Maxim Serebryakov

Generative AI’s greatest potential lies in the physical world, where the ability to simulate, design, and iterate faster can reshape trillion-dollar sectors. That’s why we’re thrilled to announce that N47 is leading Luminary Cloud’s $72M Series B. The Luminary team is pioneering the Physics AI Model Factory, underpinned by a GPU-native physics simulation platform. This technology is designed from the ground up to unleash the performance of modern GPUs and generate the high-value datasets that power next-generation AI. Now, engineers can run hundreds of design iterations overnight instead of waiting days. AI models trained on physics-grounded data can suggest new aerodynamic designs or optimize energy systems in ways previously impossible, and companies across industries can accelerate their innovation cycles while reducing cost. With co-founders Juan Alonso and Pete Schlampp, Luminary has the technical depth and operational experience to define the new era of Physics AI. We’re proud to partner with them as they create the future of simulation and redefine what’s possible in the built world. Learn more about Luminary Cloud’s vision here: https://lnkd.in/gbjeWrvy 

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Exciting to see startups aiming to use AI to discover chemicals, materials, drugs, etc. Semi companies have taken notice: AMD is investing in and Cadence is acquiring them. Semi/EDA companies have broken out by becoming critical path, whether it’s through critical software, packaging, IP, design kits from foundries, or user communities. Aside from just making it easy to make new materials, these “AI for making X” companies also need to articulate a vision as to how they can establish monopolistic positions in their industries.

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Remember how Midjourney and Sora blew your mind? Inception Labs brings that same "wow" factor to text and code with diffusion models. I'm proud to announce Mayfield led the investment  in Inception Labs last July, creators of Mercury - the first commercial-scale diffusion LLM that runs 10x faster and at 1/10th the cost of traditional LLMs. The founding team represents the perfect storm of talent: Stanford University professor Stefano Ermon who co-invented diffusion models, UCLA professor Aditya Grover, and Cornell University professor Volodymyr Kuleshov. After working together for over 10 years on AI research, they’ve embarked on the ambitious mission to rebuild the AI tech stack from the ground up fundamentally. Personally, partnering with Inception Labs feels like a homecoming. It brings me back to my Stanford days when my PhD research in video compression led to my first startup, VXtreme (acquired by Microsoft), the pioneer in video streaming. I’m witnessing the same pattern unfold again, but with significantly higher stakes. AI represents a once-in-a-lifetime opportunity to reshape how we work, live, and play. As I see it, Inception Labs' technology is an enabling layer that will propel #CollaborativeIntelligence to new heights. Their approach mirrors human thought processes more closely than traditional left-to-right text generation, resulting in faster, more accurate, real-time language generation with fewer hallucinations. This breakthrough has the potential to democratize AI. With lower costs and reduced computing requirements, Mercury can bring powerful language models to the edge, even to the palm of your hand. The possibilities are truly endless. Are you curious how this breakthrough happened? Watch my conversation with the Inception Labs cofounders, in which they share their journey from academic research to startup and their vision for revolutionizing AI with diffusion LLMs. What areas do you think will be most transformed by diffusion LLMs? #AI #DiffusionModels #Mayfield

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