IQT (In-Q-Tel)’s Post

Early in my career I worked on Data Center Modernization for the US Navy. I created a long list of every server in Naval inventory that I could find, and then identified exactly what was running on that server. Our goal was to virtualization this infrastructure so it was ready to move to the cloud. I don’t want to do this again. Generative AI is not just transforming industries—it will be a cornerstone of global competition and national security. As AI systems like GPT-4 and beyond scale, they’re exposing a critical vulnerability in the U.S. technological landscape: our reliance on Conventional Compute Era (CCE) infrastructure—legacy hardware and software built for workloads like enterprise SaaS and high-performance computing. These systems were not designed to meet the demands of today’s AI, and the resulting bottlenecks, as IQT points out, are already slowing progress. I’m glad IQT has raised this issue because I’ve long been thinking back to my Navy day’s as we face scaling challenges. To maintain the U.S.’s leadership in AI, we must embrace the Neural Compute Era (NCE)—a new paradigm of hardware and software purpose-built for AI’s unique requirements. This shift isn’t just a technical evolution; it’s a strategic necessity. Investing in NCE infrastructure will enable the scalability, speed, and energy efficiency required to train and deploy cutting-edge models, instead of retrofitting CCE technologies to create bottlenecks that put national security at risk. The need for AI infrastructure in the NCE is rapidly becoming a key element of economic resiliency and national security strategy. Building hardware is difficult, and the U.S. risks ceding ground to nations that are already doubling down on sovereign AI capabilities. This is a thesis I’m deeply passionate about: we need to invest now in building infrastructure for the NCE. I want to thank IQT (In-Q-Tel) for highlighting this issue, which I’ve been discussing with others in the field. Policymakers should take note, AI doesn’t wait for legislation to pass where investments are needed today. The CHIPS Act is a great start to rebuilding the manufacturing base but it needs follow-through to accelerate us deeper into the Neural Compute Era (NCE). The future of AI—and our security—depends on it.

IQT (In-Q-Tel) believes the future of #AI depends on our ability to solve the infrastructure challenges that we face today as quickly as possible. The demand for generative AI is only going to increase—and without a new foundation, the digital infrastructure that powers this transformative technology will struggle to keep up.  Countries who do so will gain a significant advantage in the global AI race, while those who delay risk falling behind.   This blog by my coleagues Rita Costa Waite, Abirami Sivananthan and Esube Bekele dive into this topic. Give it a read.....

While generative AI continues to dominate the headlines, edge AI is set to usher in new possibilities for the #industrial world. Edge #AI describes the processing of data when and where it’s generated (that is, at the edge of a network), rather than relying solely on remote cloud servers. Proponents of this approach state that by moving computing power to the edge, companies can access #insights that help improve their operational #efficiency. Paul Bloudoff - Senior Director of edge services at NTT DATA says "“We are seeing several enterprises pushing for these solutions. The reason is that Edge AI brings actionable intelligence and real-time decision-making possibilities into operational technology environments, such as the factory floor.” https://lnkd.in/ggwPnTDg

Another great article in the The Wall Street Journal this morning which highlights a seismic shift in the tech world driven by #AI advancements. As #artificialintelligence becomes more integral to business operations, it's reshaping the very foundation of tech infrastructure. 🔍 Key Takeaways: - Infrastructure Overhaul: Companies must rethink their IT frameworks to support AI’s growing demands for data processing and storage. - Cloud Computing Surge: The rise of AI is accelerating the need for robust cloud solutions, driving investments in scalable and flexible cloud infrastructures. - New Technology Paradigms: Traditional IT setups are being replaced by more dynamic, AI-optimized systems, necessitating a shift in tech strategies and resource allocation. This article underscores that adapting to these changes isn't optional; it's essential for staying competitive in an increasingly AI-driven landscape. And with Kyndryl being the worlds largest infrastructure services provider, we are in a prime spot to help customers with their #ai strategy and adapt to these changes! AI is not just a tool but a catalyst for fundamental infrastructure #transformation. #AI #TechInfrastructure #CloudComputing #DigitalTransformation #Innovation https://lnkd.in/eewwcFfi

With all the talk of the impact of AI on data, it is forcing tech leaders to examine their cloud infrastructure and AI readiness more deeply, as outlined in this WSJ article. --> AI models need to analyze massive historical datasets to generate insights and improve performance, demanding a fundamentally different approach to data storage and access. Companies like CoreWeave and VAST Data are stepping up to meet the challenge with innovative solutions for storage and access. --> CoreWeave is focused on the hardware side, providing the computing power via access to NVIDIA chips. VAST Data is tackling the software side, optimizing data storage and access for AI workloads. Together, their solutions aim to meet the increasing demands of AI-driven data growth in the cloud. Is your business prepared for a heavier cloud and the new era of AI-driven data? #AI #CloudComputing #DataStorage #Innovation https://lnkd.in/gYwPKfEh

🤖👾Companies around the globe are utilizing AI on the internet continuously—without AI processors in end-user devices, maintaining peak performance becomes a challenge. Explore the following article to understand how companies are meeting the technological demands of AI.👾🤖

Is AI the thunder that breaks up the cloud, or does it come from it? The computing pendulum swings from the edge to the cloud and back again. 💡 Enterprises are increasingly hesitant to release their data and IP to train Gen AI models. This has sparked a new wave of edge and server innovations, making “on-prem” hot again. 📊 SaaS must rethink how and where the data (or AI brain) is stored and processed. 🌐 This fundamental shift in computing architecture is driving massive market growth opportunities. Partner ecosystems are set to move up the value chain substantially. 🎓 Get that math degree! It’s going to come in handy! #AI #EdgeComputing #CloudComputing #SaaS #PartnerEcosystems

💡 Exploring the future of AI: Edge AI vs. Distributed AI 🌐 Dive into the comparison between the two paradigms! #EdgeAI #DistributedAI #Innovation #TechTrends #FutureTech #MachineLearning #ArtificialIntelligence #TechDebate

Explore how custom AI infrastructure is transforming enterprises, driving competitive advantage, and revolutionizing the industry landscape in this comprehensive analysis. https://buff.ly/3BmUe70 #ArtificialIntelligence #enterprise #AIinfrastructure

To help you keep up with the current state of #AI, its trends and challenges, and to learn about best practices for building and deploying scalable and efficient AI systems, we’ve recently published the "The State of AI Infrastructure" report. Read here: https://lnkd.in/djbKpV79 #cloudinfrastructure #AIinfrastructure #artificialintelligence