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Most organizations are solving today's problems with today's tools. Quantum computing, intelligent systems, and next-gen infrastructure are already converging, well before most enterprises have finished their current AI roadmap. At HPE Discover 2026, David Nicholson sat down with Kirk Bresniker of HPE to look past this week's AI headlines...

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Six Five Media

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99,678 次观看 • 2 个月前 •via X (Twitter)

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A year is a long time in the AI infrastructure market right now, long enough for enterprise deployments to move from isolated pilots into platforms that have to function end-to-end. Networking, compute, and open ecosystem architecture are converging faster than most organizations have reorganized their strategy to match. At HPE Discover 2026, David Nicholson and Matthew Kimball sat down with Trish Damkroger and Praveen Jain of HPE to break down sovereign AI's growing urgency and where Helios fits into HPE's broader AI strategy.
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A year is a long time in the AI infrastructure market right now, long enough for enterprise deployments to move from isolated pilots into platforms that have to function end-to-end. Networking, compute, and open ecosystem architecture are converging faster than most organizations have reorganized their strategy to match. At HPE Discover 2026, David Nicholson and Matthew Kimball sat down with Trish Damkroger and Praveen Jain of HPE to break down sovereign AI's growing urgency and where Helios fits into HPE's broader AI strategy.

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Modernization, AI adoption, security, and cost control used to be sequential decisions. Now they are landing on enterprise leaders' desks at the same time. At HPE Discover 2026, David Nicholson and Tom Hollingsworth sat down with Dante Orsini and Justin Giardina of 11:11 Systems to get into why infrastructure complexity has become this cycle's defining challenge.
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Modernization, AI adoption, security, and cost control used to be sequential decisions. Now they are landing on enterprise leaders' desks at the same time. At HPE Discover 2026, David Nicholson and Tom Hollingsworth sat down with Dante Orsini and Justin Giardina of 11:11 Systems to get into why infrastructure complexity has become this cycle's defining challenge.

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A 2.7x cost-per-token reduction on the same infrastructure, just from optimizing memory tiering and KV cache offload. That's the kind of number CIOs bring to the board, not a roadmap slide. At HPE Discover 2026, David Nicholson and Matthew Kimball sat down with Justin McGarry of HPE and Justin Christiansen of Intel to break down what's actually driving enterprise AI infrastructure decisions, including a new edge device running 80B parameter models from under an airplane seat.
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A 2.7x cost-per-token reduction on the same infrastructure, just from optimizing memory tiering and KV cache offload. That's the kind of number CIOs bring to the board, not a roadmap slide. At HPE Discover 2026, David Nicholson and Matthew Kimball sat down with Justin McGarry of HPE and Justin Christiansen of Intel to break down what's actually driving enterprise AI infrastructure decisions, including a new edge device running 80B parameter models from under an airplane seat.

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Distribution used to mean fulfillment. Now Eric Kohl of Ingram Micro USA calls complexity "job security," and the partner ecosystem has grown complicated enough to prove him right. At HPE Discover 2026, David Nicholson and Tom Hollingsworth sat down with Kohl to break down what distribution actually requires across networking, security, and AI convergence, from automated quoting to identity as the new perimeter.
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I sat down with NVIDIA Sam Stanwyck (Sam Stanwyck) at ISC to talk about one of the most misunderstood areas in computing: quantum. We discussed why NVIDIA is not building a quantum computer, but instead the infrastructure around it: GPUs, AI, CUDA-Q, quantum simulation, control systems, error correction, and the path toward hybrid CPU/GPU/QPU supercomputing. The key takeaway: Quantum will likely not arrive as a standalone magic machine. It will arrive as part of a much larger accelerated computing stack, combining classical supercomputers, AI, GPUs, and quantum processors to tackle problems in chemistry, materials science, energy, optimization, and fundamental science. Full episode with Sam Stanwyck is now live.

