Mentioned in 9 AI use cases across 6 industries
Think of NVIDIA BioNeMo as a set of very smart chemistry and biology "co-pilots" that can read and write molecules and proteins the way ChatGPT reads and writes text. Instead of scientists manually trying out millions of possibilities in the lab, BioNeMo helps them design and screen promising drug candidates on a computer first, massively narrowing the search space.
Think of this as a team of digital traffic cops, building inspectors, and city service reps that never sleep. They watch camera feeds, sensors, and city data in real time, then suggest or take actions to keep traffic flowing, fix issues faster, and improve public safety.
This is like building a super–medical dictionary and research assistant that understands DNA, diseases, and treatments all at once. Hospitals and researchers feed it massive amounts of genomic and clinical data so it can help spot patterns, suggest new drug targets, and personalize treatments much faster than humans alone.
Think of this as giving a city a "digital nervous system" powered by NVIDIA chips and AI software so it can see traffic, predict congestion, and coordinate signals, buses, and emergency vehicles more intelligently and automatically.
This is like giving an AI a chest X-ray or MRI scan and having it write the first draft of the radiologist’s report, instead of the doctor starting from a blank page. The doctor still reviews and edits, but the AI does the heavy lifting of describing what it sees.
Think of today’s big AI models as brilliant general doctors who know a little about everything but aren’t yet safe or precise enough to treat complex, high‑risk patients. This paper is about how to retrain and constrain those general doctors so they can safely become top‑tier specialists in specific medical tasks, like reading scans, summarizing patient records, or supporting treatment decisions.
Imagine a TV show where many of the sets, background characters, and even some visual effects are created and tweaked in real‑time by a super–smart digital art department instead of huge physical sets and big VFX teams. That’s what the ‘Beta Earth’ AI production phase is about: using AI as a permanent, responsive virtual studio for a TV series.
This is like building a superpowered AI microscope for DNA and medical records. Mount Sinai brings huge amounts of patient and genomic data, and NVIDIA brings the AI “engines” and computing hardware. Together they’re trying to find hidden patterns in our genes and health histories that humans and traditional software would miss.
This is like giving medical researchers a supercharged AI microscope for DNA: Nvidia supplies the AI ‘engine’ and Sheba provides massive amounts of patient genomic data so computers can spot disease patterns and potential drug targets much faster than humans ever could.