Generative AI in Healthcare: A Challenge for Computer Scientists

Want an edge in the new data era? Start where AI, HPC, and Quantum intersect. Paul Bloch, co-founder and president of DDN, brings a global perspective on digital transformation and the evolution of AI Infrastructure. He will explore how data, AI, and supercomputing are redefining innovation across scientific research, industry, and digital technology, outlining key challenges and opportunities. Get the agenda, speakers, and registration details to see what you can implement now and where AI Infrastructure is headed: bit.ly/4gxxKAN E4 Computer Engineering

A new method helps researchers steer generative AI models to design breakthrough materials for quantum computing and other applications. “We don’t need 10 million new materials to change the world. We just need one really good material,” Mingda Li says. https://lnkd.in/e96btvDM

Artificial intelligence is consuming enormous amounts of energy, but researchers at the University of Florida have built a chip that could change everything by using light instead of electricity for a core AI function. By etching microscopic lenses directly onto silicon, they’ve enabled laser-powered computations that cut power use dramatically while maintaining near-perfect accuracy. https://lnkd.in/e-NvWf_V

Silicon Meets Synapse: The Rise of Neuromorphic Computing These aren’t your average processors — they think, learn, and adapt like the human brain. Neuromorphic chips fire like neurons, making AI faster, smarter, and more energy-efficient. The future of computing isn’t digital… it’s biological.

Silicon Meets Synapse: The Rise of Neuromorphic Computing These aren’t your average processors — they think, learn, and adapt like the human brain. Neuromorphic chips fire like neurons, making AI faster, smarter, and more energy-efficient. The future of computing isn’t digital… it’s biological.

Last year, I sat down with Brian Greene at World Science Festival to talk about AI and quantum computing. At the time, I said these technologies were moving faster than most of us expected. Today, that feels even more true and more urgent. A few themes stand out from that conversation: 🔹 Democracy is at risk. When AI-generated images and videos are indistinguishable from reality, misinformation can undermine and erode trust. We need authentication and strong safeguards before this becomes an existential problem. 🔹 Safety must come first. Current systems already show the capacity to enable cyber or biological attacks. Industry and government need to work together to ensure this technology stays in the right hands. 🔹 Education and healthcare can be transformed. AI can expand access to education and healthcare. Imagine an AI tutor or doctor in every pocket that is free, personalized, and available anywhere in the world, changing the trajectory of billions of lives. 🔹 Innovation will be democratized. We’re heading toward a world where anyone can say “build this for me” and AI will assemble the tools, code, or simulations. That changes not just what we build, but who gets to build. 🔹 Classical computing is nearing its limits. As we hit physical boundaries in chip design, advances in 3D packaging and breakthroughs in quantum computing will define the next era. 🔹 The opportunity is extraordinary. AI can double productivity, quantum can open new frontiers of discovery, and together they can expand human potential. But we can’t be passive observers. We need to shape these technologies responsibly or risk weakening the very systems that hold society together. #ArtificialIntelligence #QuantumComputing https://lnkd.in/eNGysij7

The Department of Computer Science at North Dakota State University, led by Jeremy Straub, has an innovative gradient descent training method that revolutionizes AI by optimizing network structures for enhanced transparency and reliability. This cutting-edge technology identifies and weights rules and facts, ensuring every decision point is auditable and understandable. This technology has a U.S. Patent Pending US2023/0281/452A1 (https://lnkd.in/gq9dbvzK) and is available for licensing/partnering opportunities. To learn more: https://lnkd.in/gVur2dCg. #AI #Transparency #Reliability #Scalability #NDSUResearch

What's the biggest misconception about quantum computing? It's not a magic bullet. Quantum computing excels at solving problems currently beyond classical computers, particularly NP-hard problems. While AI might see some speed improvements, the real quantum leap will be in tackling computationally difficult problems that would otherwise take eons to solve. It's about speed, not magic. #quantumcomputing #NP hard #AI #innovation #technology

One of the biggest misconceptions about quantum computing? That it’s some kind of magical solution for everything. In reality, quantum computers aren’t replacing classical systems—they're complementing them. Their real strength lies in solving complex, computationally intensive problems, especially NP-hard ones, that classical machines struggle with. While AI may benefit from faster processing in specific cases, the true game-changer is quantum’s potential to tackle problems that would otherwise take centuries to compute. It’s not about magic. It’s about speed, scale, and solving what was previously unsolvable. #quantumcomputing #NPhard #AI #innovation #technology