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148,133 次观看 • 3 个月前

BREAKING: THE MOST IMPORTANT VIDEO TO WATCH IF YOU ARE INVESTED IN QUANTUM COMPUTING COMPANIES. $IONQ $RGTI $QBTS $QUBT The world's leading quantum computing researcher Scott Aaronson calls out the scams and snakeoilmen in the public quantum computing stock market. $IONQ $RGTI $QBTS $QUBT - "The most important thing that I can say in this whole interview, if I am taking to Retail investors is that unfortunately there are companies that I see that are really trying to solve the hardware problems, they might succeed, they might fail but they are really focused on solving the real problems and talking about it more or less honestly" - "and then there are companies that have focused on like marketing themselves to Retail investors and doing IPO's" i.e. the 4 public quantum computing companies IONQ, Rigetti, D-Wave and QUBT. - "and I see these 2 sets of companies being mostly disjoint from each other" - "So the companies that have focused on doing IPO's are actually not the ones that are in the lead on in the hardware, what they are in the lead on is selling a narrative to people...... - "convincing people this is already useful for solving problems in optimization and machine learning and finance, which sounds great to people, but all depends on you agreeing to not ask the question Q. well could a classical computer have done that just as well, could a classical computer actually have done that much faster and easier " "When people are talking about that the big use of a quantum computer is to solve optimization or machine learning problems or to turbo charge AI, or it can already do this, it's already delivering value to customers...." "these are the tells you are dealing with a SNAKEOIL SALESMAN" He calls out the "scammy" companies in this space! Remember the only 4 quantum pure play companies that have IPO'd are $IONQ $RGTI $QUBT $QBTS He also says earlier in the interview “I would say $IONQ has not demonstrated anything in trapped ion hardware close to what Quantinuum has demonstrated in the last year” YOU ARE BEING LIED TO! Full video in comments from the The Quantum Bull
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19,233 次观看 • 7 个月前

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We are announcing potpie AI $2.2M pre-seed fundraise to advance Spec-Driven Development for large enterprise codebases. The round is led by Emergent Ventures , with participation from All In Capital , DeVC , and PointOne Capital , along with the support of some amazing angel investors from companies including Atlassian, OpenAI, Meta, Razorpay and Flobiz. As AI accelerates code generation, the constraint inside large enterprises has shifted from coding to maintenance and assurance. The limiting factor is no longer writing code, but understanding complex systems, aligning teams around intent, and safely evolving large, interdependent codebases. In most organizations, specifications exist as static documents, while production systems evolve independently. Context is fragmented across repositories, tickets, logs, reviews, and floating documents making reliable AI adoption difficult. We are building the foundational layer that makes Spec-Driven Development executable at scale. By unifying engineering context and operationalizing the spec as a structured source of truth, we enable AI systems to reason with architectural awareness rather than surface-level code completion. We are already working with large enterprise customers, including Fortune 500 organizations. This milestone allows us to deepen those partnerships and support more teams transitioning from experimental AI usage to structured, production-grade AI-first engineering workflows. If you are leading engineering at scale and evaluating how AI should integrate into mission-critical systems, we would love to chat with you!
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We are announcing potpie AI $2.2M pre-seed fundraise to advance Spec-Driven Development for large enterprise codebases. The round is led by Emergent Ventures , with participation from All In Capital , DeVC , and PointOne Capital , along with the support of some amazing angel investors from companies including Atlassian, OpenAI, Meta, Razorpay and Flobiz. As AI accelerates code generation, the constraint inside large enterprises has shifted from coding to maintenance and assurance. The limiting factor is no longer writing code, but understanding complex systems, aligning teams around intent, and safely evolving large, interdependent codebases. In most organizations, specifications exist as static documents, while production systems evolve independently. Context is fragmented across repositories, tickets, logs, reviews, and floating documents making reliable AI adoption difficult. We are building the foundational layer that makes Spec-Driven Development executable at scale. By unifying engineering context and operationalizing the spec as a structured source of truth, we enable AI systems to reason with architectural awareness rather than surface-level code completion. We are already working with large enterprise customers, including Fortune 500 organizations. This milestone allows us to deepen those partnerships and support more teams transitioning from experimental AI usage to structured, production-grade AI-first engineering workflows. If you are leading engineering at scale and evaluating how AI should integrate into mission-critical systems, we would love to chat with you!

