Perceptron AI Launches Isaac 0.5, a Frontier Open-Weight Robotics Model

Skip to Content News Archives Economy Energy Oil & Gas Renewables Electric Vehicles Mining Commodities Agriculture Real Estate Mortgages Mortgage Rates Finance Banking Insurance Fintech Cryptocurrency Work Wealth Smart Money Wealth Management Investor Personal Finance Family Finance Retirement Taxes High Net Worth FP Comment Executive Women Puzzmo Newsletters Financial Times Business Essentials More Innovation Information Technology FP500 Podcasts Small Business Lives Told Tails Told Shopping Financial Post Store Obituaries Place a Notice Advertising Advertising With Us Advertising Solutions Postmedia Ad Manager Sponsorship Requests Classifieds Place a Classifieds ad Working Profile Settings My Subscriptions My Offers Newsletters Customer Service FAQ News Economy Energy Mining Real Estate Finance Work Wealth Investor FP Comment Executive Women Puzzmo Newsletters Financial Times Business Essentials This advertisement has not loaded yet, but your article continues below.HomeBusiness Wire News ReleasesPMN Press ReleasesThis section is The content in this section is supplied by Business Wire for the purposes of distributing press releases on behalf of its clients. Postmedia has not reviewed the content. by Business Wire Perceptron AI Launches Isaac 0.5, a Frontier Open-Weight Robotics ModelAuthor of the article:Perceptron’s Isaac 0.5 outperforms leading open robot models, including Physical Intelligence’s π0.5 and NVIDIA’s GR00T N1.7THIS CONTENT IS RESERVED FOR SUBSCRIBERS ONLYSubscribe now to read the latest news in your city and across Canada.Exclusive articles from Barbara Shecter, Joe O'Connor, Gabriel Friedman, and others.Daily content from Financial Times, the world's leading global business publication.Unlimited online access to read articles from Financial Post, National Post and 15 news sites across Canada with one account.National Post ePaper, an electronic replica of the print edition to view on any device, share and comment on.Daily puzzles, including the New York Times Crossword.SUBSCRIBE TO UNLOCK MORE ARTICLESSubscribe now to read the latest news in your city and across Canada.Exclusive articles from Barbara Shecter, Joe O'Connor, Gabriel Friedman and others.Daily content from Financial Times, the world's leading global business publication.Unlimited online access to read articles from Financial Post, National Post and 15 news sites across Canada with one account.National Post ePaper, an electronic replica of the print edition to view on any device, share and comment on.Daily puzzles, including the New York Times Crossword.REGISTER / SIGN IN TO UNLOCK MORE ARTICLESCreate an account or sign in to continue with your reading experience.Access articles from across Canada with one account.Share your thoughts and join the conversation in the comments.Enjoy additional articles per month.Get email updates from your favourite authors.THIS ARTICLE IS FREE TO READ REGISTER TO UNLOCK.Create an account or sign in to continue with your reading experience.Access articles from across Canada with one accountShare your thoughts and join the conversation in the commentsEnjoy additional articles per monthGet email updates from your favourite authorsSign In or Create an AccountBELLEVUE, Wash. — Perceptron AI has launched Isaac 0.5, a 36-billion-parameter open-weight embodied foundation model that combines video understanding, embodied reasoning and robot control, the first open model at the frontier of all three. Perceptron is working with customers to adapt the model for industrial systems.Isaac can read video, follow language instructions, locate and track objects, estimate the state of a task, and generate robot actions. Industrial automation and robotics teams can use it as the policy that controls a robot or use its visual outputs inside an existing planning and control system.Isaac was trained on three trillion multimodal tokens, one million hours of general video and 100,000 hours of robotics-oriented experience across more than 35 robot systems. Perceptron also established a new scaling law for the data behind robot models. In controlled training experiments, scaling general video from 1,000 hours to one million cut the teleoperation needed to reach the same, well-calibrated action loss from ~5,900 hours to 28.Get the latest headlines, breaking news and columns.By signing up you consent to receive the above newsletter from Postmedia Network Inc.A welcome email is on its way. If you don't see it, please check your junk folder.The next issue of Top Stories will soon be in your inbox.We encountered an issue signing you up. Please try again“Companies need a model that performs at the frontier, learns a new task quickly and adapts to their hardware. Isaac gives them a strong, open starting point, and our team is working alongside our customers to bring it into real operations,” said Armen Aghajanyan, co-founder and CEO of Perceptron AI.Frontier performance among open robot modelsIsaac is evaluated on the same kinds of capabilities required in deployed robotics: understanding a scene, following an instruction, adapting to a new task and completing an action sequence. Its results place it at the top of the open-model field across both robot control and embodied reasoning.On LIBERO, a standard benchmark for robot manipulation, Isaac averages 97.2% success across spatial, object, goal and long-horizon tasks. The paper reports 97.0% for NVIDIA GR00T N1.7 and 96.9% for π0.5 in the same comparison table.Isaac also learns new tasks faster. After one training pass over a single expert demonstration, it reduced error by 7.0x to 10.5x across three unseen tasks. The strongest competing open model, π0.5, improved by 2.3x to 3.1x. GR00T N1.7, MolmoAct2 and SmolVLA also trailed Isaac on every task in the study.From an open model to customer deploymentPerceptron works with customers across manufacturing, logistics, warehousing, security and mobility. The company works directly with teams to adapt Isaac to their cameras, robot hardware, demonstration data and operating workflows.Customers can begin with the open model, fine-tune it on their own demonstrations, and work with Perceptron on the final deployment. The same checkpoint can support video analysis, pointing and grounding, task-progress monitoring, and continuous or discrete robot control.“A real robot workflow rarely begins and ends with one motion. The system has to understand what it sees, decide what matters and connect that decision to action. Isaac was built to carry that workflow from video and language through to control,” said Akshat Shrivastava, co-founder and CTO of Perceptron AI.A new data recipe for robot learningRobot demonstrations are expensive because each hour requires hardware, operators and a controlled setup. General video is far easier to collect. While training Isaac 0.5, Perceptron proved a new scaling law for robot learning: video-heavy training mixtures can reduce the teleoperation data requirement by ~210x. This scaling law gives robotics teams a practical way to plan where the next unit of training data should come from.Open and available to build onPerceptron released both the model and tools needed to evaluate and adapt Isaac for field deployments:Perceptron provides direct support for companies adapting Isaac to commercial deployments.is an AI research lab pushing the frontier of physical AI, building systems that perceive, reason, and act in the real world, reliably and at scale. Headquartered in Bellevue, Washington, Perceptron was founded in November 2024 by Armen Aghajanyan and Akshat Shrivastava, both former research scientists at Facebook AI Research (FAIR).View source version on businesswire.com: This advertisement has not loaded yet.Notice for the Postmedia NetworkThis website uses cookies to personalize your content (including ads), and allows us to analyze our traffic. Read more about cookies here. By continuing to use our site, you agree to our Terms of Use and Privacy Policy.