisco AI research company building open-source large language models with hybrid reasoning - the same model can answer instantly or stop to reason before responding. Founded in 2024 by former Google engineer Drishan Arora, the company trains its Cogito models with a method called Iterated Distillation and Amplification (IDA), which lets a model improve by learning from its own reasoning rather than from human labels. Its stated goal is general superintelligence, and its flagship 671B open model competes with the strongest open systems from DeepSeek and Meta.
Oumi (Open Universal Machine Intelligence) is a Kirkland/Bellevue, Washington-based public benefit corporation building a fully open-source, end-to-end platform for foundation models. Founded in 2024 by ex-Google, Apple, Meta and Microsoft engineers, its open software stack lets researchers and enterprises prepare data, pretrain, fine-tune, evaluate and deploy LLMs and vision-language models - from 10M to 405B parameters - anywhere from a laptop to a cloud cluster. Backed by $10M in seed funding and a coalition of 13 top research universities, Oumi pitches itself as the 'Linux of AI': a neutral, collaborative, unconditionally open alternative to closed frontier labs.
Pokee AI is a Bellevue-based startup building foundation AI agents that plan, reason, and act across thousands of internet tools. Founded in 2024 by former Meta applied-reinforcement-learning lead Zheqing (Bill) Zhu, the company uses reinforcement learning rather than pure LLM function-calling to sequence tool use reliably, claiming its foundation model outperforms GPT-4o, Claude 3.7, and Gemini 2.5 Pro on tool selection. Pokee raised a $12M seed round in 2025 led by Point72 Ventures, ships an enterprise platform with private/on-prem deployment, and open-sourced PokeeResearch-7B, a state-of-the-art small deep-research agent.
Voio is a Berkeley-based frontier AI lab building a unified reading platform for radiology. Spun out of UC Berkeley and UCSF, it develops the open-source Pillar family of models that interpret CT, MRI and X-ray scans across hundreds of conditions, aiming to help radiologists work faster without trading away accuracy. The company exited stealth in November 2025 with $8.6M in seed funding.
Aitomatic builds autonomous AI agents that capture and operationalize the hard-won knowledge of veteran industrial experts - the kind of know-how that quietly walks out the door when senior engineers retire. Founded in 2021 by ex-Google and ex-Panasonic veterans, the Palo Alto company has open-sourced OpenSSA (Small Specialist Agents) as an inaugural member of the AI Alliance with IBM and Meta, and released SemiKong, the world's first open-source LLM purpose-built for the semiconductor industry.
Kintsugi is a Berkeley-based AI company that built voice biomarker technology able to flag signs of clinical depression and anxiety from roughly 20 seconds of free-form speech. Founded in 2019 by Grace Chang and Rima Seiilova-Olson, it sold an API-first platform into call centers, telehealth, and remote patient monitoring before winding down operations in early 2026 and releasing its models, methods, and research into the public domain.
Charles Packer is the co-founder and CEO of Letta, the San Francisco startup building the memory layer for AI agents. He is the original author of MemGPT, the viral research project that reframed large language models as operating systems that manage their own memory. A UC Berkeley computer science PhD out of the BAIR and Sky Computing labs, Packer walked away from offers at OpenAI and Google DeepMind to build stateful agents that remember, learn, and improve after deployment - the layer he argues sits above the base models and separates a real agent from a chatbot with a nice interface.
Drishan Arora is the co-founder and CEO of Deep Cogito, a San Francisco AI lab building toward general superintelligence through openly released reasoning models. A former senior engineer at Google who led large language model work for its generative search, Arora left to chase a contrarian bet: that intelligence improves not by searching harder but by building better intuition. His team trained the Cogito family of hybrid reasoning models - which can answer instantly or stop to think - in roughly 75 days, then scaled to a 671-billion-parameter model his company calls the strongest open-weight LLM from a US firm. The method underneath it all, iterated distillation and amplification, lets the models internalize their own reasoning paths and self-improve.
Emmanouil 'Manos' Koukoumidis is the CEO and co-founder of Oumi (Open Universal Machine Intelligence), a Seattle-area public benefit corporation building what he calls AI's 'Linux moment' - an unconditionally open platform where data, code, model weights and training recipes are all transparent and reproducible. A Princeton PhD who scaled Google Cloud's PaLM with a 300-person virtual team before it became Gemini, and who earlier built emotionally intelligent chatbots at Microsoft, Manos left big tech to give researchers and the wider world the truly open AI he believes they deserve. Oumi raised a $10M seed in early 2025 and launched its commercial custom-model platform in 2026.

Misha Laskin is the co-founder and CEO of Reflection AI, a New York lab building open-weight frontier models and autonomous coding agents. A theoretical physicist by training (Yale, University of Chicago), he led reward modeling for Google DeepMind's Gemini and worked in reinforcement learning at Berkeley and DeepMind before launching Reflection in 2024 with AlphaGo co-creator Ioannis Antonoglou. In 2025 the company raised roughly $2 billion at an $8 billion valuation, positioning itself as America's open-source answer to DeepSeek.