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Everyone is obsessing over AI models and cloud GPUs. But the next AI winners might be decided by something far less hyped: Mobile networks. At Mobile World Congress, I sat down with Peter Linder, Head of Thought Leadership at Ericsson to unpack why connectivity, not just compute, will determine who actually monetizes AI. Here’s what most leaders are missing… #MWC26 #EricssonMWC Ericsson Ambassador Ericsson N. America
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Everyone is obsessing over AI models and cloud GPUs. But the next AI winners might be decided by something far less hyped: Mobile networks. At Mobile World Congress, I sat down with Peter Linder, Head of Thought Leadership at Ericsson to unpack why connectivity, not just compute, will determine who actually monetizes AI. Here’s what most leaders are missing… #MWC26 #EricssonMWC Ericsson Ambassador Ericsson N. America

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11,263 次观看 • 6 个月前

For 20+ years, we've stayed ahead of every major shift in technology. Today we take the next one: we're introducing the world's first AI-native tech services model. Most of the industry is adding AI to the way it already works. Like bolting a copilot onto old processes and calling it transformation because it's faster than before. That's not what enterprises actually need. works differently. It provides instant access to AI Pods (service units run by AI agents and supervised by Globant experts) that deliver tech services at machine speed, but with the rigor, the governance, and the quality that enterprise-grade work demands. It is a smarter model, running the right AI through parallel agents, loops, workflows, and deterministic processes. With organizations access AI services with transparent, output or consumption-linked pricing, not per hour or per seat, and they own everything they produce. We are bringing the speed AI promises, with the rigor and quality any business needs. Join the waitlist at
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For 20+ years, we've stayed ahead of every major shift in technology. Today we take the next one: we're introducing the world's first AI-native tech services model. Most of the industry is adding AI to the way it already works. Like bolting a copilot onto old processes and calling it transformation because it's faster than before. That's not what enterprises actually need. works differently. It provides instant access to AI Pods (service units run by AI agents and supervised by Globant experts) that deliver tech services at machine speed, but with the rigor, the governance, and the quality that enterprise-grade work demands. It is a smarter model, running the right AI through parallel agents, loops, workflows, and deterministic processes. With organizations access AI services with transparent, output or consumption-linked pricing, not per hour or per seat, and they own everything they produce. We are bringing the speed AI promises, with the rigor and quality any business needs. Join the waitlist at

Martin Migoya

393,770 次观看 • 1 个月前

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🌐 Inside the Future of Global Finance Tokenization, settlement, ISO 20022 messaging, digital policy and the shift toward real institutional adoption. The transformation is happening faster than most people realize. We sat down with: • Andre Casterman — former Head of Corporate and Trade Markets at SWIFT and a leading figure in trade finance tokenization through ITFA and the XDC Network. • Arushi Goel — former Chainalysis policy lead and former digital currency lead at the World Economic Forum Together they break down: • How blockchain evolved from early experiments to today’s institutional era • Why stablecoins became the first real scaled tokenized asset • What ISO 20022 actually means for interoperability and financial messaging • How regulators in the US, EU, UAE and Asia are shaping digital asset policy • Public vs private infrastructure and where global institutions are really building • How AI, digital identity and DLT are converging • What tokenization could look like by 2030 as finance quietly goes on-chain If you want to understand where global markets and digital infrastructure are heading, this conversation is essential. Podcast powered by XDC Foundation

