Latest news with #NVIDIAInception
Forbes
13-06-2025
- Business
- Forbes
The Physical AI, Autonomous Systems And Robotics (PAI-ASR) Security Posture Management (SPM) Gap
Frank Jonas, Founder Fidelitas Defense (NVIDIA Inception & Microsoft Startups F.H.) | FBI (ret) | U.S. Marine Corps Vet getty In March 2024, the cybersecurity world was rattled when it was revealed that XZ Utils, a popular open-source software (OSS) compression utility used across Linux distributions, had been quietly backdoored by a sophisticated threat actor. Over two years, an attacker posing as a helpful contributor gained maintainership rights, gradually inserting malicious code designed to grant remote shell access to compromised systems. This wasn't just a supply chain breach; it was a proof of concept for a new era of cyber threat operations: long-term, not detected and buried deep in the dependencies that modern infrastructure relies on. Now imagine the same concept applied to the software stack of a surgical robot, an autonomous submarine or a port logistics AI system. In a world where Physical AI, Autonomous Systems and Robotics (PAI-ASR) often runs on stacks of OSS and pretrained models, the risks are greater than ever. We're no longer just talking about compromised servers—we're talking about compromised machines that make decisions in the physical world. In boardrooms across the Defense, Healthcare, Maritime, Manufacturing and Energy sectors, executives are rapidly considering, piloting or deploying PAI-ASR systems that promise revolutionary advancements in efficiencies. Yet many independent security teams are struggling with an uncomfortable truth: These sophisticated machines remain dangerously vulnerable to attacks that could transform innovations into significant business risk overnight. From automated cranes at global ports to select robotic procedures performed in operating rooms, we are witnessing a rapid and mass migration of AI into the physical world. PAI-ASRs are no longer niche or experimental. They're operational, essential and often invisible to the end user. Defense agencies rely on AI-enabled drones for intelligence, surveillance, reconnaissance (ISR) and precision strikes. Shipping giants use robotic systems to manage logistics throughout maritime and ports operations. Hospitals are increasingly integrating autonomous systems and robotics to enhance patient care and streamline operations. This is the promise of PAI-ASR: Machines that move, decide and scale. But the speed of innovation may be outpacing our ability to properly secure these systems from cyber and insider risks. PAI-ASR systems are often tested and built from a soup of vulnerable components: OSS libraries like OpenCV and Robot Operating System (ROS), low-level firmware, pretrained AI models scraped from the internet and sensors subject to spoofing. Each layer introduces unique threats: supply chain compromises, insider threats, model inversion attacks—even adversarial patches that trick AI vision systems into seeing stop signs as speed limits. A decade ago, in 2015, researchers at the University of Washington demonstrated how a surgical robot prototype could be compromised through network-based attacks, causing it to misbehave or shut down entirely. In real-world industrial environments, automation systems have been found exposed online, running unpatched Linux kernels with default credentials. In military settings, autonomous drones remain vulnerable to GPS spoofing and sensor manipulation. These aren't just IT risks; they're threats to operational integrity and physical safety. The OSS ecosystem has revolutionized robotics and AI, but not without risk. OSS libraries like OpenCV power everything from defect detection in manufacturing to perception in autonomous vehicles, medical imaging and surgical robotics. They're flexible, fast and free. But packages like OpenCV, at a reported 2-3 million lines of code, depending on the build, are sprawling with broad contributor access and are often poorly maintained and inconsistently secured. Worse, these open source packages are often deeply embedded in critical systems, where malicious code could cascade into real-world harm. Many PAI-ASR systems rely heavily on open source code written by volunteers or academic researchers who never thought their work would underpin military drones or surgical robots. There's often a lack of patch cadence and centralized oversight. Worse, many organizations don't understand or perform a risk assessment on the open source package's own software dependencies and imports. That's a hacker's dream: critical systems built on complex, unaudited code, operated by organizations unaware of their own dependencies, creating a perfect storm of exploitable vulnerabilities. Traditional IT security solutions weren't built for the unique challenges of PAI-ASR. When machines can move, make decisions and interact with the physical world, the SPM paradigm fundamentally changes. PAI-ASR SPM isn't just vulnerability scanning or regulatory and compliance auditing. It's a risk-driven, holistic, contextual understanding of PAI-ASR attack surfaces. PAI-ASR SPM methodologies, frameworks and platforms monitor and baseline the security state of PAI-ASR components, from low-level