TetraMem - Accelerate The World

Excited and honored for TetraMem to participate in the Lam Capital Venture Competition poster session alongside so many outstanding semiconductor and AI innovators! A big thank you to Lam Research and Lam Capital for the strong multi-round investment support and ongoing collaboration with TetraMem. Beyond investment, we are also working together through strategic technical collaborations and joint engagements to help accelerate next-generation intelligent semiconductor manufacturing with built-in AI capabilities! At TetraMem, we believe the future of AI computing will require fundamentally new architectures beyond conventional digital scaling. Our multi-level RRAM analog in-memory computing technology aims to dramatically reduce data movement and unlock the next leap in AI efficiency and scalability. Looking forward to the deep technical discussions and meeting everyone at the event! 🌟 #AI #Semiconductor #AIHardware #InMemoryComputing #AnalogComputing #RRAM #Memristor #DeepTech #LamResearch #FutureOfComputing #StartupInnovation

TetraMem Announces 22nm Multi-Level RRAM Analog In-Memory Computing SoC Milestone 🌟Excited to share that TetraMem has achieved a major commercial milestone based on years of deep technology development: our MLX200 multi-level RRAM–based analog in-memory computing SoC on a commercial 22nm TSMC process. This marks an important step in bringing analog computing—based on one of the most promising and disruptive non-volatile memory (NVM) technologies, RRAM (also known as memristor)—into real silicon at advanced nodes, moving beyond research toward scalable production. Why this matters: 👉 Memory and compute are converging through multi-level RRAM, enabling true in-memory computing with massive parallelism 👉 Data movement is now the dominant bottleneck in AI—driving power, latency, and cost 👉 RRAM brings key advantages: small cell size, multi-level storage, analog programmability, good retention, good endurance and CMOS compatibility 👉 Scalable to advanced nodes below 3nm, enabling continued gains in density and efficiency 👉 New architectures are needed, and analog in-memory computing offers a path beyond the von Neumann limit With EVK shipments targeted for 2H 2026, we are working closely with partners and customers to accelerate real-world deployment and full mask tape-out production! Special thanks to TSMC for their strong collaboration and support, and to our eco-system partners and customers for their continued trust and engagement. Proud of the entire team and our ecosystem partners who made this possible. 📄 Full release: https://lnkd.in/gCfnqeG3 #AI #AIHardware #InMemoryComputing #AnalogComputing #RRAM #Memristor #Semiconductor #TSMC #DeepTech #FutureOfComputing

Excited to see this work officially published in Science. A big step forward for pushing computing beyond traditional limits—proud of the team and our collaborators!! Onward 🚀 #RRAM #Memristor #DeepTech #AIHardware #Space

Every probe humanity has sent to Venus has failed. The Soviet Venera landers survived just 23 minutes to 2 hours under ~460°C. Even specially designed electronics eventually broke down—data stopped flowing. Now imagine computing systems that don’t just survive—but operate reliably far beyond that. We’re excited to share that our joint research with leading academic partners has been formally published in Science (May 15 issue): 🔥 RRAM / memristor devices operating at 700°C with multi-level capability 🔥 Data retention >50 hours at extreme temperature 🔥 >1 billion switching cycles 🔥 Low-voltage, high-speed operation This is not just a materials breakthrough—it’s a foundation for a new class of computing. At TetraMem, we believe this validates something deeper: 👉 Computing is moving closer to physics 👉 Memory and compute are converging 👉 AI infrastructure will extend beyond traditional environments include space! From edge AI to industrial systems—and ultimately to space-based AI infrastructure—this is a step toward enabling intelligence anywhere. Proud of the incredible collaboration across academia and industry that made this possible. 📄 Full announcement: https://lnkd.in/gWi6s44J #RRAM #Memristor #AIHardware #InMemoryComputing #Semiconductor #DeepTech #SpaceTech #SPACE #AnalogComputing #FutureOfComputing #USC #UMASS

Breaking through extreme conditions is not just a scientific milestone — it’s a pathway to real-world impact 🌟 While academic research continues to push the boundaries of what’s physically possible, the next step is translating these breakthroughs into scalable, manufacturable, and deployable technologies. At TetraMem, we are focused on exactly that:Bringing next-generation memory and computing innovations from lab concepts into production-ready AI hardware. We are proud to see foundational work led by J. Joshua Yang — Arthur B. Freeman Chair Professor at University of Southern California, and Co-founder, Scientific Board Member, and Chief Advisor of TetraMem — continuing to expand the frontier of memory technology!! From research to commercialization, this journey is what will ultimately define the future of AI computing 🌟 🌟 #TetraMem #AIHardware #Semiconductor #DeepTech #Commercialization #Innovation #FutureOfComputing #USC #USCViterbiSchoolofEngineering