Generation Infinity

161,251 次观看 • 9 个月前

🇦🇲 Armenia launches one of the world’s most advanced AI data centers Armenia has officially joined the ranks of countries with their own artificial intelligence infrastructure. #EleveightAI has announced the launch of the #SouthCaucasus’ first AI Factory in the town of Gagarin, powered by #NVIDIA Blackwell B300 chips — one of the world’s most advanced architectures for generative AI. The project is now valued at up to $120 million for the first phase, significantly above the previously reported $70 million. The facility is designed to scale up to 35 MW of computing capacity and is considered supercomputing-class infrastructure. According to the company, Armenia has the potential to become a new global hub for #AI computing — an alternative location to the United States and Western #Europe. Among the advantages cited are lower energy costs, the availability of technical talent, and the region’s growing international connectivity. Eleveight AI CEO Arman Aleksanyan stated that the goal of the project is to transform Armenia from a consumer of AI into a country where AI is developed, trained, and deployed. The company is also considering future expansion into #CentralAsia'n and European markets. Twenty percent of the center’s computing capacity will be provided free of charge to Armenian universities, research institutions, and non-profit organizations. The project is already being described as part of a broader strategy to turn #Armenia into a regional technology and AI hub. As part of that strategy, another AI data center — developed by FireBird — is expected to launch in #Hrazdan, with planned investments of $500 million in the first phase and $4 billion in the second. NVIDIA Blackwell B300 chips are considered among the most advanced AI processors in the world and are designed for generative AI, supercomputing, and high-performance computing workloads. Access to such technology is subject to #US export-control regulations and is granted under strict licensing and compliance requirements. #IT #technology #MiddleEast #EU
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🇦🇲 Armenia launches one of the world’s most advanced AI data centers Armenia has officially joined the ranks of countries with their own artificial intelligence infrastructure. #EleveightAI has announced the launch of the #SouthCaucasus’ first AI Factory in the town of Gagarin, powered by #NVIDIA Blackwell B300 chips — one of the world’s most advanced architectures for generative AI. The project is now valued at up to $120 million for the first phase, significantly above the previously reported $70 million. The facility is designed to scale up to 35 MW of computing capacity and is considered supercomputing-class infrastructure. According to the company, Armenia has the potential to become a new global hub for #AI computing — an alternative location to the United States and Western #Europe. Among the advantages cited are lower energy costs, the availability of technical talent, and the region’s growing international connectivity. Eleveight AI CEO Arman Aleksanyan stated that the goal of the project is to transform Armenia from a consumer of AI into a country where AI is developed, trained, and deployed. The company is also considering future expansion into #CentralAsia'n and European markets. Twenty percent of the center’s computing capacity will be provided free of charge to Armenian universities, research institutions, and non-profit organizations. The project is already being described as part of a broader strategy to turn #Armenia into a regional technology and AI hub. As part of that strategy, another AI data center — developed by FireBird — is expected to launch in #Hrazdan, with planned investments of $500 million in the first phase and $4 billion in the second. NVIDIA Blackwell B300 chips are considered among the most advanced AI processors in the world and are designed for generative AI, supercomputing, and high-performance computing workloads. Access to such technology is subject to #US export-control regulations and is granted under strict licensing and compliance requirements. #IT #technology #MiddleEast #EU

