Lightning talks: Augmented Mathematical Intelligence

Subscribers:
343,000
Published on ● Video Link: https://www.youtube.com/watch?v=6_nLj9OnbDg



Duration: 38:47
272 views
8


Speakers:
Leonardo de Moura, Senior Principal Researcher, Microsoft Research Redmond
Kevin Buzzard, Professor of Pure Mathematics, Imperial College London
Daniel Selsam, Senior Researcher, Microsoft Research Redmond

Augmented Mathematical Intelligence (AMI) refers to the ability to solve formally specified problems as reliably as humans can over all classes of such problems that are of interest to our civilization. This includes not only mathematics but also computer science, cryptography, and statistics, for example. AMI also includes many subproblems arising in software engineering, physics, finance, and possibly even law. Whereas Artificial General Intelligence (AGI) is both philosophically ill-posed and arbitrarily out of reach, we see a relatively concrete path to reaching AMI using near-future technology on top of the Lean Proof Assistant, an open-source Microsoft Research project. AMI is merely a tool without agency, and does not aim to replace human judgment or aesthetics. Instead, AMI will empower humans to innovate more and with less onerous training.

Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit

Related:
https://leanprover.github.io/about/
https://github.com/dselsam
https://twitter.com/leanprover
https://stacks.math.columbia.edu/




Other Videos By Microsoft Research


2022-02-08Keynote: Learning from observation: Small-data approach to human common sense
2022-02-08Fireside chat: Emergent innovation
2022-02-08Tutorial: Accelerating research with the InnerEye medical imaging toolbox and Azure machine learning
2022-02-08Opening remarks: Towards Human-Like Visual Learning and Reasoning
2022-02-08Research talk: Research and application of AI in Healthcare
2022-02-08Research talk: AI in medical imaging: What’s next?
2022-02-08Research talk: AI for drug discovery
2022-02-08Research talk: Decrypting the secret of gene regulation with AI
2022-02-08Closing remarks: Empowering software developers and mathematicians with next-generation AI
2022-02-08Research talks: Software supply chain security
2022-02-08Lightning talks: Augmented Mathematical Intelligence
2022-02-08Research talk: Torchy: A tracing JIT compiler for PyTorch
2022-02-08Research talks: AI for software development
2022-02-08Opening remarks: Empowering software developers and mathematicians with next-generation AI
2022-02-08Closing Remarks: Health and Life Sciences - Delivery
2022-02-08Tutorial: Translating real-world data into evidence
2022-02-08Future of technology in combatting disease and disparities in treatment: A cardiovascular case study
2022-02-08Research talks: Showcasing health equity, access, and resilience collaborations
2022-02-08Opening remarks: Health & Life Sciences - Discovery
2022-02-08The role of tech in decreasing health inequities, improving access, and strengthening resilience
2022-02-08Opening remarks: Health and Life Sciences - Delivery



Tags:
machine learning systems
symbolic reasoning
next generation AI
developer productivity
microsoft research summit