ENTERING THE AI HEALTHCARE ERA
Transcript of ENTERING THE AI HEALTHCARE ERA
JP Morgan 2021 | Kimberly Powell VP, GM Healthcare
ENTERING THE AI HEALTHCARE ERA
Forward-Looking Statements
Except for the historical information contained herein, certain matters in this presentation including, but not limited to, statements as to: theperformance, benefits, abilities, availability and impact of our products and technologies; TAMs, market sizes and market spend; artificialintelligence being the most powerful technology force of our time; how artificial intelligence is used; Cambridge-1; the adoption of ourtechnologies; AI healthcare startups; enabling the AI healthcare era; our markets; and our growth and growth drivers are forward-lookingstatements within the meaning of the Private Securities Litigation Reform Act of 1995. These forward-looking statements and any otherforward-looking statements that go beyond historical facts that are made in this presentation are subject to risks and uncertainties that maycause actual results to differ materially. Important factors that could cause actual results to differ materially include: global economicconditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological developmentand competition; development of new products and technologies or enhancements to our existing product and technologies; marketacceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences anddemands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated intosystems and other factors.
NVIDIA has based these forward-looking statements largely on its current expectations and projections about future events and trends that itbelieves may affect its financial condition, results of operations, business strategy, short-term and long-term business operations andobjectives, and financial needs. These forward-looking statements are subject to a number of risks and uncertainties, and you should not relyupon the forward-looking statements as predictions of future events. The future events and trends discussed in this presentation may not occurand actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. Although NVIDIAbelieves that the expectations reflected in the forward-looking statements are reasonable, the company cannot guarantee that future results,levels of activity, performance, achievements or events and circumstances reflected in the forward-looking statements will occur. Except asrequired by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances. For acomplete discussion of factors that could materially affect our financial results and operations, please refer to the reports we file from time totime with the SEC, including our Annual Report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports we file with the SEC areposted on our website and are available from NVIDIA without charge.
SAFE HARBOR
$1.25T Industry | $2B R&D per Drug | 12 Years Development | 90% Failure Rate
ADVANCING DRUG DISCOVERY THROUGH COMPUTING
Literature
Drug CandidateDisease Target
Real World Data
STRUCTURE DOCKING SIMULATION
SEARCH
NLP
Chemical Compounds
GENOMICS IMAGING
ARTIFICIAL INTELLIGENCE —THE MOST POWERFUL TECHNOLOGY FORCE OF OUR TIME
GENETIC VARIANT DETECTION
Deep Learning Variant CallingNVIDIA Clara & Google DeepVariant
PROTEIN STRUCTURE PREDICTION
Experimental AccuracyGoogle AlphaFold
BIOMEDICAL & CLINICALNLP
State-of-the-Art Language ModelNVIDIA BioMegatron BioBERT
VIRTUAL DRUG SCREENING
Docking 40B CompoundsUBC DeepDocking
DRUG DISCOVERY
1,000X Faster SimulationsCaltech OrbNet
COMPUTATIONALMICROSCOPE
Atomic Molecular SimulationUCSD NAMD & ANL DeepDrive MD
Experimental Accuracy | Prediction | Simulation
0
5
10
2016 2018 2020
COMPUTATIONAL DEMAND FOR AI DRIVEN DRUG DISCOVERY(petaFLOPS per organization)*
AI
