Dan Spellman’s Post

Nvidia Clara for Biopharma looks very interesting. Clara is a a collection of frameworks, applications, generative AI solutions, and pretrained models. NVIDIA BioNeMo is a generative AI platform for drug discovery that simplifies and accelerates the training of models using your own data and scaling the deployment of models for drug discovery applications. It contains AI models for predicting protein and small-molecule properties (ESM-1, ESM-2, MegaMolBART, MoFlow), protein generation (ProtGPT2), pose prediction (DiffDock), and 3D protein structure prediction (OpenFold, AphaFold2, ESMFold). BioNeMo microservices, including BioNeMo Cloud APIs for rapid access to optimized biomolecular AI models, enable users to effortlessly harness generative AI for drug discovery applications. https://lnkd.in/emyAgTbZ Using Generative AI to Enhance Biologics Discovery - Success Story by Amgen https://lnkd.in/eExS6zYZ

A warning about LLM and AI from German government: https://lnkd.in/gMDaGDij Yes. Regulation and validation/verification (V&V) are critical. For example, nuclear tests were to V&V atomic bomb models. An UN newly released report said that AI ONLY benefits small amount of states, companies and individuals, i.e., some few humans are making big money by using AI to harm many people. AI is based on math models, and models must be V&V before we can trust them. Using math models to simulate a physical process started from the Manhattan Project in WWII for nuclear bomb design. Then, in 1960s, it came the C4ISR, which is today's AI, whose original missions were just breaching enemy's security, dis-/mis-information, cognitive manipulation, cheat, surveillance, detection for kill, etc.. In our reality, AI causes expensive electricity bills to a C-level friend of ours. 😔 😥 😿 AI can do many things, but NOT everything, at least NOT what we are doing, by using our intellectual property (IP), a copyrighted multilingual metadata. Without metadata, NO data can be found/retrieved, even by AI. https://lnkd.in/g-aJFnXR

Yes, now we have a good way to transmit/process data by using such advanced technologies, but we need more human inputs. Please try this fact-check question of AI-IP: "Is there any today's data technology/solution you know, that can interpret and answer the following fundamental and realistic Chinese-English multilingual questions of BI?" With our intellectualproperty (IP), a copyrighted multilingual metadata, we can provide real time answers for policy/decision making, withevidence. "Who, in the Ontario province of Canada, has new US patents granted on the nearest Tuesday, when the USPTO releases the newly granted US patents on a weekly basis?" "Who, in the "江蘇‘’ province of China, has new US patents granted on the nearest Tuesday, when the USPTO releases the newly granted US patents on a weekly basis?" Metadata is an enabler, whose purpose is to help us find the data we want. Without metadata, NO data can be found/retrieved, even by the most advanced technologies, like AI, NVIDIA chips, supercomputers, etc. https://lnkd.in/g-aJFnXR Our IP can also make your data service UNIQUE globally. Do you or any of your contacts need our expertise/IP?

As Kimberly Powell puts it - Generative AI is poised to impact healthcare more profoundly than ANY other area of life. Everything from accelerating drug discovery to enhancing patient diagnostics and postoperative care is on the table. The only roadblock in front of us is the speed and efficiency with which we can implement AI on scale. Could Nvidia be the answer to these teething issues? #AIHealthcare #Healthcare #NvidiaAI #GenerativeAI #MedicalInnovation

Interesting article that provides an interesting synopsis of the many ways that Nvidia has begun to explore AI applications in healthcare

Generative artificial intelligence (AI) is spearheading a significant shift in the healthcare sector, as highlighted by Kimberly Powell, vice president of healthcare at NVIDIA. According to Powell, AI is positioned to revolutionize pharmaceutical research, patient diagnostics, and post-operative treatment, marking the beginning of a healthcare transformation. She emphasized the profound impact AI is poised to have on healthcare, stating that it is likely to be the most influential application of generative AI. The insights shared at Nvidia's AI Summit shed light on the potential of AI to shape the future of healthcare. #AI #Healthcare #Nvidia #ArtificialIntelligence

Wow! Big news in the world of AI and medicine, everyone! 😃 Just caught wind of NVIDIA and Insilico Medicine’s groundbreaking collaboration. They’re pushing the boundaries of generative AI in drug discovery, and the results are mind-blowing. Insilico’s Pharma.AI platform, powered by NVIDIA’s tech, is redefining the drug development timeline. 🧪 They’ve got a drug for idiopathic pulmonary fibrosis in Phase 2 trials—discovered and designed by AI! ⏱️ The kicker? They slashed preclinical discovery from 6 years to just 18 months. That’s the power of AI, folks! Imagine designing new drugs in days, not years. Talk about fast-tracking innovation! I’m thrilled to see our field literally saving lives. It’s not just about cool tech anymore; we’re reshaping the future of healthcare! Who else is pumped about AI’s impact on medicine? https://lnkd.in/eisWqNwB #AI #AIinHealthcare #FuturePharma #GenerativeAI

Struggling to Demonstrate ROI with GenAI? Here’s a Game-Changing Insight If you're finding it challenging to showcase the ROI of Generative AI, the key lies in selecting high-impact use cases. A great example comes from Genentech and NVIDIA, who are leveraging GenAI to revolutionize drug discovery in Early Development and Research. In this short video, they demonstrate how GenAI is being used to design novel molecules and generate experimental data, aiming to uncover the next big breakthrough in medicine. These advancements not only accelerate the drug discovery process but also hold the potential to transform healthcare as we know it. This is innovation at its finest, paving the way for a healthier future for all. https://lnkd.in/eG5aBadw

Generative AI is revolutionizing the landscape of drug discovery, paving the way for groundbreaking advancements in medicine. From unlocking innovative solutions to accelerating the development of life-saving treatments, the impact of Generative AI is profound. By harnessing the capabilities of Large Language Models and cutting-edge technology, we are witnessing a paradigm shift in how new drugs are identified, personalized, and optimized. Drug discovery teams can now easily integrate Generative AI into their workflows to better understand and design drug molecules virtually and reduce the need for resource-heavy physical experiments. Read the latest announcement on NVIDIA BioNeMo at #GTC24 #generativeai #llm #deeplearning #drugdiscovery https://lnkd.in/epZmFmUH

🎥💻 Live Webinar: December 10 🎥💻 10 AM PT | 12 PM CT | 1 PM ET 🏥 AMD & Vultr: Accelerating AI in Healthcare and Life Sciences 🏥 Explore how cutting-edge AI and GPU technologies are transforming healthcare and biotech in this exclusive live webinar. Experts from AMD and Vultr will share how their collaboration drives drug discovery, genomics, and patient care breakthroughs. What you’ll learn: • How AI is revolutionizing diagnostics and precision medicine. • The power of Vultr's cloud GPU infrastructure accelerated by AMD CPUs and GPUs. • Real-world case studies in drug discovery and genomics research. • Best practices for compliance, security, and scalability in healthcare. • Insights into emerging healthcare technology trends. 🎤 Speakers: • Kevin Cochrane, CMO, Vultr • Nathan Goulding, Engineer, Vultr • Tony Nunes and Harini Malik, AMD Specialists 🩺 Don’t miss this opportunity to learn from leaders shaping the future of AI in healthcare. Reserve your spot now: https://lnkd.in/eM3ddJss