The successes that deep learning systems have achieved in the last decade in all kinds of domains are unquestionable. Self-driving cars, skin cancer diagnostics, movie and song recommendations, language translation, automatic video surveillance, digital assistants represent just a few examples of the ongoing revolution that affects or is going to disrupt soon our everyday life.
But all that glitters is not gold…
Read the full post on the Amethix Technologies blog
Building reproducible machine learning in production (Ep. 96)
Bridging the gap between data science and data engineering: metrics (Ep. 95)
A big welcome to Pryml: faster machine learning applications to production (Ep. 94)
It's cold outside. Let's speak about AI winter (Ep. 93)
The dark side of AI: bias in the machine (Ep. 92)
The dark side of AI: metadata and the death of privacy (Ep. 91)
The dark side of AI: recommend and manipulate (Ep. 90)
The dark side of AI: social media and the optimization of addiction (Ep. 89)
More powerful deep learning with transformers (Ep. 84) (Rebroadcast)
How to improve the stability of training a GAN (Ep. 88)
What if I train a neural network with random data? (with Stanisław Jastrzębski) (Ep. 87)
Deeplearning is easier when it is illustrated (with Jon Krohn) (Ep. 86)
[RB] How to generate very large images with GANs (Ep. 85)
More powerful deep learning with transformers (Ep. 84)
[RB] Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 83)
What is wrong with reinforcement learning? (Ep. 82)
Have you met Shannon? Conversation with Jimmy Soni and Rob Goodman about one of the greatest minds in history (Ep. 81)
Attacking machine learning for fun and profit (with the authors of SecML Ep. 80)
[RB] How to scale AI in your organisation (Ep. 79)
Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 78)
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