Training and optimizing a machine learning model takes a lot of compute resources, but what if we used ML to optimize ML? Luis Ceze created Apache Tensor Virtual Machine (TVM) to optimize ML models and has now founded a company, OctoML, to leverage this technology. Fundamentally, machine learning relies on linear algebra, but how should we pick the fastest approach for each model? Today this is done with human intuition, but TVM builds machine learning models to predict the best approaches to try. It also creates an executable so the model can run best on various target hardware platforms. It can also help select the right target platform for a given model.
Three Questions:
- How long will it take for a conversational AI to pass the Turing test and fool an average person?
- Is machine learning a product or a feature?
- Can you think of any fields that have not yet been touched by AI?
Guests and Hosts:
- Luis Ceze, CEO of OctoML. Find Luis on Twitter at @LuisCeze
- Chris Grundemann, a Gigaom Analyst and Managing Director of Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com and on Twitter at @ChrisGrundemann
- Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett
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