• Episode 38: Collective intelligence (Part 2)

    In the second part of this episode I am interviewing Johannes Castner from CollectiWise, a platform for collective intelligence. I am moving the conversation towards the more practical aspects of the project, asking about the centralised AGI and blockcha...

  • Episode 38: Collective intelligence (Part 1)

    This is the first part of the amazing episode with Johannes Castner, CEO and founder of CollectiWise. Johannes is finishing his PhD in Sustainable Development from Columbia University in New York City, and he is building a platform for collective intelli...

  • Episode 37: Predicting the weather with deep learning

    Predicting the weather is one of the most challenging tasks in machine learning due to the fact that physical phenomena are dynamic and riche of events. Moreover, most of traditional approaches to climate forecast are computationally prohibitive. It seem...

  • Episode 36: The dangers of machine learning and medicine

    Humans seem to have reached a cross-point, where they are asked to choose between functionality and privacy. But not both. Not both at all. No data, no service. That’s what companies building personal finance services say. The same applies to marketing c...

  • Episode 35: Attacking deep learning models

    Attacking deep learning models Compromising AI for fun and profit   Deep learning models have shown very promising results in computer vision and sound recognition. As more and more deep learning based systems get integrated in disparate domains, they w...

  • Episode 34: Get ready for AI winter

    Today I am having a conversation with Filip Piękniewski, researcher working on computer vision and AI at Koh Young Research America. His adventure with AI started in the 90s and since then a long list of experiences at the intersection of computer scienc...

  • Episode 33: Decentralized Machine Learning and the proof-of-train

    In the attempt of democratizing machine learning, data scientists should have the possibility to train their models on data they do not necessarily own, nor see. A model that is privately trained should be verified and uniquely identified across its enti...

  • Episode 32: I am back. I have been building fitchain

    I know, I have been away too long without publishing much in the last 3 months. But, there's a reason for that. I have been building a platform that combines machine learning with blockchain technology. Let me introduce you to fitchain and tell you more ...

  • Founder Interview – Francesco Gadaleta of Fitchain

    Cross-posting from Cryptoradio.io Overview Francesco Gadaleta introduces Fitchain, a decentralized machine learning platform that combines blockchain technology and AI to solve the data manipulation problem in restrictive environments such as healthcare ...

  • Episode 31: The End of Privacy

    Data is a complex topic, not only related to machine learning algorithms, but also and especially to privacy and security of individuals, the same individuals who create such data just by using the many mobile apps and services that characterize their di...

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