Thinking About Thinking is a 501(c)3 non-profit organization, and our mission is to drive open-access research into the fundamentals of intelligence and computation.
Project 1: Quarterly summits on algorithmic innovation and entrepreneurship.
Day-long events every quarter in which scientists and industry specialists present algorithms for innovation, and creativity, and discovery, and discuss more general use cases.
Leading researchers from universities give a succession of short talks and discussions that spotlight how their algorithms are being used to generate innovations in computational research, biomedicine, engineering, and in the tech industry.
Industry leaders attend and discuss these ideas in Q&A sessions, roundtable discussions, and panel events. These include faculty from business schools, as well as representatives from entrepreneurship, VCs, tech, consultancy, and biomedicine.
Project 2: a large-scale annual conference on the fundamentals of cognitive science, computational neuroscience, and artificial intelligence.
We aim for radical innovation in the mathematical frameworks that underlie our scientific disciplines into understanding and reverse-engineering the brain and mind.
The number of research teams and seminal papers working on problems in cognition, biocomputation, and artificial intelligence has doubled over the last five years. We need new venues where people can present new frameworks, methods, and challenging data, in addition to classical conferences that focus on incremental progress in existing paradigm
Project 3: Partnerships to help scientists move between academia and industry.
In recent years, there has been an enormous upheaval in the way AI research is conducted. Instead of being done in an academic environment, industrial teams are becoming the main source of technical and conceptual developments. This has triggered a fast and steady flow of highly trained researchers from universities to commercial companies, with 75% of AI PhD graduates choosing industry in 2022 versus 58% in 2015.
There has also been a reverse migration. With financial security assured, many conceptual leads from industry are attracted back into part-time roles and collaborations with academia, interested in the blue-sky thinking and intellectual freedom that pure science affords.
This relationship needs infrastructure. At our events and using fellowships we connect leading academics investigating intelligence to conceptual teams in industry. We also connect thought leaders from industry to the leading edge of conceptual work in the academy.
Through fostering these partnerships, creating paid opportunities and investment into pure research, and focusing on open access and traditionally under-represented groups, we keep growing and deepening our efforts to understand and emulate intelligence.