Arthur Maghakian

63,985 次观看 • 3 个月前

🚀 SEALSQ $LAES at Times Square — Leading the Future of Quantum & AI Security! We’re proud to share that SEALSQ was featured today on the Nasdaq Tower in Times Square, announcing that our CEO Carlos Moreira will deliver the Opening Keynote at IQT Quantum + AI 2025, taking place October 19–21 in New York City. 🎤 Keynote: “AI Meets Quantum: Building Unbreakable Post-Quantum Security” Carlos will explore how AI and Quantum Computing are converging to redefine cybersecurity and shape the next era of digital trust. He will also join Panel 8: CEO Roundtable, alongside top executives from Rigetti, ORCA, SEEQC, and Arqit, to discuss the business and technology strategies driving the quantum revolution. 🔐 During the event, SEALSQ will present updates on its groundbreaking Quantum Shield “QS7001” — a RISC-V-based post-quantum secure hardware platform — and the progress of its Common Criteria EAL5+ certification with Serma Labs. The QS7001 platform integrates Kyber and Dilithium (NIST-standardized post-quantum algorithms) with advanced hardware accelerators for low-latency, high-throughput encryption, ensuring robust protection for IoT, automotive, healthcare, and critical infrastructure systems. 🌐 With this innovation, SEALSQ enables partners to future-proof devices against both classical and quantum attacks, ensuring compliance, efficiency, and trust in a rapidly evolving digital landscape. 💬 “Quantum and AI represent both opportunity and risk. With the Quantum Shield QS7001 platform and our broader post-quantum roadmap, SEALSQ is building the security foundation required to protect critical infrastructure, connected devices, and human data against the threats of tomorrow.” — Carlos Moreira, CEO, SEALSQ 📍 Event Details: 🗓️ October 19–21, 2025 📍 New York City 🎤 Opening Keynote: “AI Meets Quantum: Building Unbreakable Post-Quantum Security” 👤 Speaker: Carlos Moreira, CEO, SEALSQ 💼 Panel 8: CEO Roundtable featuring Rigetti, ORCA, SEEQC, Arqit, and SEALSQ #SEALSQ #PostQuantum #AI #QuantumComputing #Cybersecurity #TimesSquare #Nasdaq #IQT2025 #Innovation #RISC-V #Kyber #Dilithium #FutureOfSecurity
0:29

🚀 SEALSQ $LAES at Times Square — Leading the Future of Quantum & AI Security! We’re proud to share that SEALSQ was featured today on the Nasdaq Tower in Times Square, announcing that our CEO Carlos Moreira will deliver the Opening Keynote at IQT Quantum + AI 2025, taking place October 19–21 in New York City. 🎤 Keynote: “AI Meets Quantum: Building Unbreakable Post-Quantum Security” Carlos will explore how AI and Quantum Computing are converging to redefine cybersecurity and shape the next era of digital trust. He will also join Panel 8: CEO Roundtable, alongside top executives from Rigetti, ORCA, SEEQC, and Arqit, to discuss the business and technology strategies driving the quantum revolution. 🔐 During the event, SEALSQ will present updates on its groundbreaking Quantum Shield “QS7001” — a RISC-V-based post-quantum secure hardware platform — and the progress of its Common Criteria EAL5+ certification with Serma Labs. The QS7001 platform integrates Kyber and Dilithium (NIST-standardized post-quantum algorithms) with advanced hardware accelerators for low-latency, high-throughput encryption, ensuring robust protection for IoT, automotive, healthcare, and critical infrastructure systems. 🌐 With this innovation, SEALSQ enables partners to future-proof devices against both classical and quantum attacks, ensuring compliance, efficiency, and trust in a rapidly evolving digital landscape. 💬 “Quantum and AI represent both opportunity and risk. With the Quantum Shield QS7001 platform and our broader post-quantum roadmap, SEALSQ is building the security foundation required to protect critical infrastructure, connected devices, and human data against the threats of tomorrow.” — Carlos Moreira, CEO, SEALSQ 📍 Event Details: 🗓️ October 19–21, 2025 📍 New York City 🎤 Opening Keynote: “AI Meets Quantum: Building Unbreakable Post-Quantum Security” 👤 Speaker: Carlos Moreira, CEO, SEALSQ 💼 Panel 8: CEO Roundtable featuring Rigetti, ORCA, SEEQC, Arqit, and SEALSQ #SEALSQ #PostQuantum #AI #QuantumComputing #Cybersecurity #TimesSquare #Nasdaq #IQT2025 #Innovation #RISC-V #Kyber #Dilithium #FutureOfSecurity