Misha Herscu is the co-founder and CEO of Cake, a New York based platform that bundles more than 100 open-source AI components into managed, production-ready infrastructure so mid-market teams get the control of a build with the ease of a buy. A Harvard physics graduate turned full-stack engineer, he previously founded the radiology AI marketplace EnvoyAI (McCoy Medical Technologies), which TeraRecon acquired in 2018. After running over 200 customer-discovery calls as an operator in residence at Primary Venture Partners, he started Cake in 2022 with CTO Skyler Thomas and raised a $13M seed round led by Google's Gradient in late 2024.
Ying Sheng is the co-founder and CEO of RadixArk, an AI infrastructure company that spun out of SGLang, the open-source inference engine she helped create in 2023. SGLang now runs across hundreds of thousands of GPUs and serves trillions of tokens a day for Google, Microsoft, NVIDIA, xAI and others. A Stanford computer science PhD and former xAI technical staff who co-led the inference team behind Grok, she launched RadixArk in May 2026 with $100 million in seed funding led by Accel at a $400 million valuation, on a mission to make frontier-level AI infrastructure open and accessible to everyone.
Reflection AI is a New York-based artificial intelligence lab founded in 2024 by former Google DeepMind researchers Misha Laskin and Ioannis Antonoglou. It is building autonomous coding agents and open frontier language models, with the stated ambition of reaching superintelligence by first solving software engineering. Its flagship product, Asimov, is a code research and comprehension agent for large codebases. After raising $2 billion at an $8 billion valuation in October 2025, the company has positioned itself as an open, Western alternative to closed labs like OpenAI and Anthropic and to Chinese open-weight models like DeepSeek.
Zyphra is a superintelligence research and product company building efficient, open foundation models and a full-stack AI cloud. Best known for its SSM-hybrid Zamba models, the ZAYA1 reasoning family trained entirely on AMD hardware, and the Zonos text-to-speech system, Zyphra argues that frontier intelligence should run cheaply, locally, and outside the walled gardens of a handful of labs. In June 2025 it raised a $100M Series A at a $1B valuation led by Jaan Tallinn.
Meta Platforms is the company behind Facebook, Instagram, WhatsApp, Messenger, and Threads - a Family of Apps used by more than 3 billion people daily. Founded as Facebook in 2004 and renamed Meta in 2021, it runs one of the world's largest digital advertising businesses while pouring tens of billions into artificial intelligence (the open-weight Llama models and Meta AI assistant) and wearable computing (Quest headsets and Ray-Ban Meta smart glasses). In 2025 it reported roughly $201 billion in revenue.
H2O.ai is a Mountain View-based AI cloud company founded in 2012, on a mission to democratize artificial intelligence for everyone. The company offers a converged platform spanning predictive and generative AI - from its open-source H2O-3 machine learning framework to enterprise products like Driverless AI, h2oGPTe, and the H2O AI Cloud. Trusted by over 20,000 organizations including more than half the Fortune 500, H2O.ai is known for employing the world's largest team of Kaggle Grandmasters and for pioneering automated machine learning. With $246 million in total funding at a $1.7 billion valuation, the company serves industries from financial services and healthcare to government and telecommunications, delivering AI that organizations can deploy on their own terms - on-premises, in the cloud, or in air-gapped environments.
Mukunda Srinivasagowda is a seasoned technologist and Co-Founder of SuperAGI, a Palo Alto-based AI company building a full-stack agentic intelligence platform. With over 13 years spanning Amazon, Zomato, and fintech unicorn Navi, he co-built SuperAGI from the ground up in 2023 alongside CEO Ishaan Bhola. The company's open-source autonomous agent framework earned 17,500+ GitHub stars, attracted a $10 million Series A led by Jan Koum's secretive Newlands VC, and spawned a suite of AI-native products including SuperSales, SuperMarketing, and SuperCoder - all targeting the shift from LLMs that generate content to agents that actually take action.
Together AI is a San Francisco-based AI acceleration cloud that lets developers and enterprises train, fine-tune, and run open-source generative AI models on a high-performance GPU platform. Backed by $533M+ from General Catalyst, NVIDIA, Salesforce Ventures and others, it has become one of the most prominent challengers to the closed-model status quo.

Dean Ball is a leading AI policy scholar, writer, and former White House advisor who shaped America's AI strategy from the inside. As Senior Fellow at the Foundation for American Innovation, co-host of the AI Summer podcast, and author of the widely-read Hyperdimensional newsletter, he makes the case for market-driven, light-touch governance of frontier AI - arguing that private governance mechanisms, not government mandates, are the right framework for the most transformative technology of our time.