All episodes

"Rust Is Amazing, as Long as Nobody Looks at It" - Fact-Checking DHH

DHH told Rails World that hand-written code is over, that HEY's backend is being AI-rewritten in Rust ("amazing, as long as you never look at it"), and that developer happiness no longer matters. This episode checks his statements…

AI coding agents have a Mythical Man-Month problem

Fifty years ago Fred Brooks showed why adding more people to a late project makes it later. Today we do the same thing with tokens — more context, more autonomy, same myth, different currency. Struggling with AI and Software? Here is my…

One researcher published the 'System 1 AI' idea in 2025; a frontier lab shipped it as new in 2026

A 2025 solo-author paper on non-generative decision models, a 2026 frontier-lab launch that looks a lot like it, and what these fast, non-autoregressive models can and can't actually do. Struggling with AI and Software? Here is my new book…

AI slowdown: why Altman, Amodei & Musk suddenly agree

Three rival AI CEOs never agree on anything, until now. I break down the Sanders-Casar bill, the timing, and why "too dangerous" might be the best pitch deck line money can buy. Struggling with AI and Software? Here is my new book…

AI is punishing game developers

What is the state of AI and videogames? Who is considering it? What are the big fails so far? This and much more is covered in this 1st episode of AI and videogames. Buy me a coffee Discord Channel: ✨ Connect with us! Personal newsletter…

EU AI Act. What is this thing? (Part 2)

What is "wrong" with the EU AI Act? Watch the full episode and get in touch. Buy me a coffee Discord Channel: ✨ Connect with us! Personal newsletter: 📩 Newsletter: 🎙 Podcast: Available on Spotify, Apple Podcasts, and more. 🐦 Twitter…

EU AI Act. What is this thing? (Part 1)

AI takes over (kinda). Regulators look for a new job. Watch the full episode and get in touch. Buy me a coffee Discord Channel: ✨ Connect with us! Personal newsletter: 📩 Newsletter: 🎙 Podcast: Available on Spotify, Apple Podcasts, and…

AI is the Concorde of our time

AI is technically extraordinary and economically precarious. OpenAI spent $1.35 for every dollar it earned in 2025. Global data center investment now surpasses global oil supply spending. We have built something genuinely remarkable and we…

The propaganda algorithm

Modern propaganda isn’t random noise. It’s a repeatable, engineered algorithm that starts with ideology, weaponizes identity, and manufactures conflict. Once you see the pattern, you can’t unsee it.What happens with AI? Buy me a coffee…

AI tips & tricks

Some of the most asked questions on the channel. Here answered. Buy me a coffee Discord Channel: ✨ Connect with us! Personal newsletter: 📩 Newsletter: 🎙 Podcast: Available on Spotify, Apple Podcasts, and more. 🐦 Twitter: @DataScienceAtHome…

AI and videogames: Conversational NPCs

Can NPCs in videogames leverage new LLM-based tech? What are the benefits? What are the costs? Buy me a coffee Discord Channel: ✨ Connect with us! Personal newsletter: 📩 Newsletter: 🎙 Podcast: Available on Spotify, Apple Podcasts, and…

AI and videogames

What is the state of AI and videogames? Who is considering it? What are the big fails so far? This and much more is covered in this 1st episode of AI and videogames. Buy me a coffee Discord Channel: ✨ Connect with us! Personal newsletter…

Europe, wake up! You Can't Be a Superpower on Someone Else's Servers

Rebuilding a defense industrial base takes 20 years and costs trillions. Tech sovereignty takes 3 years and political will. Europe is doing the hard thing and refusing the easy one. Here's why — and who's profiting from that refusal. Buy…

Social media is an ant mill (Internet is a disaster)

Internet followed nature. Until it didn't. And became the disaster we know. Buy me a coffee ✨ Connect with us! Personal newsletter: 📩 Newsletter: 🎙 Podcast: Available on Spotify, Apple Podcasts, and more. 🐦 Twitter: @DataScienceAtHome…

About Apple's Privacy

Paragon's spyware hacked fully updated iPhones without a single click. Apple just spent $2B on tech that reads your silent speech. And your iCloud? Governments can request it with paperwork. This is what the privacy brand actually buys…

Productivity is the new data breach

Your employees aren't being hacked. They're doing it themselves, one ChatGPT prompt at a time. What is it? And how to fix the biggest corporate espionage of all times. Buy me a coffee ✨ Connect with us! Personal newsletter: 📩 Newsletter: 🎙…

Programmable Money: The Cage They'll Call Convenience

Money has always been yours to spend freely. That's about to change. This episode breaks down programmable money, the technology that turns your wallet into a permission system. ✨ Connect with us! Personal newsletter: 📩 Newsletter: 🎙…

There Is No AI. There's a Stateless Function on 10,000 GPUs Pretending to Know You