Carlos Creus Moreira

12,991 次观看 • 11 个月前

NEW EP: Why AGI Will Happen This Decade with Emad Mostaque The AI revolution is here, but *actually* who controls the intelligence we'll all rely on? In today's episode, & Wayne Sim sit down with Emad of Intelligent Internet to cover: > Who Controls AI? > The Ghibli Effect by ChatGPT-4o > Why Most AI Models Are Inefficient > Universal Basic Intelligence > AI Atlantis: Economic Disruption & Rebirth > Credibly Neutral AI Infrastructure Full episode links below. Timestamps: 00:00 Intro 00:56 Mantle Ad 01:37 Ghibli AI Use 04:50 Replacing Humans with AI? 05:21 Artificial Remote Intelligence 10:14 Emad’s Opinion on Better AI Models 12:25 Concentration of Power with AI? 16:34 Training AI Models 20:46 Compute Demand Collapse? 27:00 Abundance of Open Source AI 30:04 Shift Towards Specialized Models 34:05 RedStone Ad 34:18 Frax Ad 34:44 Approaching Biases in AI 45:16 End of Original Thoughts? 50:30 Intelligent Internet & Reinforced Learning 59:07 Coordinating Incentives
1:05:59

NEW EP: Why AGI Will Happen This Decade with Emad Mostaque The AI revolution is here, but *actually* who controls the intelligence we'll all rely on? In today's episode, & Wayne Sim sit down with Emad of Intelligent Internet to cover: > Who Controls AI? > The Ghibli Effect by ChatGPT-4o > Why Most AI Models Are Inefficient > Universal Basic Intelligence > AI Atlantis: Economic Disruption & Rebirth > Credibly Neutral AI Infrastructure Full episode links below. Timestamps: 00:00 Intro 00:56 Mantle Ad 01:37 Ghibli AI Use 04:50 Replacing Humans with AI? 05:21 Artificial Remote Intelligence 10:14 Emad’s Opinion on Better AI Models 12:25 Concentration of Power with AI? 16:34 Training AI Models 20:46 Compute Demand Collapse? 27:00 Abundance of Open Source AI 30:04 Shift Towards Specialized Models 34:05 RedStone Ad 34:18 Frax Ad 34:44 Approaching Biases in AI 45:16 End of Original Thoughts? 50:30 Intelligent Internet & Reinforced Learning 59:07 Coordinating Incentives

The Rollup

32,804 次观看 • 1 年前

@kenzimori sits down with nick, Co-Founder of Allora, to unpack the early conviction that pulled him into crypto — not as a trend, but as a new way to rethink power, coordination, and how systems are built. Before founding Allora, Nick led blockchain development at a major asset manager and insurance firm across North America, during a time when most enterprises were still focused on private chains and consortiums. Instead, he pushed toward public Ethereum — building real enterprise use cases around decentralized insurance and trying to capture what actually made blockchain powerful. From those early experiments to the AI x crypto frontier, this conversation traces how Nick’s view of decentralized systems kept expanding.
4:05

@kenzimori sits down with nick, Co-Founder of Allora, to unpack the early conviction that pulled him into crypto — not as a trend, but as a new way to rethink power, coordination, and how systems are built. Before founding Allora, Nick led blockchain development at a major asset manager and insurance firm across North America, during a time when most enterprises were still focused on private chains and consortiums. Instead, he pushed toward public Ethereum — building real enterprise use cases around decentralized insurance and trying to capture what actually made blockchain powerful. From those early experiments to the AI x crypto frontier, this conversation traces how Nick’s view of decentralized systems kept expanding.

BeaconLayer Podcast

30,776 次观看 • 4 个月前

the IBM earnings reinforced something I think Wall Street is still underestimating: IBM is becoming an operating system for enterprise AI. The initial earnings reaction focused on the familiar metrics—revenue growth, infrastructure, margins and quarterly expectations. But that misses the bigger transformation underway. The AI market is bifurcating. On one side are companies building frontier models. On the other are companies helping enterprises operationalize AI—integrating it with existing systems and data, governing it, securing it, and turning AI into measurable business outcomes. IBM is increasingly positioning itself for that second market. And that's important because the enterprise AI conversation is moving from models to tools, from experimentation to outcomes, and ultimately toward autonomy and agents. IBM has decades of enterprise infrastructure, software, data and consulting relationships sitting underneath that transition. The mainframe isn't necessarily legacy in this world—it can become part of the context and transaction infrastructure AI acts upon. Wall Street initially looked at the quarter. I think the more important question is what IBM is becoming. My commentary below. #IBM #AI #EnterpriseAI #AgenticAI #HybridCloud
1:31

