Nikesh Arora

We are excited to back Morphing Machines. As Dr. Ranjani, CTO and co-founder says: “For the first time in India and globally, we have a processor that is truly runtime reconfigurable, catering to emerging workloads.” While Nvidia’s growth and high valuation are driven by robust demand for “infra-compute” in high-performance GPUs, spurred by Gen AI, there is a distinct need for innovative solutions tailored to a new wave of reactive applications. Enter Morphing Machines. It addresses this demand with its unique product designed for next-gen telecom, autonomous vehicles, collaborative robots, avionics, and online data analytics. This product is specifically engineered to handle heterogeneous workloads and diverse tasks with varying performance demands simultaneously, ensuring a high level of scalability. As we move from an institutionally-backed research team at IISC to productization, Golden Sparrow is collaborating with Speciale Invest and others to support Deepak Shapeti, who joined as CEO three years ago after earning his Masters at Stanford. He brings not only technical expertise but also the business acumen necessary to guide the product to commercial success. Venkat Raju Afreed Faizan Anand Rao Ritik Singh Michael Marmor

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💡 #MOCHAX #PORTFOLIO ➡️ TwinMatrix Technologies (tmt) 🦄 TwinMatrix Technologies (TMT) operates in the spatial computing sector that is underpinned by several key technologies. 🚀 Market Size and Growth: Current Market Size: The spatial computing market was valued at approximately $81.8 billion in 2022. Projected Growth: It is expected to grow to around $269.8 billion by 2030, with a compound annual growth rate (CAGR) of 23.5% from 2024 to 2031 (The Brainy Insights) (AB Newswire). #SpatialTwins #DigitalTwins #Web3 #Innovation #MOCHAX

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With over 20 years of experience building accelerated computing solutions across domains, such as security, data movement, and data storage, DataPelago CEO and Co-Founder Rajan Goyal has assembled a world-class team with decades of expertise across system, architecture, data analytics, cloud SaaS, open source development, and more to rethink data processing in today's AI-driven world. Today, the company came out of stealth with $47M in funding and introduced the first universal data processing engine and ultimately, is creating a new data processing standard for the accelerated computing era to overcome performance, cost, and scalability limitations. By enabling data to be extracted as quickly as it's generated, businesses will have the ability to harness insights to make better decisions and operate more efficiently, unlocking new possibilities in critical industries like supply chain, healthcare, energy, and more. https://bit.ly/4gG5hIy   Congratulations Rajan Goyal and DataPelago team!

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No Vendor lockins, No Proprietary Stuff, Freedom in using the Cloud, Data Sovereignity is the way to go! And of course lower TCO and better quality of service. Computing should be a utility, simple and easy to use, not just for techies. This is what we are set out to do at People+ai #OpenCloudCompute #OCC

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Buckle up your seats. Recogni’s simulations have its single-rack system offering 320,000 tokens/s for Llama3.1-405B (2304 concurrent users), with 3× faster time to first token (TTFT) and 6.4× faster time per output token (TPOT) compared to an equivalent size Nvidia H200-based system. Competition to the NVIDIA domination is coming and real !!! #genai #gpu Celesta Capital

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Looking forward to this talk. #HPC, #AI, or any other sensitive workloads are not truly confidential without securing them AND verifying the integrity of that security. Both AMD and Invary are critical components of this, showcased through the NSA's maat project. Join us and use the code SPEAKER15 to get 15% off your pass. #CCSummit

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In the rapidly evolving landscape of artificial intelligence, the phenomenon of shadow AI—unofficial AI projects operating without formal oversight—poses unique challenges for large enterprises. This roundtable discussion at the AI Networking Summit next week during ONUG Spring in Dallas will dive into the complexities of shadow AI, examining its risks, including security vulnerabilities, data silos, and inefficiencies. You can see the full agenda here: https://bit.ly/3va215q