firmware to high-level decision logic. They identify drift in AI model performance. They detect anomalous behavior in PAI-ASR systems. They scan for source code vulnerabilities and dependency alerts in embedded code and verify that sensor inputs haven't been manipulated. Crucially, they do this continuously and not just once a year for a compliance checkbox. We're entering a decade of PAI-ASR critical infrastructure. Military and defense, healthcare and MedTech, maritime and Ports—all of them will depend on machines that make decisions humans don't directly control. If those machines are compromised, the results won't be confined to cyberspace. We're talking about hospital mishaps, disrupted logistics supply chains and negatively impacted defense capabilities. PAI-ASR SPM companies don't eliminate risk, but they can redefine how it's managed. These firms bring domain expertise, mission alignment, real-time visibility and operational resilience to one of the most complex engineering challenges of our time. We're engineering PAI-ASR systems at an unprecedented pace—machines that are faster and more autonomous than most could have imagined just a decade ago. But while their capabilities have evolved rapidly, our SPM paradigms haven't kept up. The next decade won't be defined by innovation alone but by whether we can properly secure and minimize risk to the confidentiality, integrity and availability of PAI-ASR systems. PAI-ASR SPM isn't a luxury. It is fundamentally necessary. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
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Business Standard
06-06-2025
- Business
- Business Standard
Andhra Pradesh government and Nvidia sign MoU to power AI University
The Government of Andhra Pradesh and Nvidia have entered into a Memorandum of Understanding (MoU) to jointly advance the establishment of a proposed Artificial Intelligence (AI) University and foster a robust AI ecosystem through skilling, research, infrastructure development, and startup acceleration. This collaboration is aimed at positioning Andhra Pradesh as a national leader in AI-driven innovation and talent development. As part of this partnership, the two parties will work together to skill 10,000 engineering students across Andhra Pradesh over the next two years. Nvidia will also provide curriculum guidance and technical training resources to support AI education and capacity building in engineering colleges across the state. In addition to workforce development, the MoU also focuses on enhancing research and development capabilities. Nvidia will support the identification and establishment of AI research centres that address pressing technological challenges and develop transformative solutions across sectors. Both parties will encourage joint research initiatives that contribute to the growth of AI knowledge and applications. Speaking on this development, Sh Nara Lokesh, Minister for IT, Government of Andhra Pradesh, said: 'This partnership with Nvidia marks a decisive step in our vision to position Andhra Pradesh as a national leader in artificial intelligence. By equipping 10,000 students with cutting-edge AI skills and supporting our startup ecosystem, we are laying the foundation for a future-ready economy driven by innovation, research, and entrepreneurship.' The collaboration will further extend to the development of advanced computational infrastructure required for the proposed AI University. Nvidia will assist in identifying the necessary tools, software platforms, and hardware capabilities to ensure the university is equipped to deliver world-class education and research outcomes. 'We are proud to collaborate with the Government of Andhra Pradesh in building a strong and inclusive AI ecosystem. This initiative reflects our commitment to democratising access to AI education, accelerating research, and enabling startups to innovate at scale. Together, we aim to create a model that can inspire similar efforts across the country,' said Vishal Dhupar, Managing Director, Asia South, Nvidia. Another key aspect of the MoU is the sharing of experience and best practices in establishing next-generation AI Factories. Nvidia will provide insights from its global expertise in operationalising AI Factories that serve as hubs for innovation, industry collaboration, and talent incubation aimed at democratisation of AI. The partnership also includes a strong focus on entrepreneurship. The Government of Andhra Pradesh intends to facilitate up to 500 AI-focused startups from the state in applying to the NVIDIA Inception programme during the term of this MoU, subject to the programme's eligibility criteria and availability. This initiative is expected to give a significant boost to the startup ecosystem in the region by providing emerging companies with access to Nvidia's global network, technical resources, and market opportunities. This MoU represents a significant milestone in Andhra Pradesh's ambition to become a hub for advanced AI research, education, and innovation. By combining the technological leadership of Nvidia with the vision of the Government of Andhra Pradesh, the initiative aims to build a sustainable and scalable AI ecosystem that delivers long-term economic and social value.
