How AI Happens A Highly Compositional Future with Dr. Eric Daimler
Dr. Daimler is an authority in Artificial Intelligence with over 20 years of experience in the field as an entrepreneur, executive, investor, technologist, and policy advisor. He is also the founder of data integration firm Conexus, and we kick our conversation off with the work he is doing to integrate large heterogeneous data infrastructures. This leads us into an exploration of the concept of compositionality, a structural feature that enables systems to scale, which Dr. Daimler argues is the future of IT infrastructure. We discuss how the way we apply AI to data is constantly changing, with data sources growing quadratically, and how this necessitates an understanding of newer forms of math such as category theory by AI specialists. Towards the end of our discussion, we move on to the subject of the adoption of AI in technologies that lives depend on, and Dr. Daimler gives his recommendation for how to engender trust amongst the larger population.
Key Points From This Episode:
- Experience Dr. Daimler has in AI in an academic, commercial, and governmental capacity.
- An issue in the choices being made around how to create data that is useful in large organizations.
- Dr. Daimler’s work bringing heterogeneous data together to influence better business decisions.
- How much money is wasted on ETL processes and how bad the jobs in that field are.
- The difference between modularity and compositionality and why the latter is the future of IT infrastructure.
- How compositionality enables scalability and the need of certain branches of math to justify it.
- The work Dr. Daimler is doing in the field of compositionality at Connexus.
- Whether it is crucial to grasp these newer forms of math to achieve AI mastery.
- How AI systems can integrate into contexts involving human labor and empathy.
- The need to bring together probabilistic and deterministic AI in life and death contexts.
- How to get the public to trust and believe in AI-powered tech with the capacity to save lives.
- What AI practitioners can do to ensure they use their skillset to create a better future.
Tweetables:
“You can create data that doesn’t add more fidelity to the knowledge you’re looking to gain for better business decisions and that is one of the limitations that I saw expressed in the government and other large organizations.” — @ead [0:01:32]
“That’s the world, is compositionality. That is where we are going and the math that supports that, type theory, categorical theory, categorical logic, that’s going to sweep away everything underneath IT infrastructure.” — @ead [0:10:23]
“At the trillions of data, a trillion data sources, each growing quadratically, what we need is category theory.” — @ead [0:13:51]
“People die and the way to solve that problem when you are talking about these life and death contexts for commercial airplane manufacturers or in energy exploration where the consequences of failure can be disastrous is to bring together the sensibilities of probabilistic AI and deterministic AI.” — @ead [0:24:07]
“Circuit breakers, oversight, and data lineage, those are three ways that I would institute a regulatory regime around AI and algorithms that will engender trust amongst the larger population.” — @ead [0:35:12]
Links Mentioned in Today’s Episode: