Join Lukas Biewald on Gradient Dissent, an AI-focused podcast brought to you by Weights & Biases. Di
Pete is the Technical Lead of the TensorFlow Micro team, which works on deep learning for mobile and
Pieter is the Chief Scientist and Co-founder at Covariant, where his team is building universal AI f
In this episode we're joined by Chris Albon, Director of Machine Learning at the Wikimedia Foundatio
In this episode, Emily and Lukas dive into the problems with bigger and bigger language models, the
Jeff talks about building Facebook's early data team, founding Cloudera, and transitioning into biom
Josh explains how astronomy and machine learning have informed each other, their current limitations
Xavier shares his experience deploying healthcare models, augmenting primary care with AI, the chall
Spence shares his experience creating a product around human-in-the-loop machine translation, and ex
Roger and DJ share some of the history behind data science as we know it today, and reflect on their
Amelia and Filip give insights into the recommender systems powering Pandora, from developing models
From Apache TVM to OctoML, Luis gives direct insight into the world of ML hardware optimization, and
Matthew explains how combining machine learning and computational biology can provide mainstream med
Clem explains the virtuous cycles behind the creation and success of Hugging Face, and shares his th
Wojciech joins us to talk the principles behind OpenAI, the Fermi Paradox, and the future stages of
Phil shares some of the approaches, like sparsity and low precision, behind the breakthrough perform
From working on COVID-19 vaccine rollout to writing a book on responsible ML, Alyssa shares her thou
Sean joins us to chat about ML models and tools at Lyft Rideshare Labs, Python vs R, time series for
Polly explains how microfluidics allow bioengineering researchers to create high throughput data, an
Adrien Gaidon shares his approach to building teams and taking state-of-the-art research from concep
A look at how Nimrod and the team at Nanit are building smart baby monitor systems, from data collec
