Everybody, welcome. Great to see all of you. I have a special treat for you.We have two sessions. We have so many great speakers for you. We broke it up into two sessions.Let's get right to it. I think we love a world where there's proprietary products, but we also we also need a world where, a whole bunch of companies and different industries in different domains need models as a technology, that we could then transform into products. So today, really what I wanted to celebrate is not the proprietary versu ...

Core Insights - Rowspace is an AI platform designed to help financial institutions like private equity firms and hedge funds leverage their proprietary data for better decision-making and capital allocation [3]. Funding and Launch - Rowspace is publicly launching with $50 million in funding, which includes a seed round led by Sequoia and a Series A co-led by Sequoia and Emergence Capital, with additional participation from Basis Set Ventures, Stripe, and Conviction [3]. Market Context - The launch of Rowspace comes amid concerns about the impact of large language models on software, with industry experts suggesting that applications like Rowspace will thrive in an AI-driven environment [4]. Product Differentiation - Rowspace is described as an intelligence layer that integrates both structured and unstructured data from financial institutions, focusing on enhancing decision-making processes [5]. - Unlike consumer tools that take possession of data, Rowspace processes data within the customers' own cloud systems, ensuring data security and integrity [6].

Do you have a theory as to how continual the continual learning problem can be solved and do you want to share it with us all. >> I can give you some clues. We are working very hard on it.Um we've done some work on you know I think the best work on this in the past with things like Alpha Zero you know that learned from scratch um versions of Alph Go Alph Go Zero also learned on top of the the knowledge it already had. So we've done it in much narrower domains. You know games are obviously a lot easier than ...

#NVIDIAHealthcare #biopharma #aiforscience Joined by a panel of luminaries from Arc Institute/UC Berkeley, Chai Discovery, EvolutionaryScale, and Flagship Pioneering to dig into the intricacies of handling biological data and scaling foundation models, to ultimately understand their current and future impact on our understanding of human health, the discovery of novel therapeutics, and the scientific process itself. Follow us: X: https://nvda.ws/4hi2sxB LinkedIn: https://nvda.ws/4eSlE3B Subscribe to the NVI ...

I know you're very focused on driving scientific progress, just discovering new materials. Even we've seen now Gemini being integrated into humanoid robots is the alpha fold moment for the physical world. And I here.What is that and what does that look like. Yeah, I spent a lot of the last year actually looking very carefully into robotics. I do think we're on the cusp of a kind of breakthrough moment in physical intelligence.I still think we're about 18 months, two years away from doing. We need to do more ...

Just like the fact that this whole thing works, it's kind of mind-blowing. >> Yeah. >> Right.Like you you build this like loosely brain inspired thing that has very general purpose learning algorithm. You feed it data and it somehow gets it and gets it way better than anything we've ever had before. And this applies to robots and it applies to vision and language and sound and all kinds of other things.And like I think if you stop for a second and just think about it how it works and and that it works, it's ...

Core Insights - RLWRLD, a Physical AI startup, won first place in the Foundation Models, Robot Brains and Runtime category at the 2025 Nebius Robotics & Physical AI Awards, highlighting its advancements in next-generation robotics and Physical AI [2][3][5] Group 1: Awards and Recognition - The Nebius Robotics & Physical AI Awards, hosted by Nebius and supported by NVIDIA, awarded $1.5 million in AI cloud compute and inference credits to startups from over 250 applicants across 60+ countries [3][5] - RLWRLD received $150,000 in Nebius AI Cloud compute and inference credits as the first-place winner, emphasizing its innovative contributions to the field [5] Group 2: Company Focus and Technology - RLWRLD specializes in developing robot foundation models for high-difficulty manipulation and reliable industrial deployment, focusing on practical applications rather than general-purpose robotics [6][8] - The company's core platform, RLDX, is a proprietary robotics foundation model that controls a 15-degree-of-freedom robotic hand, enabling tasks that require human-level dexterity [6] Group 3: Commercial Readiness and Partnerships - Judges recognized RLWRLD's use of high-fidelity, multimodal industrial data and its collaboration with industry partners as indicators of commercial readiness, particularly in manufacturing and logistics [7] - Following the award, RLWRLD plans to expand global partnerships and accelerate the commercial deployment of its foundation models, focusing on manufacturing and logistics environments in the U.S. and Asia [8] Group 4: Company Background - Founded in 2024, RLWRLD develops robot foundation models that enable machines to operate with human-like dexterity and cognition, utilizing high-precision 4D+ multimodal industrial data [9] - The company operates in the United States, South Korea, and Japan, and is working with major manufacturing partners to establish itself as a global leader in industrial robotics AI [9]

Core Insights - Apple has appointed an outsider to lead its machine-learning research and foundation models efforts [1] Company Developments - The new leader will focus on enhancing Apple's capabilities in machine learning [1] - This move indicates Apple's commitment to advancing its technology in artificial intelligence [1] Industry Implications - The appointment reflects a broader trend in the tech industry where companies are increasingly investing in AI and machine learning [1] - This strategic shift may position Apple to better compete with other tech giants in the AI space [1]

L4 is really the pinnacle of vehicle autonomy. L4 autonomy refers to a self-driving system that can handle all driving tasks within a limited geographical area within specific operating conditions without any human intervention. Immediata's approach to L4 autonomy builds on the concept of foundation models.most specifically builds upon Cosmos, which is Nvidia's family of foundation models that have been developed specifically for physical AI applications such as autonomous vehicles. The beauty of co-develop ...

My name is Marco Pavon and I lead autonomous vehicle research at Nvidia. I'm also a professor at Stanford where I lead the autonomous systems lab. I was used to tell my students maybe 3 four years ago that as a researcher I felt a bit stuck.Of course we were making progress but that was very incremental. But in the past three years, there's been a massive influx of new technologies primarily from the field of artificial intelligence that have revolutionized essentially all the building blocks through which ...