Business Wire
04-06-2025
- Business
- Business Wire
Accenture Helps High-Potential AI Startups Grow with Support from NVIDIA Inception
NEW YORK--(BUSINESS WIRE)--Accenture (NYSE: ACN) today announced expanded support for high-potential AI startups with a new engagement initiative, established through Accenture Ventures with support from NVIDIA Inception. This collaboration is designed to accelerate startup growth and innovation by closing a common gap many early-stage companies face—moving from breakthrough ideas to scalable enterprise solutions. The initiative will provide startups with market intelligence, technical workshops, enterprise workflow knowledge and exposure to real-world business environments. Startups will gain access to Accenture's deep industry experience and enterprise relationships, as well as emerging technology resources across Accenture Innovation's global network. Combined with NVIDIA's advanced technical capabilities and global developer ecosystem, this initiative will provide a powerful launchpad for the next generation of AI innovators. 'AI is reshaping industries at a breakneck pace, but many startups struggle to bridge the gap between innovation and enterprise-ready solutions,' said Tom Lounibos, global lead for Accenture Ventures. 'Through this collaboration, we're creating an environment where these companies can turn fresh ideas into reality—faster, smarter and with the right strategic backing.' Accenture Ventures and NVIDIA Inception will bring together world-class technical, commercial, and strategic support, and access to NVIDIA's extensive venture capital network. This will help AI startups rapidly adapt and refine solutions to achieve enterprise readiness and deliver meaningful impact in the market. 'The startup ecosystem drives technological innovation across all sectors, from customer experience to healthcare,' said Howard Wright, vice president of startup ecosystem at NVIDIA. 'NVIDIA Inception working together with Accenture Ventures will help startups accelerate their impact on every industry powered by AI.' Initial focus on marketing and customer experience The first phase of this initiative will focus on startups in the areas of marketing, sales, and customer service, where AI is reinventing how businesses connect with customers through data-driven insights, personalized content, and immersive experiences. Startups will be able to tap into marketing and customer domain expertise from Accenture Song's tech-powered creative group. Today's announcement highlights Accenture's ongoing investment in data and AI capabilities to help clients grow their business and sustain relevance with customers. It expands on the Accenture NVIDIA Business Group, launched last year to help clients rapidly scale AI adoption, including agentic AI systems, to drive new levels of productivity and growth. For instance, Accenture's AI Refinery™, built with NVIDIA AI Enterprise software, help companies turn raw AI technology into useful business solutions. About Accenture Accenture is a leading global professional services company that helps the world's leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 801,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world's leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at
TECHx
17-04-2025
- Business
- TECHx
SandboxAQ Advances AI Research with NVIDIA DGX Collaboration
SandboxAQ has announced a collaboration with NVIDIA to drive faster innovation across industries. The company is leveraging the power of NVIDIA DGX to build advanced AI models that support breakthroughs in biopharma, chemicals, materials, finance, cybersecurity, navigation, and medical imaging. As a member of the NVIDIA Inception program, SandboxAQ is developing a next-generation Large Quantitative Model (LQM) platform. Built on NVIDIA DGX, this platform is designed to solve complex scientific and business problems with more speed, scale, and precision. With this collaboration, SandboxAQ is improving customer outcomes across several areas. First, drug, chemical, and materials development is becoming faster. Using NVIDIA DGX, SandboxAQ can reduce discovery cycles from years to weeks. This is done through simulations that replace slow lab experiments, helping teams test and validate new ideas quickly. Second, the partnership enables the creation of high-quality scientific datasets. By combining chemical and biological simulations, SandboxAQ can detect interactions that were previously hard to identify. These datasets improve model accuracy and reduce false positives. Third, a new AI