The Data Exchange Podcast: Connor Leahy on building models and datasets for the natural language research community.
Questioning the Efficacy of Neural Recommendation Systems
The Data Exchange Podcast: Paolo Cremonesi and Maurizio Ferrari Dacrema on the reproducibility, complexity, and inefficiency of neural methods for…
Automation in Data Management and Data Labeling
The Data Exchange Podcast: Hyun Kim on building automation and DataOps tools to help companies unlock computer vision data.
Reinforcement Learning For the Win
The Data Exchange Podcast: Nicolas Hohn on challenges and best practices for using RL and machine learning in the enterprise.
How Companies Are Investing in AI Risk and Liability Minimization
The Data Exchange Podcast: Andrew Burt on the state of AI risk mitigation and responsible AI.
The Future of Machine Learning Lies in Better Abstractions
The Data Exchange Podcast: Travis Addair on how higher levels of abstractions enable non-experts to build efficient machine learning models.
Why You Should Optimize Your Deep Learning Inference Platform
The Data Exchange Podcast: Yonatan Geifman and Ran El-Yaniv on the benefits that accrue from using an inference acceleration platform.
AI Beyond Automation
The Data Exchange Podcast: Jerry Overton on building an Artificial Intelligence Center of Excellence to incubate serious AI talent.
Injecting Software Engineering Practices and Rigor into Data Governance
The Data Exchange Podcast: Steve Touw on why data governance needs to go from the boardroom into code.
Building a data store for unstructured data and deep learning applications
The Data Exchange Podcast: Davit Buniatyan on tensorial data stores optimized for deep learning.