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📣 Announcing Whiterabbit: A Cybersecurity Venture Studio Building the Future of Security I've partnered with Nir Polak (former founder & CEO of Exabeam) to create https://whiterabbit.vc. ## Who We Are 🚀 Whiterabbit is a venture studio assisting dreamers in turning ideas into industry-leading companies ## Why We Created Whiterabbit Because we believe in being more than just investors. While traditional VCs invest money and offer advice, we're founders and operators at heart. Our mission is to actively create and build cybersecurity companies from the ground up, not just invest in them. We're here to transform ideas into industry-leading companies by rolling up our sleeves and doing the work alongside passionate founders. We believe the best companies solve the most annoying and seemingly benign problems. We love starting from the smallest idea and pulling the string to create something amazing - that's how greatness is born. ## Who We're Not ❌ A VC investing in existing teams and companies ❌ An accelerator for an existing company ## What We Do ✅ Partner with passionate founders to build next-generation cybersecurity companies ✅ Identify and validate the right problems to solve in the cybersecurity industry ✅ Accelerate the process from ideation to acquiring customers ✅ Leverage our extensive network and reputation to help startups rise above the noise ✅ Assemble exceptional founding teams by attracting the best talent ✅ Work closely with founders, immersing ourselves in the challenges they face ✅ Write a $5m+ first check into the company ## We're Looking For 🔍 Passionate people who love cybersecurity and want to create companies to solve real problems 🔍 Advisors who deal with problems everyday and wished there was a solution to it no matter how big or small #Whiterabbit #Cybersecurity #VentureStudio #StartupInnovation #TechEntrepreneurship

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This is what I mean when I say AI x DEEPTECH A revolution is coming. Upending entire swaths of our economy that have been previously ignored. Nearly $10 Trillion of our GDP rebuilt with AI and software.

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** This is not Financial Advice, so do your own due diligence ** $50B TAM for 1M GPU Clusters? legendary CEO Hock Tan of Broadcom believes so. I had the opportunity to listen to Hock Tan at Arista Networks 10 year IPO anniversary. Hock believes that for generative AI to truly develop AGI or ability to reason capability, it will need 1M GPU clusters and only 2 or 3 Hyperscalers or one or two sovereign customers have the capability to build such massive clusters. Hock Tan estimates the $50B TAM per 1M GPU clusters includes $30B for GPUs (assuming GPU ASP of $30K), $5B for Networking (interesting 6:1 ratio between GPU/compute to Networking), $15B for infrastructure like Power, including power generation, cooling, data center space etc. What plausible business case supports such as massive investment? remains to be seen. Hock admits its more of a moon shot type project but believes we are getting there. The biggest inhibitor to scaling GPU or compute capacity remains power. I think this has profound implications for investors. While power generation capacity takes long time to come online (7 - 8 years) and new data center buildouts take (2 - 3 years), the only way for Hyperscalers (like Amazon Web Services (AWS), Google and Microsoft) to bring more compute functionality they will have to upgrade their existing brownfield infrastructure. This should be positive for Intel Corporation, AMD and of course NVIDIA, as not only do we have the possibility of more accelerated compute deployments, but also the upgrade of non-AI compute infrastructure. Prior to the AI momentum, the upgrade cycle of traditional compute was stretching to 5 - 6 years, with most hyperscale CFOs pushing for extending the amortization schedule of the compute assets. Power limitations and growing demand for AI capabilities will force these hyperscalers to rethink their amortization schedule and thus I believe the pendulum swings in favor of infrastructure providers. Shorter upgrade cycles, more emphasis on higher, more power efficient technologies is great for networking such as Arista Networks and optics suppliers such as Coherent Corp., Lumentum etc. Interestingly, Hock Tan believes that as AI LLM models achieve AGI capability they will begin to generate their own data(thus the ability to reason) and will not require massive external data to be trained on, thus representing significant implications for wide-area bandwidth requirements. Would love to hear Bill Gartner's thoughts on this. Hock Tan also believes that power limitations will shift the balance in favor of customer ASICs vs. GPUs. While ASICs in general are more power efficient than GPUs, I think this outcome entirely depends on the maturity of the LLM models. In the past the hyperscalers optimized for $1/Gigabit of bandwidth, but now they need to optimize for power/Gigabit. This has profound implications for networking and optics supply chain. Would love to get your thoughts.