Chemist powered by LQMs and NVIDIA DGX is transforming how discoveries are made. This tool can explore millions of chemical pathways automatically, allowing researchers to find new molecules and optimize compounds more efficiently. The collaboration builds on earlier success. In 2024, the companies achieved an 80x acceleration in quantum chemistry calculations using CUDA-accelerated DMRG. In 2025, they published research showing orbital optimization on a system with 82 electrons and 82 orbitals—double the size of previous simulations. This joint effort has broad impact. In healthcare, SandboxAQ helps pharma companies speed up preclinical testing. In materials science, it supports the development of sustainable processes and energy storage. In cybersecurity, it enables better modeling and prediction. The core advantage lies in SandboxAQ's LQMs. These AI models reflect the laws of science and economics. They provide deterministic and reliable outputs, unlike general-purpose AI models. This makes them ideal for high-stakes environments. According to Jack Hidary, CEO of SandboxAQ, the collaboration gives customers a clear advantage. 'By building on NVIDIA DGX, we help our customers innovate faster and lead with confidence,' he said. Alexis Bjorlin, Vice President of NVIDIA DGX Cloud, added, 'SandboxAQ is setting new standards in AI-native science. With NVIDIA DGX, they can deliver performance at scale and solve real-world problems.' This partnership highlights how advanced AI and high-performance computing are reshaping R&D. With NVIDIA DGX, SandboxAQ is unlocking new levels of discovery and impact across industries.
Channel Post MEA
16-04-2025
- Business
- Channel Post MEA
SandboxAQ Leverages NVIDIA DGX Cloud To Fuel Scientific Discovery
SandboxAQ has announced a collaboration with NVIDIA to accelerate breakthrough innovations across biopharma, chemicals, advanced materials, financial services, cybersecurity, navigation, and medical imaging. SandboxAQ, a member of the NVIDIA Inception program, is leveraging the NVIDIA DGX Cloud AI platform on Google Cloud to build a state-of-the-art Large Quantitative Model (LQM) platform, fueling AI-driven scientific discovery. SandboxAQ is now uniquely positioned to help customers tackle the most complex and consequential business challenges through its LQMs – delivering breakthroughs where traditional models have fallen short – while offering unparalleled speed, scalability, and precision. This collaboration enables SandboxAQ to unlock critical breakthroughs specifically designed to transform customer outcomes, including: Up to 4x Faster Discovery Across Drug, Chemical, and Materials Pipelines: Accelerated by NVIDIA DGX Cloud, SandboxAQ replaces slow, resource-intensive design-make-test cycles with high-performance, equation-based simulations – reducing discovery timelines from months to weeks. Enhanced modeling capabilities support simultaneous optimization across multiple parameters, enabling faster validation of promising candidates and accelerating breakthroughs with greater confidence. Accelerated by NVIDIA DGX Cloud, SandboxAQ replaces slow, resource-intensive design-make-test cycles with high-performance, equation-based simulations – reducing discovery timelines from months to weeks. Enhanced modeling capabilities support simultaneous optimization across multiple parameters, enabling faster validation of promising candidates and accelerating breakthroughs with greater confidence. Breakthrough Datasets, Curated with DGX Cloud: SandboxAQ is generating high-fidelity scientific datasets, combining chemical and biological simulations. These methods leverage equation-based LQM models to reveal interactions between small molecules and complex biological targets that were previously difficult to detect including conformer libraries for generative chemistry and synthetic affinity data for training predictive models. By powering causal knowledge graphs and more accurate molecular design, these datasets reduce false positives and improve success rates across the R&D pipeline. SandboxAQ is generating high-fidelity scientific datasets, combining chemical and biological simulations. These methods leverage equation-based LQM models to reveal interactions between small molecules and complex biological targets that were previously difficult to detect including conformer libraries for generative chemistry and synthetic affinity data for training predictive models. By powering causal knowledge graphs and more accurate molecular design, these datasets reduce false positives and improve success