Great event — thanks to the Foothill Ventures team and Enterprise Singapore for hosting such a meaningful discussion. The “Singapore Advantage” really stood out — as a strategic hub connecting global innovation, manufacturing, and deep tech ecosystems. These cross-border conversations are increasingly important as semiconductors and AI infrastructure scale globally. Appreciate the opportunity to connect with fellow founders and partners — looking forward to building more together!! #DeepTech #Semiconductor #AI #EdgeAI #DataCenter #Startup #GlobalInnovation #Singapore

Thank you Lam Capital for the great support and summary! GTC 2026 clearly showed that the AI stack is being fundamentally rewritten. A few reflections from our side at TetraMem – Accelerate The World: 🧠 The real bottleneck is shifting As AI becomes the infrastructure layer, the challenge is no longer just compute scaling — it’s data movement, memory, and energy efficiency. 👉 The industry is moving from: Compute-centric → memory-centric architectures Training focus → inference at scale ⚡ Inference is where efficiency matters most We fully agree — inference is now the strategic battleground. At scale, the key metrics are: *Energy per token *Latency *Cost efficiency This is exactly where compute-in-memory (CIM) and new architectures can deliver step-function improvements. 🔗 Beyond interconnect — reducing the need for movement Optical interconnect is a critical step forward, but it also highlights a deeper issue: We are still trying to move massive amounts of data faster. At TetraMem, we believe the next leap is: 👉 Eliminating unnecessary data movement altogether 🚀 Our perspective With memristor-based analog in-memory computing: *Compute happens where the data resides *Memory and compute are unified *Efficiency scales from edge to data center 🎯 Bottom line AI is becoming infrastructure — but its scalability will be defined by how efficiently we handle data, not just how fast we compute. Excited to see the ecosystem pushing forward across compute, memory, and interconnect. #AI #GTC2026 #Inference #EdgeAI #DataCenter #Semiconductor #Memory #ComputeInMemory #RRAM #Memristor #DeepTech

Proud to see this recognition — and grateful to be part of this journey. Huge congratulations to our co-founder, Prof. J. Joshua Yang and the entire USC community for this well-deserved spotlight. The work on memristor/RRAM, neuromorphic computing, and next-generation AI hardware is not only academically groundbreaking, but increasingly critical to the future of scalable AI systems. At TetraMem – Accelerate The World, we are excited to translate these innovations into real-world impact — from analog in-memory computing to enabling efficient AI across edge and data center. As AI continues to scale, breakthroughs in memory and compute architectures will be key to overcoming the limits of today’s systems. Looking forward to seeing even more innovation coming out of USC and the broader ecosystem. #USC #Innovation #AIHardware #RRAM #Memristor #ComputeInMemory #Neuromorphic #Semiconductor #DeepTech

Great discussion at the CASPA Spring Symposium — many thanks to Joe Chen and the CASPA Office team for organizing such a timely event. This year’s focus on storage really resonated. As AI scales, data movement and memory are becoming the true bottlenecks — not just compute. 🧠 Mobile vs. Cloud — Our View While massive investments are flowing into AI data centers, the mobile side risks being underdeveloped. If mobile cannot deliver low-power, high-performance AI chips, we risk a future where: *AI lives only in the cloud *Devices become thin clients *Smartphones become “dumb” again 🚀 TetraMem’s Perspective At TetraMem, we believe the path forward is not just scaling compute — but eliminating data movement across both edge and data center. With memristor-based analog in-memory computing: *Enable large-scale models on edge devices *Operate within mobile power constraints *Deliver significantly lower energy per token *Scale seamlessly from data center to edge as a unified computing fabric 🎯 Bottom Line If AI becomes efficient enough at the edge, demand will explode — across both mobile and cloud. That’s the future we are building at TetraMem – Accelerate The World! #AI #EdgeAI #MobileAI #DataCenter #Semiconductor #Memory #ComputeInMemory #RRAM #Memristor #Innovation

🚀 Memristor / RRAM Are Ready for Space Data Center!!! We’re excited to share that memristor (RRAM) technology has reached a major milestone — demonstrating reliable operation under extreme conditions, including up to 700°C and harsh space environment, while maintaining strong endurance. This is a powerful validation that RRAM is not only ready for next-generation AI computing, but also for the most demanding environments — from edge to space. 📄 The work has just been published as a main article in Science: https://lnkd.in/dHKFrmKQ 👏 Congratulations to the entire team on another outstanding achievement!! 🔥 Why this matters Extreme reliability → Enables aerospace, defense, and harsh-environment applications High endurance under stress → Validates long-term stability of RRAM devices Broadens the horizon → From AI acceleration to space-grade computing 💡 At TetraMem, we believe breakthroughs like this continue to reinforce the foundation for analog in-memory computing (A-IMC) — delivering scalable, efficient intelligence across edge, data center, and beyond Earth. #RRAM #Memristor #AIHardware #Semiconductor #SpaceTech #ComputeInMemory #Innovation #USC #UMASS