the IBM earnings reinforced something I think Wall Street is still underestimating: IBM is becoming an operating system for enterprise AI. The initial earnings reaction focused on the familiar metrics—revenue growth, infrastructure, margins and quarterly expectations. But that misses the bigger transformation underway. The AI market is bifurcating. On one side are companies building frontier models. On the other are companies helping enterprises operationalize AI—integrating it with existing systems and data, governing it, securing it, and turning AI into measurable business outcomes. IBM is increasingly positioning itself for that second market. And that's important because the enterprise AI conversation is moving from models to tools, from experimentation to outcomes, and ultimately toward autonomy and agents. IBM has decades of enterprise infrastructure, software, data and consulting relationships sitting underneath that transition. The mainframe isn't necessarily legacy in this world—it can become part of the context and transaction infrastructure AI acts upon. Wall Street initially looked at the quarter. I think the more important question is what IBM is becoming. My commentary below. #IBM #AI #EnterpriseAI #AgenticAI #HybridCloud

John Furrier

47,663 次观看 • 1 个月前

🚨$OSS is not an AI company. → It is the hardware that lets AI exist where the cloud cannot. Most investors don’t understand $OSS because they think AI = software. $OSS builds the physical “brains” that run AI in extreme environments where cloud computing fails. Jets. Ships. Tanks. Drones. Space. Hospitals. That’s the game. 1) What $OSS actually is $OSS (One Stop Systems) designs rugged high-performance computers and storage systems for AI at the edge. Meaning: They bring data-center-level computing power into harsh environments. Their products include rugged servers, GPU accelerators, storage arrays, and expansion systems used for AI, sensor processing, and autonomous systems. In simple terms: Cloud AI = brain in a safe building. $OSS AI = brain inside machines operating in chaos. 2) Why this is crucial Most AI today runs in data centers. But the future of AI is not in the cloud. It’s on: • autonomous vehicles • military systems • drones • ships • industrial machines • medical devices These systems cannot wait for the cloud. Latency, connectivity, security, and survival demand local AI. $OSS delivers “data-center performance at the edge” across land, sea, and air. Without companies like OSS, autonomous systems simply don’t work. 3) What OSS actually does: Think of OSS as building AI engines that survive reality. 🌊 SEA example: naval surveillance aircraft and ships. $OSS supplies rugged storage and compute systems for U.S. Navy reconnaissance aircraft to collect and process massive sensor data in real time. Translation: Instead of sending raw data back to base, the aircraft analyzes threats instantly onboard. $OSS = the onboard AI brain. 🪖 LAND example: military vehicles and tactical operations. $OSS delivers high-performance servers and FPGA systems for mobile military intelligence platforms used by the U.S. Department of Defense. Translation: Tanks and vehicles detect threats, process sensor data, and make decisions locally. $OSS = the battlefield computer. ✈️ AIR example: airborne AI. $OSS builds GPU-accelerated servers designed for aircraft, described as a “datacenter in the sky.” Translation: Jets and drones run AI models mid-flight. $OSS = flying supercomputers. 🚀 SPACE example: $OSS hardware is designed for extreme environments and autonomous systems across aerospace and defense. Translation: Future satellites, space drones, and autonomous spacecraft need onboard AI. $OSS = the computing core of autonomous space systems. BONUS: CIVILIAN & COMMERCIAL $OSS systems are used in: • autonomous trucking and farming • industrial automation • healthcare imaging • energy and mining • telecom and 5G Example:A medical imaging company uses $OSS hardware to run real-time AI diagnostics in next-gen breast cancer scanners. $OSS = AI where milliseconds matter. 4) Who their customers are (pattern, not names) $OSS sells to: • defense primes • government programs • industrial OEMs • AI infrastructure companies • medical device manufacturers These customers share one trait: They cannot rely on the cloud. That’s why $OSS exists. 5) The mental model that makes $OSS obvious $NVDA = AI chips $PLTR = AI software $OSS = AI hardware in the real world If AI is electricity, $OSS builds the generators that work in storms. Most investors understand AI software. Few understand AI infrastructure at the edge. That gap is the opportunity. 6) The real thesis The world is moving toward: • autonomous warfare • autonomous vehicles • real-time AI systems • distributed intelligence All of that requires rugged edge computing. $OSS is positioned exactly there. Infrastructure. The hardest layer to build. And often the most valuable.
0:51

