Optical Computing Tools

I wanted to share something that has deeply impressed me: a breakthrough from Microsoft Research that I believe signals where computing is heading. Last week, our team unveiled the Analog Optical Computer (AOC), a system that uses light to tackle two of computing's biggest challenges simultaneously: AI inference – how AI makes predictions, from Copilot's suggestions to medical image analysis, and complex optimization – finding the best solution among millions of possibilities. The remarkable thing is: The AOC handles both using light, achieving potential 100x improvements in speed and energy efficiency, built with commercially available components like smartphone camera sensors and micro-LEDs. The potential for real-world impact is already tangible: We've demonstrated reconstructing MRI images (theoretically reducing scan times from 30 to 5 minutes). Our projected performance reaches 500 TOPS per watt at 8-bit precision – compared to current GPUs at around 4.5 TOPS per watt. This breakthrough comes at a pivotal moment. As AI transforms every industry, we have the opportunity to make computing radically more sustainable with innovations that can decouple growth from resource consumption. This underscores the importance of Microsoft Research's approach: tackling the hardest problems with practical, scalable solutions. For those interested in diving deeper into the technical details, the full research was published in Nature last week. This is the kind of innovation that gives me optimism about our digital future – not just making things faster, but reimagining how we compute. Read more on our blog, in Nature, and on Microsoft Research. https://lnkd.in/ejcy6wtp https://lnkd.in/eCcUkhpe https://lnkd.in/eXqSCiNJ Francesca Parmigiani Hitesh Ballani Jannes Gladrow Kirill Kalinin

A few weeks ago at OFC in Los Angeles, I had a conversation with Xianxin Guo of Lumai that I shared shortly after, and have been thinking about ever since. He couldn’t say much at the time, but mentioned Lumai would be breaking news that impacts the future of AI infrastructure. It was the type of cliff-hanger that makes you know something big is near and it wasn’t just what he said, but the smile, confidence, and conviction he said it with. Today, Lumai unveiled their full optical computing product line, which has achieved world-firsts across many AI performance metrics! In of itself, this is a major milestone. But as Xianxin had hinted, the announcement signals something much larger than a product roadmap. It’s a shift in the direction compute is heading. AI is hitting structural limits across the entire stack. Interconnect bottlenecks. Power-hungry processors. Every inefficiency is throttling the potential of inference workloads, and the industry is desperate for solutions. Lumai’s team recognized this wall coming years ago and focused on building an optical compute device that would leapfrog other technologies in terms of compute performance and energy efficiency. Xianxin told me last week, “Our first generation of products, Nova and Iris, can achieve a peak compute speed above 100 TOPS and is fully integrated into a rack-scale system. We can run a billion-parameter LLM for inference, in optics, in real time. This is the first time for any optical or novel computing system to achieve anything like this.” It’s highly impressive to hear these results from an optical system, especially since optical computing has been worked on for decades and Lumai isn’t the first startup to try it. And they didn’t stop at the component level. CTO James Spall's perspective on the announcement made that point resonate: “Now is the right time for optical computing because of the overlap of three things: The maturity of optical components from adjacent industries, the market dynamics, and us reaching a point where we can build systems using existing, manufacturable components rather than relying on experimental or non-scalable approaches.” That combination makes Lumai’s news all the more exciting. Many deep tech efforts start at the device. Lumai made system-level thinking a part of their strategy from the beginning. Now, they have validated technology, system-level deployability, and the tailwind of market timing. A winning combination. All of that said, perhaps the BIGGEST insight about Lumai that will highlight this team’s future potential is that they achieved all of this in a few year’s time and with capital efficiency that is extremely rare for a hardtech startup. If Xianxin and James can keep scaling with efficiency as a core operating principle, they will be the ones that truly democratize AI for humanity. Kudos to Xianxin, James and the entire Lumai team. This team is absolutely one to watch! #artificialintelligence #photonics #startups

