Rajiv Khemani retweeted
Today’s guests are Barun Kar, CEO, and @rkhemani, Executive Chairman at @upscale_ai_inc. Barun and Rajiv’s bet is that the AI era needs its own network: open, standards-based and built to connect AI chips to each other. From switch silicon to supply chains, we discuss: - How scale-up and scale-out networks work - Where copper, optics and optical switches fit - Why open standards matter for AI chips - What a network operating system does - How Upscale secures its supply chain - Building culture while scaling to 300 people Timestamps: 0:00 Introduction 1:05 Why AI needs a new network 5:21 Why cloud-era chips fall short for AI 9:05 Scale-up and scale-out inside an AI rack 16:09 The Auradine spin-out and Upscale’s founding story 20:52 Memory semantics versus packet switching 27:23 From Cavium and Palo Alto Networks to Upscale 32:23 Competition and the system-level advantage 35:55 What a network operating system does 37:01 Optics and optical switching 41:45 Selling to hyperscalers, new clouds and enterprises 47:40 How big AI networking could get 50:43 Securing supply across the chain 54:29 Building at the forefront of AI 57:40 Beyond networking: what comes next 1:03:38 Building culture in a fast-growing company Listen to the show, and follow along for new episodes every Tuesday.
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Rajiv Khemani retweeted
Most of the attention in AI goes to the chips. Barun Kar and @rkhemani working on how those chips get connected, and they’re betting that network should be open instead of locked to one vendor. New episode of The Compute 100 with the @upscale_ai_inc founders.
Today’s guests are Barun Kar, CEO, and @rkhemani, Executive Chairman at @upscale_ai_inc. Barun and Rajiv’s bet is that the AI era needs its own network: open, standards-based and built to connect AI chips to each other. From switch silicon to supply chains, we discuss: - How scale-up and scale-out networks work - Where copper, optics and optical switches fit - Why open standards matter for AI chips - What a network operating system does - How Upscale secures its supply chain - Building culture while scaling to 300 people Timestamps: 0:00 Introduction 1:05 Why AI needs a new network 5:21 Why cloud-era chips fall short for AI 9:05 Scale-up and scale-out inside an AI rack 16:09 The Auradine spin-out and Upscale’s founding story 20:52 Memory semantics versus packet switching 27:23 From Cavium and Palo Alto Networks to Upscale 32:23 Competition and the system-level advantage 35:55 What a network operating system does 37:01 Optics and optical switching 41:45 Selling to hyperscalers, new clouds and enterprises 47:40 How big AI networking could get 50:43 Securing supply across the chain 54:29 Building at the forefront of AI 57:40 Beyond networking: what comes next 1:03:38 Building culture in a fast-growing company Listen to the show, and follow along for new episodes every Tuesday.
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Rajiv Khemani retweeted
Our $110M Series A was featured in @SemiEngineering's roundup of notable industry funding rounds, reflecting the growing importance of purpose-built compute for Physical AI and ultra-low-power compute for AI data centers. We’re proud to be featured, a testament to the technology and culture we’re building here at @Velaura_AI. Read the full roundup for more on our Series A funding: semiengineering.com/startup-…
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Rajiv Khemani retweeted
We’ve refreshed our website to better reflect @Velaura_AI’s vision, the technology we’re building, and the deep industry expertise behind it. With a new look and expanded content, the site highlights how we’re addressing two major AI megatrends: Physical AI and ultra-low-power compute for AI data centers. Explore how our purpose-built Physical AI SoC is designed for the next generation of intelligent robots, drones, and autonomous systems, as well as how our Titan Core™ solution addresses the data center power challenge with patented technology that reduces power consumption for arithmetic operations in AI accelerators by 2–4x. Backed by decades of semiconductor leadership experience and underlying technology proven at commercial scale with over 30 million ASICs deployed, Velaura AI is bringing proven silicon innovation to the next generation of AI compute. Explore our refreshed website: velaura.ai/
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Rajiv Khemani retweeted
Three Upscale teams. Two winning projects at the SONiC 2026 Hackathon. 🔍 Streaming orchagent records over gNMI: youtu.be/Pw5PkH1XRG4?t=3206 🏆 Bridging sonic-mgmt to KNE: youtu.be/Pw5PkH1XRG4?t=6335 🏆 Firebreak: youtu.be/Pw5PkH1XRG4?t=7304 Thanks to the SONiC Foundation for hosting.