🚨$OSS is not an AI company. → It is the hardware that lets AI exist where the cloud cannot. Most investors don’t understand $OSS because they think AI = software. $OSS builds the physical “brains” that run AI in extreme environments where cloud computing fails. Jets. Ships. Tanks. Drones. Space. Hospitals. That’s the game. 1) What $OSS actually is $OSS (One Stop Systems) designs rugged high-performance computers and storage systems for AI at the edge. Meaning: They bring data-center-level computing power into harsh environments. Their products include rugged servers, GPU accelerators, storage arrays, and expansion systems used for AI, sensor processing, and autonomous systems. In simple terms: Cloud AI = brain in a safe building. $OSS AI = brain inside machines operating in chaos. 2) Why this is crucial Most AI today runs in data centers. But the future of AI is not in the cloud. It’s on: • autonomous vehicles • military systems • drones • ships • industrial machines • medical devices These systems cannot wait for the cloud. Latency, connectivity, security, and survival demand local AI. $OSS delivers “data-center performance at the edge” across land, sea, and air. Without companies like OSS, autonomous systems simply don’t work. 3) What OSS actually does: Think of OSS as building AI engines that survive reality. 🌊 SEA example: naval surveillance aircraft and ships. $OSS supplies rugged storage and compute systems for U.S. Navy reconnaissance aircraft to collect and process massive sensor data in real time. Translation: Instead of sending raw data back to base, the aircraft analyzes threats instantly onboard. $OSS = the onboard AI brain. 🪖 LAND example: military vehicles and tactical operations. $OSS delivers high-performance servers and FPGA systems for mobile military intelligence platforms used by the U.S. Department of Defense. Translation: Tanks and vehicles detect threats, process sensor data, and make decisions locally. $OSS = the battlefield computer. ✈️ AIR example: airborne AI. $OSS builds GPU-accelerated servers designed for aircraft, described as a “datacenter in the sky.” Translation: Jets and drones run AI models mid-flight. $OSS = flying supercomputers. 🚀 SPACE example: $OSS hardware is designed for extreme environments and autonomous systems across aerospace and defense. Translation: Future satellites, space drones, and autonomous spacecraft need onboard AI. $OSS = the computing core of autonomous space systems. BONUS: CIVILIAN & COMMERCIAL $OSS systems are used in: • autonomous trucking and farming • industrial automation • healthcare imaging • energy and mining • telecom and 5G Example:A medical imaging company uses $OSS hardware to run real-time AI diagnostics in next-gen breast cancer scanners. $OSS = AI where milliseconds matter. 4) Who their customers are (pattern, not names) $OSS sells to: • defense primes • government programs • industrial OEMs • AI infrastructure companies • medical device manufacturers These customers share one trait: They cannot rely on the cloud. That’s why $OSS exists. 5) The mental model that makes $OSS obvious $NVDA = AI chips $PLTR = AI software $OSS = AI hardware in the real world If AI is electricity, $OSS builds the generators that work in storms. Most investors understand AI software. Few understand AI infrastructure at the edge. That gap is the opportunity. 6) The real thesis The world is moving toward: • autonomous warfare • autonomous vehicles • real-time AI systems • distributed intelligence All of that requires rugged edge computing. $OSS is positioned exactly there. Infrastructure. The hardest layer to build. And often the most valuable.

Black Panther Capital

30,138 次观看 • 7 个月前