Single-Photon Switching Breakthrough Signals a New Era for Photonic Computing Introduction For decades, engineers have chased the ability to control light using light itself. Traditional optical systems require enormous power, preventing single-photon control and blocking the path to true photonic computing. Purdue University researchers have now cracked the problem by demonstrating a transistor-like optical switch that operates using only a single photon—a milestone that could propel both quantum and classical computing into an ultra-fast, ultra-efficient future. Key Developments A Photonic Transistor at Single-Photon Intensity • Researchers created an optical switch where a single photon can modulate a much stronger optical beam. • Achieved using a nonlinear refractive index far beyond any previously known material. • Published in Nature Nanotechnology, the result solves a decades-long barrier in photon-photon interaction. Avalanche Multiplication as the Enabler • Instead of exotic quantum cavities, the team repurposed commercial single-photon avalanche diodes. • A single photon triggers an electron avalanche, amplifying quantum-scale events into macroscopic effects. • This amplification allows single photons to influence powerful optical beams with precision. Three Competitive Advantages • Works at room temperature, unlike fragile cryogenic quantum systems. • Fully compatible with semiconductor manufacturing for chip-level integration. • Supports gigahertz speeds today, with a pathway toward hundreds of gigahertz and eventual terahertz-class performance. Transformational Applications • Quantum: Faster quantum teleportation, improved single-photon sources, and more efficient quantum networks. • Classical: Creates the switching backbone needed for true photonic CPUs, enabling dramatic gains in speed and energy efficiency. • Broader impact: Potential shifts in data centers, communications, and high-performance computing. A Long Scientific Journey • After four years of iterative experimentation, the team demonstrated the first working device. • Next steps include designing custom SPADs and optimizing geometries for industrial-grade performance. • Researchers describe this as a new foundational platform for advancing light-based technologies. Why It Matters This breakthrough removes one of the final roadblocks to practical photonic computing. By enabling photon-level switching at room temperature, Purdue’s approach bridges quantum mechanics and real-world engineering. It positions light—not electricity—as the future engine of high-speed computing, with profound implications for national security, AI acceleration, and global technological competitiveness. I share daily insights with 33,000+ followers across defense, tech, and policy. If this topic resonates, I invite you to connect and continue the conversation. Keith King https://lnkd.in/gHPvUttw

🔮 Light at the Speed of Thought: A Breakthrough in Optical Computing 🌟 Overview Researchers have discovered luminescent nanocrystals that can rapidly switch between light and dark, promising a revolution in optical computing. This innovation, by scientists from Oregon State University and global collaborators, could enable data to be processed and stored using light—delivering unprecedented speed and energy efficiency. Published in Nature Photonics, this study represents a leap toward sustainable artificial intelligence. 🤓 Geek Mode At the core of this breakthrough are avalanching nanoparticles, tiny crystals that amplify light emission dramatically with minimal laser intensity changes. Made of potassium, chlorine, and lead, and doped with neodymium, these nanocrystals exhibit a rare property: intrinsic optical bistability. Think of them as a switch: once turned on with higher laser power, the nanocrystals stay on with less power, behaving like a “light memory.” This behavior is not only energy-efficient but also instantaneous, making these materials ideal for photonic applications like telecommunications, quantum computing, and medical imaging. 💼 Opportunity for VCs The commercial potential is staggering. These nanocrystals could disrupt industries by enabling: • Faster AI hardware that transcends current silicon limitations. • Energy-efficient data centers, reducing the carbon footprint of our digital age. • Advanced optical devices for sensing, imaging, and secure communication on the edge. The scalability of this technology offers fertile ground for startups to pioneer applications in photonic processors, quantum interconnects, and smart sensing solutions. Investors who back these ventures now could shape the optical computing ecosystem of the future. 🌍 Humanity-Level Impact This innovation brings sustainability in computation. By reducing energy demands for AI and data processing, it aligns with the global push for green technologies. On the separate hand, the applications in healthcare, environmental monitoring, and secure communications promise widespread societal benefits, from better diagnostics to more secure data transmission. ✨ A Closing Thought We’re witnessing the dawn of a new computing era, one illuminated by light itself. These luminescent nanocrystals are a beacon of how science and ingenuity can shape the future. 📄 Original Study in Nature Photonics: https://lnkd.in/gCiVA4BH #Photonics #DeepTech #AI #Sustainability #Innovation