Right now, millions of people are simultaneously chatting with a system that remembers nothing, knows nothing, and resets after every message. The engineering keeping that illusion alive is actually the impressive part. ✨ Connect with us!…

Your Favorite AI Startup is Probably Bullshit

The brutal truth about why Silicon Valley is blowing billions on glorified autocomplete while pretending it's the next iPhone. We're diving deep into the AI investment circus where VCs who can't code are funding companies that barely…

Why AI Researchers Are Suddenly Obsessed With Whirlpools

VortexNet uses actual whirlpools to build neural networks. Seriously. By borrowing equations from fluid dynamics, this new architecture might solve deep learning's toughest problems—from vanishing gradients to long-range dependencies…

AGI: The Dream We Should Never Reach

Also on YouTube Two AI experts who actually love the technology explain why chasing AGI might be the worst thing for AI's future—and why the current hype cycle could kill the field we're trying to save. Want to dive deeper? Head to…

When Data Stops Being Code and Starts Being Conversation

Mark Brocato built Mockaroo—the tool that taught millions of developers how to fake data. Now, as Head of Engineering at Tonic.ai, he's building the AI agent that's making his own creation obsolete. In this episode, we explore why static…

Your AI Strategy is Burning Money: Here's How to Fix It

Most companies don't have an AI problem. They have a decision-making problem. Matt Lea, founder of Schematical and CloudWarGames, has spent nearly 20 years helping tech leaders ship smarter. In this conversation, he breaks down when AI…

From Tokens to Vectors: The Efficiency Hack That Could Save AI

LLMs generate text painfully slow, one low-info token at a time. Researchers just figured out how to compress 4 tokens into smart vectors & cut costs by 44%—with full code & proofs! Meanwhile OpenAI drops product ads, not papers. We…

Why AI Researchers Are Suddenly Obsessed With Whirlpools

VortexNet uses actual whirlpools to build neural networks. Seriously. By borrowing equations from fluid dynamics, this new architecture might solve deep learning's toughest problems—from vanishing gradients to long-range dependencies…

The Scientists Growing Living Computers in Swiss Labs

Fred Jordan, Co-CEO of FinalSpark, takes us inside the radical world of biological computing, where real neurons extracted from human tissue are being trained to solve problems that would require 10 megawatts in silicon. We explore the…

When AI Hears Thunder But Misses the Fear

Sanjoy Chowdhury reveals AI's hidden weakness: while systems can see objects and hear sounds perfectly, they can't reason across senses like humans do. His research at University of Maryland College Park, including the Meerkat model and…

Why VCs Are Funding $100M Remote Control Toys

This episode exposes the uncomfortable truth: most defense tech startups are just software engineers cosplaying as military innovators, creating fragmented solutions that Pentagon doesn't need. Not now, at least. References War On The…

How Hacker Culture Died

A nostalgic dive into the rise and fall of true hacker culture - from MIT's curious tinkerers to today's hustle-obsessed "founders." Plus, why IRC was peak internet and what we lost when convenience killed community. For anyone who misses…

Robots Suck (But It’s Not Their Fault)

We were promised robot butlers and got Roombas that cry under the couch. In this brutally honest (and slightly hilarious) episode, Francesco dives into why the robot revolution fizzled, why your dishwasher still needs you, and how robotics…

Your Favorite AI Startup is Probably Bullshit

The brutal truth about why Silicon Valley is blowing billions on glorified autocomplete while pretending it's the next iPhone. We're diving deep into the AI investment circus where VCs who can't code are funding companies that barely…

Tech's Dumbest Mistake: Why Firing Programmers for AI Will Destroy Everything

From the viral article "Tech's Dumbest Mistake: Why Firing Programmers for AI Will Destroy Everything" on my newsletter at here are my thoughts about AI replacing programmers... 🎙️ Sponsors AGNTCY — The open source collective building the…

Brains in the Machine: The Rise of Neuromorphic Computing

In this episode of Data Science at Home, we explore the fascinating world of neuromorphic computing — a brain-inspired approach to computation that could reshape the future of AI and robotics. The episode breaks down how neuromorphic…

DSH/Warcoded - AI in the Invisible Battlespace

This episode explores the invisible battlespace of cyber and electronic warfare, where AI takes center stage. From autonomous hacking bots to smart jamming and adversarial attacks on machine learning models, we uncover how modern conflicts…

DSH/Warcoded Swarming the Battlefield

Swarming the Battlefield explores how artificial intelligence is revolutionizing combat through coordinated drone swarms. We dive into the algorithms that enable autonomous collaboration, from decentralized decision-making to real-time…

DSH/Warcoded Kill Chains and Algorithmic Warfare – Autonomy in Targeting and Engagement