HPC
TOTAL HPC+AI
*Source: NVIDIA estimated - assumes a computational pipeline that identifies 10 disease targets, screens 1M compounds per target (inc. virtual & HCS) and 500 simulations per target
CV
ML
NLP
AlphaFold
DeepVariant
Generative Models
Domain Specific: Data, Algorithms, Skills
ARTIFICIAL INTELLIGENCE — SOFTWARE THAT WRITES SOFTWARE
AI MODEL
DEVELOP DEPLOY
Digital Health Data Algorithms & Compute Automated Skills
RADIOLOGY
PATIENT
MONITORING
PATHOLOGY
GENOMICS
SURGICAL
DECISION
SUPPORT
NVIDIA CLARA DOMAIN SPECIFIC COMPUTATIONAL PLATFORM FOR HEALTHCARE
RADIOLOGY
PATIENT
MONITORING
PATHOLOGY
GENOMICS
SURGICAL
DECISION
SUPPORT
Digital Health Data Algorithms & Compute Automated Skills
DATA CENTERCLOUD EDGE EMBEDDED
Genomics
Chemistry
Imaging
Biomedical NLP
TRITONInference
Server
MONAI
PyTorch
PRE-TRAINED MODELS TRAINING FRAMEWORK
FEDERATED LEARNING SCALABLE DEPLOYMENT
NVIDIA COMPUTING PLATFORMS
NLP IMAGING INSTRUMENTS CONVERSATIONAL AI DRUG DISCOVERYGENOMICS
NVIDIA CLARACOMPUTATIONAL PLATFORM FOR HEALTHCARE
500KNVIDIA GPU Instruments
Deployed
1,000+NVIDIA Inception
AI Healthcare
Startups
2019 2020
125KDownloads
5X
AI Computational Drug Discovery: Frameworks, Applications, Algorithms
INTRODUCING NVIDIA CLARA DISCOVERY
Literature
Drug CandidateDisease Target
Real World Data
STRUCTURE DOCKING SIMULATION
SEARCH
NLP
Chemical Compounds
GENOMICS IMAGING
RAPIDS
Clara Parabricks, RAPIDS CryoSPARC, Relion, AlphaFold RAPIDS NAMD, VMD, OpenMM, MELD Clara Imaging, MONAI
BioMegatron, BioBERT
World Leaders Using GPU Accelerated Computing & AI for Drug Discovery
AI DRIVEN DRUG DISCOVERY
Literature Real World Data
SEARCH
SAMPLING SIMULATION IMAGING
NLP
STRUCTUREGENETICS
Drug CandidateDisease Target
Chemical Compounds
Above organizations focus is broader than the GPU reference applications shown
CAMBRIDGE-1 AI SUPERCOMPUTER
HEALTHCARE &
LIFE SCIENCE RESEARCH
LARGE-SCALE AI &
DATA SCIENCE RESEARCH
COLLABORATION WITH UK INDUSTRY,
UNIVERSITIES, STARTUPS
EDUCATE FUTURE
AI PRACTITIONERS
80 NVIDIA DGX A100 | 400 PETAFLOPS AI COMPUTE | UK’S FASTEST AI SUPERCOMPUTER | WORLD’S TOP 5 GREEN SUPERCOMPUTER
Computational Instrument for AI Healthcare
AI Training | Early AccessTech Integration | Industry Alliance
AI HEALTHCARE STARTUPS MAKE HISTORY IN 2020
Healthcare AI Startup Funding by Quarter*
Digital Health
Imaging &Instruments
DrugDiscovery
*Source: CBInsights: State Of Healthcare Q3'20 Report: Investment & Sector Trends to Watch
** Estimated
-$.5 B
$1.5 B
$3.5 B
$5.5 B
2019 2020**
1,095
20202017
Record Year of Funding | Dozens of Industry Firsts
273
0
10,000
20,000
2010 2015 2020
Healthcare Spend $8T | Aging & Growing Population | Chronic Disease | Prevention
AI IN THE PRACTICE OF MEDICINE
AI MODEL
DEVELOP DEPLOY
Continuous Learning -> Software DefinedAI Healthcare Research AI Skills
RADIOLOGY
PATIENT
MONITORING
PATHOLOGY
GENOMICS
SURGICAL
DECISION
SUPPORT
AI Papers in PubMed(Machine Learning or Deep Learning)
SOFTWARE DEFINEDAI INSTRUMENT REVOLUTIONSensing | Predicting | Assisting
DATA CENTER
EDGE EMBEDDED
CLOUD
NVIDIA COMPUTE PLATFORMS
ANNOUNCING OXFORD NANOPORE TECHNOLOGIES ADOPTS NVIDIA DGX FOR ULTRA-HIGH THROUGHPUT PROMETHIONReal-Time Sequencing, AI Driven Accuracy
High Throughput up to 10 Terabases | 100 Human Genomes per Run
Deep Learning Basecaller “Bonito” 98.3% Raw Accuracy
AI Driven Single Nucleotide Variant Calling 99.9% Accuracy
COVID-19 Testing | Viral Sequencing
Human Genetics | Cancer Research
z
AI SEQUENCING ACCURACY
80%
90%
100%
2016 2017 2018 2019 2020
Models & Training
Deep Learning
ENABLING THE AI HEALTHCARE ERA
Computational Platform for Healthcare Innovators in AI Drug Discovery 1000+ Member Startup Accelerator AI Instrument Revolution
NVIDIA Clara NVIDIA Ecosystem NVIDA Software DefinedNVIDIA Inception