#TSMC’s #COUPE Platform: A Closer Look at the Future of #SiliconPhotonics #TSMC is accelerating the optical-compute revolution with its #siliconphotonics platform “#COUPE,” built on the company’s advanced #SoIC #3D #packaging #technology. Recent reports from TechNews, Commercial Times, and MoneyDJ highlight how #COUPE strengthens #TSMC’s leadership in high-performance computing and next-gen optical solutions. #COUPE: Technology Breakdown 1. #COUPE connects electronic integrated circuits (#EIC) directly to photonic integrated circuits (#PIC) on wafer using copper-to-copper and hybrid bonding. 2. The #PIC integrates key optical components, including a 200G micro-ring modulator (#MRM). 3. After bonding, an oxide layer is added, and #dielectric #vias are drilled from the back to establish #electrical #connectivity. #Modulator Technologies 1. Micro-Ring Modulators (#MRM): Compact, high-density, ideal for energy-efficient, high-bandwidth #CPO applications. 2. Mach-Zehnder Modulators (#MZM): Preferred for high-power, high-speed optical performance. #TSMC is strategically investing in both, strengthening its versatility in #PIC design. #HPC Platform Integration According to #TechNews, #TSMC’s broader #HPC platform brings together: • Advanced logic • High-Bandwidth Memory (#HBM) • Passive components (inductors/capacitors) • State-of-the-art #3D# packaging + #siliconphotonics The #opticalengine can be deployed on #substrates or #interposers, depending on #system needs. What’s Next? #TSMC is now targeting: • Higher bandwidth • Faster optical-electrical performance • Better energy efficiency • Exploration of materials beyond silicon Their comprehensive #PDK, covering waveguides, splitters, and wavelength multiplexers, reinforces strong #PIC manufacturing maturity—key to scaling optical compute. As reported by #MoneyDJ citing #Nikkei: • #TSMC filed 50 U.S. patents in #siliconphotonics in 2024 — nearly double #Intel’s 26. • In 2023, the two were nearly tied (46 vs 43), showing #TSMC’s rapid acceleration. TSMC is positioning itself ahead of competitors, planning mass production of Co-Packaged Optics (CPO) by 2026, while Intel reportedly remains in R&D and demonstration phases. #TSMC’s #COUPE platform signals a decisive shift toward #heterogeneousintegration + #siliconphotonics as foundational technologies for future #AI, #HPC, and #datacenter #architectures. With rising I#P momentum and a clear #manufacturing #roadmap, #TSMC is staking an early lead in the #optical #computing #era. Image Source - TrendForce

Big news from MIT! The Optical AI Chip MIT researchers have developed a brand-new photonic (light-powered) chip that processes wireless signals at light speed—literally. This optical accelerator can: * Detect and classify signals in nanoseconds * Be ~100× faster than current digital alternatives * Hit ~95% accuracy in real-time signal processingnews.mit.edu+1ericsson.com+1news.mit.edu+1aihardware.mit.edu+1 Why it matters: * Paves the way for 6G networks, enabling smarter cognitive radios that adapt on-the-fly * Could supercharge edge AI—imagine instant decision-making in self-driving cars or real-time monitoring in medical devices * It's smaller, cheaper, and uses less power—making it ideal for next-gen IoT and communication tools This is just the beginning. The team envisions scaling to even more complex tasks—think transformer-model inference on the edge! 💡 In a nutshell: by merging optics + AI, MIT is pushing the limits of speed, efficiency, and real-time processing. This may be the engine behind future 6G, edge computing, and countless smart systems. Original research via MIT News
#6G #Photonics #EdgeAI #WirelessInnovation #MITResearch #OpticalComputing #AIHardware #NextGenNetworks

