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🎤 Vocab
❗ Information
Small summary
✒️ -> Scratch Notes
Speaker 1 - Pritesh Dasgupta
Healtcare field CTO
- Life science tech strat
AI in healthcare and Life Science Industry
5000-10000 compouns to every one approved FDA drug
- 12-14+ years
Places
- AI in Drug Discovery
- Helps to predict molec structures.
- Can accelerate
- Optimizing Clinical Trials
- AI can analyze data to identify suitable pops for clin trials, ensuring efficient research
- Personalized Medicine
- Analyze complex patient data, holistic. Consider genetic and environmental factors.
- AI Driven Genomics and Proteomics
- Improve analysis of genomic and protemoic data. Fidning hidden patterns.
- Medical Imaging and Diagnostics
- AI in Radioloigy and Imaging Analysis
Speaker 2 - Rikin Gandhi
Agrifood analysis
V1: Farmer to Farmer Videos
HIGHLY effective, massive reach, 10x more cost effective, 24% yield
V2: Deterministic Bot
Farmstack
A bot working inside telegram / whatsapp
V3: Farmer.Chat AI Coach
NLP questions, get returned pertinent info for their location / climate
Get user feedback to increase factual correctness, 70% -> 92% in less than a year
GenAI reduces cost
in person (
Speaker 3 - Karin Prasad
ML Architect
Mich State Chem+CS -> CMU MSAII Program
What is an ML Architect
Find ways to use ML to solved problems
- Reasearch Scientist
- Applied Scientist
- ML Engineer
- AI Engineer
- Data Scientist
His recommendations
Information Theory.
- Thermodynamic of AI. Bounding box.
Systems. - Not just a person interacting with a model, a person interacting with a system.
The book Deep work
Speaker 4 - Ashish Atreja
CIO, CDHO @ UCD Health
Most of a patients time is not spent with a doctor. How can a doctor help to supplement this 99% of time?
- Technology is the best way to scale (don’t have to repeat 15 spiel before surgery to every patient)
- How to prescribe apps as medicine?
AI and technology snake oil salesman
Speaker 5 - Louie Monier
AI with search engines at AltaVista and Google
Text Summarization
Qwiki (2010)
- 30-sec animated summary
- Elaborate smoke and mirrors
- 8 months to prototype
DeepDoc (2023)
- Medical Summaries
- 2 months to prod, one person
- 10x productivity improvement
🔗 -> Links
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