Saved by Darren LI and
AI at the Intersection: The A16z Investment Thesis on AI in Bio + Health
sari and added
- The generative AI revolution is swiftly giving rise to a myriad of startups, with an increasing need to categorize them by their function in the AI landscape, including foundational model providers, infrastructure enablers, and application developers.
- Generative AI is transforming industries across the globe, not just in Silicon Valley, with imp... See more
- Generative AI is transforming industries across the globe, not just in Silicon Valley, with imp... See more
Shortwave — The smartest email app on planet Earth
Nicolay Gerold added
Darren LI and added
sari added
In a pre-AI world, in order to build an application, you needed to reduce your idea to a process—a set of rules by which your software would operate to accomplish the goal you set. Sometimes this was easy; for example, a customer relationship manager like Salesforce is naturally reducible to rules.
In a post-AI world, you can build applications for ... See more
In a post-AI world, you can build applications for ... See more
Dan Shipper • Five New Thinking Styles for Working With Thinking Machines
“The promise of artificial intelligence in medicine is to provide composite, panoramic views of individuals’ medical data; to improve decision making; to avoid errors such as misdiagnosis and unnecessary procedures; to help in the ordering and interpretation of appropriate tests; and to recommend treatment.”
Eric Topol • Deep Medicine | Eric Topol
Behruz Davletov added
But business AI can be about more than dollars and cents. When applied to other information-driven public goods, it can mean a massive democratization of high-quality services to those who previously couldn’t afford them. One of the most promising of these is medical diagnosis.
Kai-Fu Lee • AI Superpowers: China, Silicon Valley, and the New World Order
Business AI mines these databases for hidden correlations that often escape the naked eye and human brain. It draws on all the historic decisions and outcomes within an organization and uses labeled data to train an algorithm that can outperform even the most experienced human practitioners. That’s because humans normally make predictions on the ba
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