What if the future of AI acceleration lies in manipulating photons? A breakthrough research demonstrates ultra-compact in-memory optical computing chips achieving over 60,000 parameters per mm². This is stunning! These chips embed parameters directly into fixed optical components, enabling passive, high-throughput neural network computation that reduces power-intensive digital processing by 90% compared to electrical networks. Unlike our beloved von Neumann architectures which shuttle data between memory and processing units, these optical chips perform computation where the data resides, imitating a key feature of biological computation. Light becomes both the information carrier and the computational medium, achieving 95.9% accuracy on multiple datasets while operating at the speed of light. As we push toward more sustainable AI, the question we are asking is whether photonic neural networks become the foundation for the next generation of AI accelerators. This is an area to watch in 2026! #PhotonicComputing #InMemoryComputing #OpticalNeuralNetworks #SustainableAI #QuantumComputing https://lnkd.in/euF6fYzm

Light is no longer just a carrier of information. It is becoming the computer. Researchers at Queen's University have built a light-powered machine that tackles complex optimization problems, including protein folding for drug discovery and number partitioning for cryptography. Built from off-the-shelf lasers, fiber optics, and modulators, it runs at room temperature and performs billions of operations per second. Using an optical version of the Ising model, pulses of light interact and settle into low-energy states that represent high-quality solutions. The target applications range from supply chains to urban planning and drug design. Is photonic computing about to move from the lab to real-world deployment? Full article: https://lnkd.in/ekiriERV #photonics #opticalcomputing #optimization #drugdiscovery #cryptography #engineeringinnovation

🔴 Researchers from imec, EPFL, KTH Royal Institute of Technology, and Tyndall National Institute present the blueprint for next-generation integrated photonics in #MicrosystemsAndNanoengineering. The paper "Integrated silicon photonic MEMS" proves that combining micro electromechanical systems with standard foundry processes will define the next decade of #SiliconPhotonics and #OpticalComputing. While silicon photonics has emerged as a mature technology for high data rate communications and autonomous vehicle sensing, the material's weak electro-optic effects remain a bottleneck. Traditional thermo-optic tuning devices demand continuous power consumption and result in large footprints. This comprehensive research proves that integrating MEMS directly into silicon photonic circuits is the ultimate solution. 1️�� Overcoming Material Limits: #PhotonicMEMS & #EnergyEfficiency By replacing bulky traditional modulators with silicon photonic MEMS, the architecture drastically reduces the device footprint. Furthermore, it introduces bistable phase switches that enable nonvolatile photonic circuits, eliminating the need for continuous static power consumption. 2️⃣ Wafer Level Scalability: #Foundry & #Packaging The true breakthrough lies in manufacturability. The research highlights the successful implementation of wafer-level hermetically sealed packaging. This ensures that these advanced MEMS components can be produced with high yield and high volume capacity using standardized silicon foundries. 3️⃣ Reconfigurable Architectures: #OpticalRouting & #QuantumInformation This scalable integration provides access to fully reconfigurable coupled resonator optical waveguides. It unlocks optimized library components for complex optical routing, paving the way for advanced photonic accelerated computing and quantum information processing. 💡 My Take: As the demands of AI and data centers push optical communication to its limits, the massive power consumption of thermo-optic tuning in traditional silicon photonics is no longer sustainable. By physically moving microscopic silicon structures using MEMS, we can route light with near-zero static power. This research is a massive wake-up call for the industry. Transitioning from solid-state thermal tuning to wafer-scale integrated photonic MEMS is not just an incremental hardware update, it is a mandatory architectural revolution required to build energy-efficient, large-scale optical networks. 👇 Link in the comments #AdvancedPackaging #HardwareArchitecture #Metrology #3DIC #DataCenter #AIHardware #Telecommunications #Optoelectronics Intel TSMC Samsung Electronics GlobalFoundries NVIDIA Broadcom Marvell Technology Cisco Applied Materials ASML Lam Research Lumentum Coherent Corp. Infinera STMicroelectronics