In the last episode of 2019 I speak with Filip Piekniewski about some of the most worth noting findings in AI and machine learning in 2019. As a matter of fact, the entire field of AI has been inflated by hype and claims that are hard to believe. A lot of the promises made a few years ago have revealed quite hard to achieve, if not impossible. Let's stay grounded and realistic on the potential of this amazing field of research, not to bring disillusion in the near future.
Join us to our Discord channel to discuss your favorite episode and propose new ones.
I would like to thank all of you for supporting and inspiring us. I wish you a wonderful 2020!
Francesco and the team of Data Science at Home
Chatting with ChatGPT: Pros and Cons of Advanced Language AI (Ep. 215)
Accelerating Perception Development with Synthetic Data (Ep. 214)
Edge AI applications for military and space [RB] (Ep. 213)
From image to 3D model (Ep. 212)
Machine learning is physics (Ep. 211)
Autonomous cars cannot drive. Here is why. (Ep. 210)
Evolution of data platforms (Ep. 209)
[RB] Is studying AI in academia a waste of time? (Ep. 208)
Private machine learning done right (Ep. 207)
Edge AI for applications in military and space (Ep. 206)
[RB] What are generalist agents and why they can change the AI game (Ep. 205)
LIDAR, cameras and autonomous vehicles (Ep. 204)
Predicting Out Of Memory Kill events with Machine Learning (Ep. 203)
Is studying AI in academia a waste of time? (Ep. 202)
Zero-Cost Proxies: How to find the best neural network without training (Ep. 201)
Online learning is better than batch, right? Wrong! (Ep. 200)
What are generalist agents and why they can change the AI game (Ep. 199)
Streaming data with ease. With Chip Kent from Deephaven Data Labs (Ep. 198)
Learning from data to create personalized experiences with Matt Swalley from Omneky (Ep. 197)
State of Artificial Intelligence 2022 (Ep. 196)
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