Data Science at Home

In this episode of our podcast, we dive deep into the fascinating world of Graph Neural Networks. First, we explore Hierarchical Networks, which allow for the efficient representation and analysis of complex graph structures by breaking them down into smaller, more manageable components. Next, we turn our attention to Generative Graph Models, which enable the creation of new graph structures that...

In this episode, I explore the cutting-edge technology of graph neural networks (GNNs) and how they are revolutionizing the field of artificial intelligence. I break down the complex concepts behind GNNs and explain how they work by modeling the relationships between data points in a graph structure. I also delve into the various real-world applications of GNNs, from drug discovery to recommendati...

In this episode, we dive into the not-so-secret sauce of ChatGPT, and what makes it a different model than its predecessors in the field of NLP and Large Language Models. We explore how human feedback can be used to speed up the learning process in reinforcement learning, making it more efficient and effective. Whether you're a machine learning practitioner, researcher, or simply curious about how...

In this episode, we explore the potential of the highly anticipated GPT-4 language model and the challenges that come with its development. From its ability to generate highly coherent and creative text to concerns about ethical considerations and the potential misuse of such technology, we delve into the promise and pitfalls of GPT-4. Join us as we speak with experts in the field to gain insights...

In this episode, we dive into the ways in which AI and machine learning are disrupting traditional software engineering principles. With the advent of automation and intelligent systems, developers are increasingly relying on algorithms to create efficient and effective code. However, this reliance on AI can come at a cost to the tried-and-true methods of software engineering. Join us as we explor...

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In this episode, we dive into the fascinating world of zero-knowledge proofs and their impact on data science. Zero-knowledge proofs allow one party to prove to another that they know a secret without revealing the secret itself. This powerful concept has numerous applications in data science, from ensuring data privacy and security, to facilitating secure transactions and identity verification. W...

Deep learning methods are not as effective with tabular data. Here is why, and what to do about it.   Sponsors If you're ready to take your WiFi game to the next level, head over to asus.click/ZenWiFi_XD5 or check out the show notes for this episode. Trust me, with ASUS ZenWiFi XD5, you'll get the best WiFi experience ever!   References https://paperswithcode.com/methods/category/deep-tabular-lear...

In this episode I speak about online learning systems and why blindly choosing such a paradigm can lead to very unpredictable and expensive outcomes. Also in this episode, I have to deal with an intruder :)     Links Birman, K.; Joseph, T. (1987). "Exploiting virtual synchrony in distributed systems". Proceedings of the Eleventh ACM Symposium on Operating Systems Principles - SOSP '87. pp. 123–138...

In this episode, I'll be discussing the capabilities and limitations of ChatGPT, an advanced language AI model. I'll go over its power to understand and respond to natural language, and its applications in tasks such as language translation and text summarization. However, I'll also touch on the challenges that still need to be overcome such as bias and data privacy concerns. Tune in for a compreh...

In this episode I am with Kevin McNamara, founder and CEO of Parallel Domain. We speak about a very effective method to generate synthetic data that is currently in production at Parallel Domain. Enjoy the show!     References Parallel Domain Synthetic Data Improves Cyclist Detection (blog post): https://paralleldomain.com/parallel-domain-synthetic-data-improves-cyclist-detection/     Beating the...

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Is it possible to reconstruct a 3D model from a simple image? Under certain constraints, it is! In this episode I tell you how.   Our Sponsors Explore the Complex World of Regulations. Compliance can be overwhelming. Multiple frameworks. Overlapping requirements. Let Arctic Wolf be your guide. Check it out at https://arcticwolf.com/datascience   Amethix works to create and maximize the impact of t...

What if we borrowed from physics some theories that would interpret deep learning and machine learning in general? Here is a list of plausible ways to interpret our beloved ML models and understand why they works, or they don't. Enjoy the show! Our Sponsors NordPass Business has developed a password manager, that will save you a lot of time and energy whenever you  need access to business accounts...

If you think that the problem of self-driving cars has been solved, think twice. As a matter of fact, the problem of self-driving cars cannot be solved with the technical solutions that companies are currently considering. Don't get fooled by marketing and PR on social media. Whoever is telling you they solved the problem of driving a vehicle fully autonomously, they are lying. Here is why.   Our...

Let's look at the history of data platforms. How did they evolve? Why? Shall I switch to the latest architecture? Enjoy the show!   Our Sponsors Explore the Complex World of Regulations. Compliance can be overwhelming. Multiple frameworks. Overlapping requirements. Let Arctic Wolf be your guide. Check it out at https://arcticwolf.com/datascience   Amethix works to create and maximize the impact of...

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. However, there is doubt about how powerful and effective such research efforts are. Is studying AI in academia a waste of time?   Our S...

There are many solutions to private machine learning. I am pretty confident when I say that the one we are speaking in this episode is probably one of the most feasible and reliable. I am with Daniel Huynh, CEO of Mithril Security,  a graduate from Ecole Polytechnique with a specialisation in AI and data science. He worked at Microsoft on Privacy Enhancing Technologies under the office of the CTO...

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That deep learning alone is not sufficient to solve artificial general intelligence, is more and more accepted statement. Generalist agents have great properties that can overcome some of the limitations of single-task deep learning models. Be aware, we are still far from AGI, though.   So what are generalist agents?   References https://arxiv.org/pdf/2205.06175 This is a public episode. If you wo...

How does an autonomous vehicle see? How does it sense the road? They are equipped of many sensors, of course. Are they all powerful enough? Small enough to hide them and make your car look beautiful?  In this episode I speak about LIDAR, high resolution cameras and some machine learning methods adapted to a minimal number of sensors.   Our Sponsors Ready to advance your career in data science? Uni...

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 reasons that were not expected during design and implementation. Can we use machine learning to predict and eventually detect out of memory kills from the operating system? Apparently, the Netflix app many of us use on a daily basis...

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. However, there is doubt about how powerful and effective such research efforts are. Is studying AI in academia a waste of time?   Our S...

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 you to Zero-Cost proxies     References https://www.technologyreview.com/2022/08/05/1056814/automation-ai-machine-learning-automl/ https://iclr-blog-track.github.io/2022/03/25/zero-cost-proxies/ This is a public episode. If you would li...

In this episode I speak about online learning systems and why blindly choosing such a paradigm can lead to very unpredictable and expensive outcomes. Also in this episode, I have to deal with an intruder :)     Links Birman, K.; Joseph, T. (1987). "Exploiting virtual synchrony in distributed systems". Proceedings of the Eleventh ACM Symposium on Operating Systems Principles - SOSP '87. pp. 123–138...