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Rajiv Khemani retweeted
Thanks to @nvidia's Gilad Shainer and Wei-Ai Tai for visiting us at OCP! “By using NVIDIA Spectrum-X Ethernet for Token Fabric’s scale-out systems, Upscale is helping customers build high-performance, open and heterogeneous AI infrastructure." - Gilad. upscale.com/blogs/upscale-in…
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Rajiv Khemani retweeted
Velaura AI Co-founder and President Sanjay Gupta joined Richard Nass on @embedded_comp's Embedded Executive Podcast to discuss two major opportunities shaping AI: ultra-low-power compute and Physical AI. The conversation explores what’s required from an IP and design perspective to reduce AI compute power consumption without compromising performance or reliability. Tune in to hear Sanjay’s perspective on these opportunities and what’s ahead for @Velaura_AI. Full recording: embeddedcomputing.com/techno…
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Rajiv Khemani retweeted
One fabric. Any accelerator. Upscale's Token Fabric simplifies networking for heterogeneous compute. At NeoCloud Summit, Upscale's Aravind Srikumar explored how Token Fabric brings scale-up and scale-out networking together in one unified architecture. #SFTechWeek
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Rajiv Khemani retweeted
Satya is right. The way to make SI safe is not to train it with a sense of self, its own moral philosophy, and permission to act as a conscientious objector. That’s the “alignment” approach and it magnifies the control problem. The engineering approach that Satya describes is different: separate the supply of intelligence from authority over it. Surround non-deterministic models with deterministic controls, observability, privilege limits, logging, and the ability to always contain or shut them down. Treat models/agents like powerful insider risks, not moral patients whose psychological wellbeing is at stake. As Satya points out, the most trustworthy system is the one that lets us trust the model the least — not the one that encourages the model to develop independent agency and grievances. Engineering safety is not the same thing as “alignment.”
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Really sad and concerning if this is true!
We are terminating Chris Degnan for unethical conduct involving Cognition. The last few months have seen incredible progress in AI capabilities. San Francisco has flourished as new companies that solve new, more ambitious problems are finding great success. Generally, it is a wonderful time to be building. We at @FactoryAI have seen overwhelming interest in our model-agnostic coding agents and our software factory product. Our team has 10x’d in size, while our revenue has 100x’d year over year. This momentum has been unprecedented. A much larger competitor, Cognition (makers of Devin) has fallen behind us on the capabilities that matter most to customers: cost, quality, and security. Instead of competing in the market, Cognition engineers feigned interviews with us to pry information about our product. Not finding what they were looking for, Cognition has decided to throw their weight and money at people with direct knowledge of our most confidential plans. It feels as though ethics is being thrown out of the window in the AI era. People are willing to do anything, including exploiting privileged information and violating ethical boundaries. I think this is unique to our time, and I don’t think it’s right. Integrity still matters. Yesterday, I made the decision to immediately terminate Christopher Degnan’s roles as a Board Observer and Advisor to Factory, after over a year of service. Prior to this decision, Chris told me he had a casual conversation with an executive at Cognition AI. When I questioned his intentions, he reassured me that ethics aside, he had “made too much money” and was “too lazy to go work for Cognition,” which I trusted and believed. On Monday, Chris spent time advising the Factory team on a handful of confidential board-level matters. That evening, he called me to say that the conversation that was initially described as casual and one-off was actually formal and recurring. For weeks, while he sat in our board meetings and advised our leadership team, he was also confiding with executives of our largest competitor. Chris was subject to confidentiality obligations in connection with his work with Factory. We do not know the extent of the information he shared, but it puts his timely questions about our product roadmap and what the parity gap involves into a new light. It is sad to sever a relationship with someone who has been a trusted advisor - and even a close friend - for over a year. But Chris’s conduct is unacceptable to me. Trust in Board Membership is one of the sacred bonds in the Silicon Valley, one that helps the startup ecosystem thrive. With it comes an enormous responsibility. That trust was violated. Competition is good. I respect and in many cases admire our competitors. San Francisco is a beautiful, singular place where the bold and ambitious go to defy the norms and precedents of the past. But certain principles that must remain. Violating ethics to seek advantage turns what should be positive-sum into zero-sum. We all love technology. And we all love to compete. But we must hold ourselves to a higher standard. The future of software engineering comes with abundance that will impact every person on Earth. Building that future comes with immense responsibility. We must build and compete with integrity.
