September 23, 2022

Predicting Out Of Memory Kill events with Machine Learning (Ep. 203)

Sometimes applications crash. Some other times applications crash because memory is exhausted. Such issues exist because of bugs in the code, or heavy memory usage for […]
September 14, 2022

Is studying AI in academia a waste of time? (Ep. 202)

Companies and other business entities are actively involved in defining data products and applied research every year. Academia has always played a role in creating new methods and solutions/algorithms in the fields of machine learning and artificial intelligence.
September 7, 2022

Zero-Cost Proxies: How to find the best neural network without training (Ep. 201)

Neural networks are becoming massive monsters that are hard to train (without the “regular” 12 last-generation GPUs).Is there a way to skip that? Let me introduce […]
September 7, 2022

Online learning is better than batch, right? Wrong! (Ep. 200)

In this episode, I speak about online machine learning systems and why blindly choosing such a paradigm can lead to unpredictable and expensive outcomes. Also, in […]
June 3, 2022

What are generalist agents and why they can change the AI game (Ep. 199)

That deep learning alone is not sufficient to solve artificial general intelligence is a more and more accepted statement. Generalist agents have great properties that can […]
May 27, 2022

Streaming data with ease. With Chip Kent from Deephaven Data Labs (Ep. 198)

In this episode, I am with Chip Kent, chief data scientist at Deephaven Data Labs. We speak about streaming data, real-time, and other powerful tools part […]
May 16, 2022

Learning from data to create personalized experiences with Matt Swalley from Omneky (Ep. 197)

In this episode I speak with Matt Swalley, Chief Business Officer of Omneky, an AI platform that generates, analyzes and optimizes personalized ad creatives at scale. […]
May 16, 2022

State of Artificial Intelligence 2022 (Ep. 196)

Let’s take a break and think about the state of AI in 2022.In this episode I summarize the long report from the Stanford Institute for Human-Centered […]
May 16, 2022

Improving your AI by finding issues within data pockets (Ep. 195)

In this episode I have a conversation with, Itai Bar-Sinai, CPO & Cofounder of Mona. We speak about several interesting points about data and monitoring.Why is […]
April 21, 2022

Fake data that looks, feels, and behaves like production.(Ep.194)

I am with Ander Steele, data scientist and mathematician with a passion for privacy and Shannon Bayatpur, product manager with a background in technical writing and […]
April 21, 2022

Batteries and AI in Automotive (Ep. 193)

In this episode my friend and I speak about AI, batteries and automotive.Dennis Berner, founder of Digitlabs has been operating in the field of automotive and […]
April 21, 2022

Bayesian Machine Learning with Ravin Kumar (Ep. 191)

This is one episode where passion for math, statistics and computers are merged.I have a very interesting conversation with Ravin,  data scientist at Google where he […]
April 21, 2022

What is spatial data science? With Matt Forest from Carto (Ep. 190)

In this episode I am with Matt Forrest, VP of Solutions Engineering at Carto. We speak about machine learning applied to spatial data, spatial SQL and […]
April 1, 2022

Connect. Collect. Normalize. Analyze. An interview with the people from Railz AI (Ep. 189)

April 1, 2022

History of data science [RB] (Ep. 188)

How did we get here? Who invented the methods data scientists use every day? We answer such questions and much more in this wonderful episode with […]
April 1, 2022

Artificial Intelligence and Cloud Automation with Leon Kuperman from Cast.ai (Ep. 187)

In this episode I speak about AI and cloud automation with Leon Kuperman, co-founder and CTO at CAST AI. Formerly Vice President of Security Products OCI […]
February 3, 2022

Embedded Machine Learning: Part 5 – Machine Learning Compiler Optimization (Ep. 186)

This is the last episode of the series “Embedded ML” and I made it for the bravest 🙂I speak about machine learning compiler optimization to a […]
January 25, 2022

Embedded Machine Learning: Part 4 – Machine Learning Compilers (Ep. 185)

In this episode I speak about machine learning compilers, the most important tools to bridge the gap between high level frontends, ML backends and hardware target […]
January 20, 2022

Embedded Machine Learning: Part 3 – Network Quantization (Ep. 184)

In this episode I speak about neural network quantization, a technique that makes networks feasible for embedded systems and small devices. There are many quantization techniques […]
January 15, 2022

Embedded Machine Learning: Part 2 (Ep. 183)

In Part 2 of Embedded Machine Learning, I speak about one important technique to prune a neural network and perform inference on small devices. Such technique […]
January 10, 2022

Embedded Machine Learning: Part 1 (Ep.182)

This episode is the first of a series about Embedded Machine Learning. I explain the requirements of tiny devices and how it is possible to run […]