EU Research’s Post

I see a lot of misunderstanding about what AI agents are and how they are very different from anything we have seen before. This exciting breakthrough in AI for scientific research by Prof. James Zou and the team at Stanford University demonstrates the great potential and begins to outline some best practices and effective approaches. "Virtual Lab" is a multi-agent AI system that's changes the way we approach scientific discovery together with AI agents. My key insights: 📊 Virtual Lab represents a paradigm shift from AI as a tool to AI as a research partner. It creates teams of specialized AI agents (like computational biologists, ML specialists, and immunologists) led by an AI "professor" agent. 🧪 Real-world impact: The team demonstrated Virtual Lab's capabilities by designing novel nanobodies that can bind to both recent and original SARS-CoV-2 variants - a novel approach to therapeutic development. 💡 What makes Virtual Lab unique: - Agents hold both group meetings and one-on-one sessions to tackle complex research problems - Multiple parallel meetings explore diverse solutions simultaneously - AI agents write their own code and develop innovative research workflows - The system combines multiple sophisticated tools (ESM, AlphaFold, Rosetta) in novel ways 🤝 The human role shifts to providing high-level guidance and experimental validation, while AI agents handle the detailed computational work and creative problem-solving. 🎯 Most impressive: Virtual Lab's nanobody designs showed promising binding profiles across diverse virus variants in real laboratory tests - from the original Wuhan strain to recent JN.1 variant. This research opens exciting possibilities for accelerating scientific discovery across multiple domains. Virtual Lab could be adapted for fields like finance, education, and climate science, potentially revolutionizing how we approach R&D. Watch the video for more detailed explanations. Research paper link in comments. https://lnkd.in/dDHEPgxF #AIAgents #ArtificialIntelligence #ScientificResearch #Innovation #BioTech #AI #Research #Stanford #DrugDiscovery

Students have released the seventh edition of the school's science magazine Catalyst. This edition, entitled The Next 100 years, covers a variety of topics including the use of hydrogen, bacteriophage treatments, generative AI in drug discovery, the future of architecture and much more. The student editors write: 'This year’s Catalyst reflects the continuing expansion of the frontiers of science. However, it also highlights the importance of being cognisant of the implications all these scientific breakthroughs bring. Therefore, in the next 100 years, the heart of the scientific drive shouldn’t just consist of curiosity and resilience, but consideration of consequences.' Read the latest edition here: https://joom.ag/UNud

Today, I published Integration and Refinement of Digital Physics, Unifying Quantum and Classical with a Calculation: A Formal Approach to Subparticles and Discrete Universe Frames - happy to take opinions! In a world where the consciousness is questioned, are we the mouse, the AI, or the construct of will? Will the discrete universe allow us to do our own bidding, or is it guiding us in the path towards escape? https://lnkd.in/drN-fbum

This is just wild! I was reading through this paper from Scientific American about new AI Advances and... just WOW. Here is my quick summarization of the article: "Researchers are breaking new ground by creating "living computers" using human brain cells, merging biology and AI in ways never seen before. These innovative systems integrate human neurons with artificial intelligence, offering the potential to learn and adapt far beyond the capabilities of traditional silicon-based computers. The technology uses organoids—clusters of human brain cells—that can operate and process data for up to 100 days. AI models are trained using dopamine and electrical signals, mimicking natural brain functions. FinalSpark claims these biocomputers could be up to 100,000 times more efficient for AI training than current technologies. Plus, the organoids' activity is live-streamed 24/7 for real-time observation. It’s both fascinating and surreal to see human brain cells contributing to the future of AI!" Let me know what you all think! I feel like we are moving towards the reality of a Sci-Fi novel. For the full details, please explore the full article: https://lnkd.in/eQ_KD6ZR #AI #Neuroscience #TechInnovation #FutureOfComputing #Biotechnology #LivingComputers #ArtificialIntelligence #NeuralComputing #InnovativeTech #AdvancedTechnology #Bioengineering #AIResearch #CuttingEdgeTech #FutureTech #ComputationalBiology #HumanMachineInterface #EmergingTech #TechRevolution

ResearchGate and Tsinghua University Press (TUP) have launched a groundbreaking partnership to boost the global visibility of TUP's open-access journals. Over 2,000 articles in fields like AI, energy, materials, and construction will now reach ResearchGate's community of more than 25 million users, expanding readership and author engagement.

Science Sanvaad is made by students of DYPIU. In this episode, they have covered Prof Prabhat Ranjan talking about how he makes AI generated songs. It also covers pioneering effort of DYPIU to launch BTech Semiconductor Engg course. #AI #aivoice #generativeai #GenAI #dypiu #prabhatranjan #semiconductorindustry #Semiconductors

“Science within academia is easier, translating that science into the real world is a hundred times harder.” At #Pendulum, we believe artificial intelligence technologies should not exist in a vacuum. We’ve spent a decade developing ours to have a tangible impact throughout some of the most critical supply chains across the globe. Watch Chief Scientific Officer and Co-Founder Dr. Suvrit Sra explain how in this video by the Alexander von Humboldt Foundation: https://lnkd.in/eyXvyX6q

🔬 A Look at DENDRAL: Pioneer of Expert Systems in Chemistry Did you know that one of the first expert systems in AI history was developed in 1965 by two brilliant Stanford University scientists? DENDRAL, the result of collaboration between Edward Feigenbaum (AI researcher) and Joshua Lederberg (geneticist), revolutionized chemical analysis and paved the way for modern expert systems. 💡 Key Features: ✔️ Ability to analyze complex compounds of carbon, hydrogen, and nitrogen ✔️ Utilization of spectrographic data for molecular structure analysis ✔️ Performance rivaling expert chemists ✔️ Widespread application in industry and academia This expert system wasn’t just a technical achievement - it was a breakthrough that laid the foundation for modern expert systems development. #ArtificialIntelligence #ExpertSystems #Chemistry #Innovation #Technology 📚 Recommended Reading: “DENDRAL: A Case Study of the First Expert System for Scientific Hypothesis Formation” by Edward A. Feigenbaum and Bruce G. Buchanan Published in Artificial Intelligence Journal DOI: 10.1016/0004-3702(93)90015-4 https://lnkd.in/e3YMMDg5 This paper provides an in-depth look at DENDRAL’s development history, system architecture, and its impact on expert systems development.

Crafting a unique and promising research hypothesis is a fundamental skill for any scientist. It can also be time consuming: New PhD candidates might spend the first year of their program trying to decide exactly what to explore in their experiments. What if artificial intelligence could help?MIT researchers have created a way to autonomously generate and evaluate promising research hypotheses across fields, through human-AI collaboration. In a new paper, they describe how they used this framework to create evidence-driven hypotheses that align with unmet research needs in the field of biologically inspired materials.Published Wednesday in Advanced Materials, the study was co-authored ...