Powering AI with the World's Largest Computer Chip with Joel Hestness - #684

Powering AI with the World's Largest Computer Chip with Joel Hestness - #684

Today we're joined by Joel Hestness, principal research scientist and lead of the core machine learning team at Cerebras. We discuss Cerebras’ custom silicon for machine learning, Wafer Scale Engine 3, and how the latest version of the company’s single-chip platform for ML has evolved to support large language models. Joel shares how WSE3 differs from other AI hardware solutions, such as GPUs, TPUs, and AWS’ Inferentia, and talks through the homogenous design of the WSE chip and its memory architecture. We discuss software support for the platform, including support by open source ML frameworks like Pytorch, and support for different types of transformer-based models. Finally, Joel shares some of the research his team is pursuing to take advantage of the hardware's unique characteristics, including weight-sparse training, optimizers that leverage higher-order statistics, and more. The complete show notes for this episode can be found at twimlai.com/go/684.

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Bridging the Patient-Physician Gap with ML and Expert Systems w/ Xavier Amatriain - #316

Bridging the Patient-Physician Gap with ML and Expert Systems w/ Xavier Amatriain - #316

Today we’re joined by return guest Xavier Amatriain, Co-founder and CTO of Curai, whose goal is to make healthcare accessible and scaleable while bringing down costs. In our conversation, we touch on ...

11 Marras 201939min

What Does it Mean for a Machine to "Understand"? with Thomas Dietterich - #315

What Does it Mean for a Machine to "Understand"? with Thomas Dietterich - #315

Today we have the pleasure of being joined by Tom Dietterich, Distinguished Professor Emeritus at Oregon State University. Tom recently wrote a blog post titled "What does it mean for a machine to “un...

7 Marras 201938min

Scaling TensorFlow at LinkedIn with Jonathan Hung - #314

Scaling TensorFlow at LinkedIn with Jonathan Hung - #314

Today we’re joined by Jonathan Hung, Sr. Software Engineer at LinkedIn. Jonathan presented at TensorFlow world last week, titled Scaling TensorFlow at LinkedIn. In our conversation, we discuss their m...

4 Marras 201935min

Machine Learning at GitHub with Omoju Miller - #313

Machine Learning at GitHub with Omoju Miller - #313

Today we’re joined by Omoju Miller, a Sr. machine learning engineer at GitHub. In our conversation, we discuss: • Her dissertation, Hiphopathy, A Socio-Curricular Study of Introductory Computer Scien...

31 Loka 201943min

Using AI to Diagnose and Treat Neurological Disorders with Archana Venkataraman - #312

Using AI to Diagnose and Treat Neurological Disorders with Archana Venkataraman - #312

Today we’re joined by Archana Venkataraman, John C. Malone Assistant Professor of Electrical and Computer Engineering at Johns Hopkins University. Archana’s research at the Neural Systems Analysis Lab...

28 Loka 201946min

Deep Learning for Earthquake Aftershock Patterns with Phoebe DeVries & Brendan Meade - #311

Deep Learning for Earthquake Aftershock Patterns with Phoebe DeVries & Brendan Meade - #311

Today we are joined by Phoebe DeVries, Postdoctoral Fellow in the Department of Earth and Planetary Sciences at Harvard and Brendan Meade, Professor of Earth and Planetary Sciences at Harvard. Phoebe ...

25 Loka 201936min

Live from TWIMLcon! Operationalizing Responsible AI - #310

Live from TWIMLcon! Operationalizing Responsible AI - #310

An often forgotten about topic garnered high praise at TWIMLcon this month: operationalizing responsible and ethical AI. This important topic was combined with an impressive panel of speakers, includi...

22 Loka 201930min

Live from TWIMLcon! Scaling ML in the Traditional Enterprise - #309

Live from TWIMLcon! Scaling ML in the Traditional Enterprise - #309

Machine learning and AI is finding a place in the traditional enterprise - although the path to get there is different. In this episode, our panel analyzes the state and future of larger, more establi...

18 Loka 201933min

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