rates across the R&D pipeline. Agentic AI Chemist – A New Era of Autonomous Discovery: SandboxAQ's AI Chemist combines and orchestrates multiple LQMs to transform the scale of the research and development process. It autonomously explores millions of potential chemical pathways, far beyond what a human chemist could evaluate, enabling the discovery of novel molecules and the optimization of compounds for clinical and scale up success. Research Breakthroughs Today's announcement builds on previous collaboration between SandboxAQ and NVIDIA: 2024 Breakthrough : SandboxAQ and NVIDIA achieved an 80x acceleration in quantum chemistry calculations using CUDA-accelerated Density Matrix Renormalization Group (DMRG), enabling accurate simulation of enzyme active sites and complex catalysts previously impossible due to computational limitations. : SandboxAQ and NVIDIA achieved an using CUDA-accelerated Density Matrix Renormalization Group (DMRG), enabling accurate simulation of enzyme active sites and complex catalysts previously impossible due to computational limitations. 2025 Breakthrough : In the newly published joint research paper, 'Orbital Optimization of Large Active Spaces via AI-Accelerators,' for the first time, researchers successfully performed orbital optimization on a system with 82 electrons in 82 orbitals – more than doubling the size of simulations compared to previous works. This groundbreaking advance for GPU accelerated quantum chemistry calculations pushes the capabilities for molecular simulations into a regime that has thus far been entirely out of reach, with potentially far-reaching implications in catalysis, material science and high-dimensional parameter optimization. Transformative Impact Across Key Customer Domains SandboxAQ's enhanced capabilities deliver strategic outcomes across customer innovation and critical workflows: Biopharma and Healthcare : Proven track record of accelerating preclinical pipelines for pharma companies by rapidly generating and optimizing therapeutic candidates based on significantly improved predictability of drug efficacy and safety. : Proven track record of accelerating preclinical pipelines for pharma companies by rapidly generating and optimizing therapeutic candidates based on significantly improved predictability of drug efficacy and safety. Chemicals and Materials : Enabling deeper, faster exploration and validation of sustainable chemical processes to unlock carbon and hydrogen utilization as well as next-generation energy storage technologies. : Enabling deeper, faster exploration and validation of sustainable chemical processes to unlock carbon and hydrogen utilization as well as next-generation energy storage technologies. Cybersecurity and Strategic Infrastructure: Leveraging advanced modeling and predictive capabilities to enhance agility, strengthen resilience, and support proactive cybersecurity postures. Pioneering How Organizations Can Effectively Leverage AI SandboxAQ is pioneering a new category of enterprise AI through its proprietary Large Quantitative Models (LQMs), a platform specifically engineered to solve massively complex, high-stakes problems where precision and deterministic outputs are critical. Unlike generalized frontier models, SandboxAQ's LQMs are designed to reflect the underlying laws of physics, chemistry, biology, and economics – enabling outcomes that are not just predictive, but scientifically reliable. In fields like drug discovery, SandboxAQ trains LQMs on high-fidelity, domain-specific datasets to dramatically improve accuracy, reduce false positives, and accelerate the path from hypothesis to therapeutic insight. This focus on scientifically grounded, application-specific modeling sets SandboxAQ apart, empowering organizations to unlock value in areas where conventional AI simply cannot deliver. 'Our expanded work with NVIDIA accelerates our customers' ability to innovate and lead in their fields,' said Jack Hidary , CEO of SandboxAQ. 'By developing our platform on NVIDIA DGX Cloud and continuing our research collaboration, SandboxAQ will deliver a level of performance and insight that gives our customers a clear edge in accelerating innovation.' 'SandboxAQ is pushing the boundaries of AI-native science,' said Alexis Bjorlin , Vice President of NVIDIA DGX Cloud. 'NVIDIA DGX Cloud provides an AI development platform with essential scale and optimized application performance, empowering SandboxAQ to deliver cutting-edge capabilities and drive real-world impact for organizations tackling society's most critical challenges.' 0 0
