Lu Zhang

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 

119

6 Comments

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.

144

5 Comments

Forward-deployed engineers (FDEs) have become one of the most in-demand roles for AI companies. Everyone's racing to adopt the latest AI models and applications, but here's what we're seeing: the biggest differentiator for AI companies isn't what model(s) they're using, it's how well they're implementing them to solve their clients' actual use cases. SaaS was about digitizing business processes. This new era of software is about using agentic AI to rethink and automate them. Because AI applications are systems of action (shoutout to Unify for coining this), they often need FDEs to translate a customer's messy business reality, not just their documented SOPs, into applications that perform reliably in production. If AI models are the gold, then forward-deployed engineers are the miners. Our partner Gordon Ritter and I wrote more about why FDEs are becoming one of the most strategic roles in enterprise AI and what second-order startup opportunities this creates. Would love to hear more thoughts on how you're seeing this trend play out! https://lnkd.in/g-gaBZeb

111

6 Comments

The largest M&A in the history of #Quantum Computing?? There are many ways to build a quantum computer but the industry is mostly organizing itself around a few major approaches. For years, it seemed like Superconducting Qubits enjoyed most of the funding (and most of the drama), with vendors like IBM, Google and Rigetti Computing dropping announcements left and right. Yesterday marks a major paradigm shift - IonQ announced its pending acquisition of Oxford Ionics for a staggering amount of $1Bn. This is the second major consolidation event within the trapped ion modality, following on the 2021 merger of Honeywell Quantum Solutions and Cambridge Quantum into Quantinuum. Among global giants, Israel's Quantum Art also stands as a major player in this field (led by Tal David, Roee Ozeri, Amit Ben Kish & Elkana Ben-Sinai). How will the industry evolve from here?

46

2 Comments

I’ve been working on the theory of why small, shippable factories are the perfect inversion to the centralized prefab factory model. It all collapsed into one line of math (credit to Gilles Retsin): Factory Efficiency = Usage × (Throughput × Product Value ) / ( CapEx + Deployment OpEx) The idea is that the closer you can drive Usage to 100 % while keeping the denominator tiny, the faster the flywheel spins.  A shippable microfactory tackles this by primarily focusing on a high Usage factor. Because the microfactory can be packed up afterwards and reused, its CapEx gets amortized over multiple projects, effectively raising its overall Usage across the year. If one project alone doesn’t fully occupy the factory, it can simply roll over to another job to maintain high Usage. Its CapEx is often an order of magnitude lower than a centralized factory (< $1M vs. $10-50M min), so the breakeven throughput is more achievable on a small pipeline of work. The real breakthrough here is portability. There is near-zero stranded capital and almost no idle time. To flesh this theory out, I wrote 3000 words on the topic for Brad Hargreaves and Thesis Driven. The article breaks down: - why “fixed factories, shipped goods” is being inverted to shipped factories, fixed goods - what a sub‑$1 M robotic cell does to CapEx per home versus a £45 M off‑site plant - early production/cost data on a shippable microfactory from Mollie Claypool, Gilles Retsin, Sam Baker and the Automated Architecture (AUAR) team - the hybrid reality of robots tackling the heavy structural components and human crews assembling faster and cheaper - technical constraints to pull this model off and future considerations on the optimal business model (own vs. rent) Major shoutout to Gilles Retsin for helping me pull this together. https://lnkd.in/eRTnbZPa

54

2 Comments

We’ve hit an inflection point in AI, and everything is about to change. Meet DeepSeek, a Chinese artificial intelligence research lab founded in May 2023 by Liang Wenfeng, as part of the High-Flyer hedge fund. If you’ve studied Clayton Christensen’s theory of disruptive innovation, you’ll know that the disruptor doesn’t always come from the biggest players. In fact, it often comes from the smallest — challenging the giants with smarter, more affordable solutions. That’s exactly what DeepSeek AI is doing right now in the world of artificial intelligence. 🔍 How? DeepSeek is pushing the boundaries of what's possible in AI with its cutting-edge algorithms and data analytics capabilities. By unlocking hidden insights from complex datasets, DeepSeek enables businesses to make smarter, faster decisions — revolutionising industries from finance to healthcare. 💡 The Disruption: While many AI solutions focus on surface-level data, DeepSeek dives deeper, offering predictive insights and actionable intelligence. This ability to extract value from large, noisy datasets is what sets it apart from traditional AI tools. ⚡ So, What’s Next? As the market evolves, companies like DeepSeek will shape the future of AI-driven automation. If you're in venture capital or innovation, now is the time to watch these disruptive players who are redefining how businesses operate and grow. 🌟 For those of you who want to stay ahead of the curve, exploring partnerships with these emerging technologies could be your next big move. 🌟 And for venture capitalists, specifically: - DeepSeek V3 (671 billion parameters) was built for just $5.58 million, compared to the tens of millions typically required by industry leaders. - Using just 2,000 specialized Nvidia chips, DeepSeek achieves performance that others need 16,000+ chips for. Their API is cost-effective, charging only $0.14 per million tokens—starkly contrasting alternatives like OpenAI. This is exactly why venture capital exists — to back the innovators who are changing the game. Small companies like DeepSeek AI have the potential to reshape industries and create opportunities where there were none before. Is DeepSeek the next big thing in AI? Only time will tell. But the industry's future may not lie with the giants — it could be with the disruptors. After all, we may not need half a trillion to participate in the AI revolution. AI Series A, here we come!

21

1 Comment

AI isn't just powering software. BrightAI just raised $51 million to automate inspection and other hardware-based AI capabilities. As Alexa von Tobel, co-founder of Inspired Capital put it: “So many people are so focused on the future of digital AI, but we’re excited about this new layer of AI: the physical world AI.” We are in the early innings of a series of AI-fueled innovations! https://lnkd.in/enhmafvH

47