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The AI Wave Is More Than Just Compute: Why Networking Companies Are Set to Explode 💥 A recent article in Barron's highlights the critical role of networking infrastructure in the development of #AI. As AI systems grow to accommodate an endless amount of compute, it becomes crucial to make the next leap in networking to support efficient data sharing and increasingly demanding performance requirements. While companies like NVIDIA have dominated the AI chip market, the Barron's article emphasizes that the AI wave extends far beyond just compute, mentioning networking companies such as Broadcom, Cisco, Arista Networks, and Marvell Technology that will play an even more critical role in the AI revolution. At Pitango First, we've never been shy about taking bold bets on the next revolution, stemming from our analysis of where data center and data technologies will evolve. Our thesis for #The_New_AI_Stack focuses on critical layers that will be disrupted as AI takes a major share of the workloads. We’re proud to be first backers in Speedata.io (compute), Volumez (storage), and DriveNets (networking) - and we’re true believers in the immense opportunity ahead. As the AI landscape continues to evolve, we believe that those companies will have a critical role. Pitango is committed to supporting companies that are shaping the future of AI infrastructure. Link to the full Barron's article in the first comment. #AI #Networking #VentureCapital #Investment Pitango Eyal Niv Yair Cassuto Gad Huldai Aviv Barzilay

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Very good interview with Avijit Sinha, President of Wind River and Amazon Web Services (AWS) at their #reinvent event, on the importance of #edgeAI and their investment in this area - including a nice shout out for EDGE AI FOUNDATION …! Bill Podrasky Efren Mercado Michael Kuptz Rosina Haberl Evgeni Gousev Walter Sullivan Sandeep Modhvadia

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The 7th workshop on Neural Scaling Laws is about to start: https://lnkd.in/gQSB5k8v Scaling laws, emergency, alignment, transfer learning, with a focused track on multilingual models. Looking forward to kick it off with Irina Rish and discuss all these topics with Yuhai Tu, Paul Bogdan, Hailey Schoelkopf, Darshil Doshi, Rio Yokota, Neha Sengupta, Preslav Nakov, Tatiana Shavrina, PhD, Yishi Xu. Join in person or virtually! #icml2024 #ai

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Good story by Karan Kamble about how the Tanvi Lall led OCC could be India's answer to the market dominance of Azure, AWS and GC types. Could be an UPI moment for cloud computing in India! https://lnkd.in/gbFBAyJj

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Challenges of AI Networking for hyperscalers and enterprises Sept 27, 2024 I had the opportunity to meet with Manohar Paluri, VP of AI at Meta, this evening at the AI Tech Leaders Club, just under 24 hours before the AI Infra Summit on September 27, 2024. It’s been confirmed that the large training cluster at 500K GPUs is the next frontier for the hyperscaler industry. Meanwhile, on the enterprise side, standalone cluster sizes typically range from 20K to much smaller setups for retraining and inference. From my experience, while the challenges in these two sectors are intertwined, they can still be stated separately. 1) Checkpointing Challenges: Large GPU clusters require numerous checkpoints to maintain system reliability. The industry has recently implemented networking and checkpointing solutions for clusters with around 20K GPUs. Imagine the challenges we’ll face at the scale of 500K GPUs! 2) GPU Utilization: Typical GPU utilization hovers around 20%. While hyperscalers may achieve better numbers, overall utilization remains low. For this, a startup came up a clever solution to power down the idle GPUs dynamically to save up to 60% of power consumption from a GPU cluster. This approach could either reduce power usage from idle GPUs or, in conjunction with increased GPU utilization through further resources sharing—like memory, network, and model partitioning/parallelization—enhance overall efficiency. 3) Deployment Flexibility: The deployment of data center networks (hyperscaler cloud) or private networks (on-premises) for enterprises often lacks the necessary flexibility. For more insight, I recommend reading the justification for Google’s Optical Circuit Switching (OCS) network. Following conventional practices without innovative solutions can lead to over-investment in AI and cloud infrastructure. 4) ROI Optimization: Classic cloud infrastructure is often not optimized for ROI in AI networking, which leads to operational challenges for enterprises. To understand this, a little involved discussion is needed. Once understood, it becomes part of your instinct. Consider the competitive disadvantage faced by businesses that optimize ROI in their AI networks. Free Takeaway from me: Conversations about the challenges of AI infrastructure and networking are very welcome at the AI Infra Summit, and participants will receive the latest AI networking problem slide! 😊

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