Reimagining biodefense at the intersection of AI, biology and urgency.
Updated
January 8, 2026 6:34 PM
Through computational tools, Valthos analyzes biological data to design adaptive solutions against emerging threats. PHOTO: VALTHOS
Valthos has raised US$30 million in seed funding, led by the OpenAI Startup Fund, Lux Capital and Founders Fund, to advance its mission of building next-generation biodefense systems.
The company’s work comes at a time when biotechnology is evolving at an unprecedented pace. Biotechnology is moving at record speed. These new tools can lead to life-changing medical discoveries, but they also bring the risk of dangerous biological agents being developed faster than ever.
“The issue at the core of biodefense is asymmetry”, said Kathleen McMahon, co-founder of Valthos. “It’s easier to make a pathogen than a cure. We’re building tools to help experts at the frontlines of biodefense move as fast as the threats they face”. The gap Valthos aims to close is between the rapid rise of biological threats and the slower pace of developing cures. Therefore, the company is developing AI systems that can rapidly analyze biological sequences and significantly shorten the time needed to design medical countermeasures.
“In this new world, the only way forward is to be faster. So we set out to build a new tech stack for biodefense”, said Tess van Stekelenburg, co-founder of Valthos. “This software infrastructure strengthens biodefense today and lays the groundwork for the adaptive, precision therapeutics of tomorrow”.
The company was founded by van Stekelenburg, a partner at Lux Capital and McMahon, the former head of Palantir’s Life Sciences division. Together, they’ve built a multidisciplinary team of experts from Palantir, DeepMind, Stanford’s Arc Institute and MIT’s Broad Institute, bringing together deep experience in software engineering, machine learning and biotechnology.
“Technology is moving fast. An industrial ecosystem of builders, companies and solutions further democratizes AI to provide broad resilience, and ensures the U.S. continues to lead as AI increasingly powers everything around us. As AI and biotech rapidly advance, biodefense is one of the new industry verticals that helps maximize the benefits and minimize the risks”, said Jason Kwon, OpenAI’s Chief Strategy Officer. “Valthos is pushing the frontier of protection and defense in one of the most strategic intersections of multiple world-changing technologies, and with the team to do it”.
Looking ahead, Valthos plans to expand its engineering team and scale its software infrastructure for both government and commercial partners — moving closer to its goal of enabling faster, smarter and more adaptive biodefense capabilities.
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AI growth is increasingly becoming a manufacturing, packaging and deployment challenge — not just a computing one.
Updated
May 26, 2026 5:28 PM
Taipei 101 and Taipei Nan Shan Plaza, viewed from Elephant Mountain. PHOTO: UNSPLASH
As AI companies continue scaling larger models and data centers, the pressure is no longer falling only on chip design. Manufacturing capacity, advanced packaging and infrastructure deployment are becoming equally important parts of the AI race. AMD’s latest investment announcement reflects how quickly that shift is accelerating.
The US chipmaker announced plans to invest more than US$10 billion across Taiwan’s semiconductor and manufacturing ecosystem to support next-generation AI infrastructure. The investment focuses on expanding partnerships and increasing advanced packaging capacity needed for future AI systems.
The announcement highlights a growing reality across the AI industry. Building powerful AI chips is no longer enough on its own. Companies now also need the manufacturing networks, packaging technologies and supply chain coordination required to deploy AI infrastructure at global scale.
AMD’s investments center heavily around advanced chip packaging, an area becoming increasingly critical as AI systems demand higher performance and greater power efficiency. Traditional chip architectures are struggling to keep pace with the size and complexity of modern AI workloads. Advanced packaging helps connect processors, memory and computing systems more efficiently while managing power and cooling limitations inside large-scale AI environments.
The company said it is working with Taiwan-based partners including ASE, SPIL and PTI to develop next-generation packaging technologies for its upcoming 6th Gen AMD EPYC processors, codenamed “Venice.” AMD also said it had qualified what it described as the industry’s first 2.5D panel-based EFB interconnect technology alongside PTI.
At the center of the broader strategy is AMD Helios, the company’s rack-scale AI infrastructure platform scheduled for deployment beginning in the second half of 2026. The platform combines AMD Instinct MI450X GPUs, 6th Gen EPYC CPUs, networking systems and AMD’s ROCm software stack into integrated AI infrastructure systems designed for hyperscale deployment.
Rather than selling individual processors alone, companies are increasingly building complete AI infrastructure platforms that combine hardware, software, cooling systems and power management into unified deployments. That transition is reshaping how AI infrastructure is designed, manufactured and delivered.
Taiwan is also becoming more deeply embedded in that process. AMD’s investment spans not only semiconductor packaging companies but also manufacturing and system integration partners including Sanmina, Wiwynn, Wistron and Inventec. The partnerships reflect Taiwan’s growing role as one of the operational centers of the global AI infrastructure economy.
Dr. Lisa Su, Chair and CEO of AMD, said: “As AI adoption accelerates, our global customers are rapidly scaling AI infrastructure to meet growing compute demand. By combining AMD leadership in high-performance computing with the Taiwan ecosystem and our strategic global partners, we are enabling integrated, rack-scale AI infrastructure that helps customers accelerate deployment of next-generation AI systems”.
Power efficiency is becoming another major challenge shaping AI infrastructure decisions. As AI workloads consume more electricity and generate more heat, infrastructure providers are increasingly being forced to rethink cooling systems, interconnect technologies and deployment economics.
AMD’s announcement signals how the AI competition is evolving beyond model development and raw computing power. The next stage may depend just as heavily on who can manufacture, package and deploy AI infrastructure fast enough to support global demand.