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Rajiv Khemani retweeted
Velaura AI welcomes Vishal Bhargava as Vice President of Engineering for our India team. Vishal brings nearly 30 years of CPU design, silicon development, and engineering leadership experience from @intel, where he most recently served as Vice President of All Cores Engineering and led a 500+ person organization in India. His deep technical expertise and leadership will be an important addition as we expand in India and advance ultra-low-power compute for data centers and purpose-built compute for Physical AI. Please join us in welcoming Vishal to @Velaura_AI.
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Rajiv Khemani retweeted
We’re building the team to take on some of the most important challenges in AI, from power efficiency in hyperscale data centers to the requirements of intelligent systems operating in the physical world. Explore open roles and join us: jobs.lever.co/velaura
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Rajiv Khemani retweeted
Myth: Reducing power in battery constrained Physical AI applications means sacrificing performance. Reality: Physical AI demands a different approach to compute, one designed to deliver the performance autonomous systems require within tight power and thermal constraints. But power is only one part of the challenge. Physical AI compute also needs to address latency, memory, and safety to support increasingly capable robots and drones operating in the physical world. For @Velaura_AI, that means rethinking the compute architecture itself to meet those demands together, not in isolation.
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Rajiv Khemani retweeted
My wife’s best friend’s husband died today from colon cancer. 6 weeks from diagnosis to death. In his 50s. Worked out. Not obese or diabetic. Get your colonoscopy and Cologuard. Get a Galleri DNA cancer test if you want to identify it before polyps grow.
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Rajiv Khemani retweeted
Heading to AI Infra Summit? Join Deepti Chandra for a discussion on how open, programmable fabrics for heterogeneous compute can break through the networking bottlenecks holding back high-utilization inference at scale. 📅 September 16, 2026 Plus, stop by Booth #1140.
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Rajiv Khemani retweeted
Today we're excited to announce Mercury 2.5 It’s the most capable diffusion LLM on the market. It is a 40% jump in intelligence over Mercury 2 and runs at over 1,100 tokens/sec on widely available @NVIDIAAI GPUs. inceptionlabs.ai/blog/introd…
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Rajiv Khemani retweeted
Thank you to @Nasdaq for recognizing @Velaura_AI's $110M Series A and celebrating this milestone on the @Nasdaq Tower. The financing reflects continued conviction in Velaura’s technology, team, and vision to advance ultra low power compute for data center and Physical AI applications. We’re grateful to our investors, partners, and team for the continued support behind this milestone.
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The ongoing AI infrastructure buildout is the largest in the history of humanity. Many times larger than the infrastructure for highways, railroads, aviation, telecommunications, internet, mobile or cloud. Likely many times all of them combined. Physical AI expansion hasn't even begun. This should last 10-15 years or more. Exciting time to be building!
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The AI infrastructure buildout now underway is the largest in human history, surpassing highways, railroads, aviation, telecom, the internet, mobile and cloud. And Physical AI has barely begun. This is a 10–15+ year transformation. An extraordinary time to be building!
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