In this gripping follow-up, we dive into how AI is transforming kinetic operations—from identifying a threat to executing a strike. 🔍 Highlights from this episode: How AI compresses the OODA loop (Observe, Orient, Decide, Act) The spectrum…

DSH/Warcoded: Eyes and Ears of the Machine – AI Reconnaissance and Surveillance

Welcome to DSH/Warcoded We explore how AI is transforming ISR (Intelligence, Surveillance, Reconnaissance)—from satellite imagery to drone feeds. In this episode: 🔍 Computer vision for target ID📡 Predictive surveillance & pattern-of-life…

AI Agents with Atomic Agents 🚀 with Kenny Vaneetvelde

🎙️ In this episode of Data Science at Home, we sit down with Kenny Vaneetvelde, the mastermind behind Atomic Agents, a groundbreaking framework redefining AI development. 🔍 Discover how atomicity simplifies complex AI systems, why…

Run massive models on crappy machines

AI shouldn’t be limited to those with access to expensive hardware. This episode explores how to break down barriers by running massive AI models on "crappy machines"—affordable, low-spec devices. Clever techniques like quantization…

WeightWatcher: The AI Detective for LLMs (DeepSeek & OpenAI included)

Is DeepSeek the next big thing in AI? Can OpenAI keep up? And how do we truly understand these massive LLMs? Enter WeightWatcher—the AI detective tool that peeks inside neural networks without needing their data. In this episode, we chat…

Tech's Dumbest Mistake: Why Firing Programmers for AI Will Destroy Everything

From the viral article "Tech's Dumbest Mistake: Why Firing Programmers for AI Will Destroy Everything" on my newsletter at here are my thoughts about AI replacing programmers... ✨ Connect with us! 📩 Newsletter: 🎙 Podcast: Available on…

Scaling Smart: AI, Data, and Building Future-Ready Enterprises with Josh Miramant

In this episode, we dive into the transformative world of AI, data analytics, and cloud infrastructure with Josh Miramant, CEO of Blue Orange Digital. As a seasoned entrepreneur with over $25 million raised across ventures and two…

Autonomous Weapons and AI Warfare

Here’s the updated text with links to the websites included: AI is revolutionizing the military with autonomous drones, surveillance tech, and decision-making systems. But could these innovations spark the next global conflict? In this…

8 Proven Strategies to Scale Your AI Systems Like OpenAI! 🚀

In this episode of Data Science at Home, we’re diving deep into the powerful strategies that top AI companies, like OpenAI, use to scale their systems to handle millions of requests every minute! From stateless services and caching to the…

Humans vs. Bots: Are You Talking to a Machine Right Now?

In this episode of Data Science at Home, host Francesco Gadaleta dives deep into the evolving world of AI-generated content detection with experts Souradip Chakraborty, Ph.D. grad student at the University of Maryland, and Amrit Singh…

AI bubble, Sam Altman’s Manifesto and other fairy tales for billionaires

Welcome to Data Science at Home, where we don’t just drink the AI Kool-Aid. Today, we’re dissecting Sam Altman’s “AI manifesto”—a magical journey where, apparently, AI will fix everything from climate change to your grandma's back pain…

AI vs. The Planet: The Energy Crisis Behind the Chatbot Boom

In this episode of Data Science at Home, we dive into the hidden costs of AI’s rapid growth — specifically, its massive energy consumption. With tools like ChatGPT reaching 200 million weekly active users, the environmental impact of AI is…

Love, Loss, and Algorithms: The Dangerous Realism of AI

Subscribe to our new channel In this episode of Data Science at Home, we confront a tragic story highlighting the ethical and emotional complexities of AI technology. A U.S. teenager recently took his own life after developing a deep…

VC Advice Exposed: When Investors Don’t Know What They Want

Ever feel like VC advice is all over the place? That’s because it is. In this episode, I expose the madness behind the money and how to navigate their confusing advice! Watch the video at Subscribe to our new Youtube channel 00:00…

AI Says It Can Compress Better Than FLAC?! Hold My Entropy 🍿

Can AI really out-compress PNG and FLAC? 🤔 Or is it just another overhyped tech myth? In this episode of Data Science at Home, Frag dives deep into the wild claims that Large Language Models (LLMs) like Chinchilla 70B are beating…

What Big Tech Isn’t Telling You About AI

Are AI giants really building trustworthy systems? A groundbreaking transparency report by Stanford, MIT, and Princeton says no. In this episode, we expose the shocking lack of transparency in AI development and how it impacts bias…

Money, Cryptocurrencies, and AI: Exploring the Future of Finance with Chris Skinner

We're revisiting one of our most popular episodes from last year, where renowned financial expert Chris Skinner explores the future of money. In this fascinating discussion, Skinner dives deep into cryptocurrencies, digital currencies, AI…

Kaggle Kommando’s Data Disco: Laughing our Way Through AI Trends

In this episode, join me and the Kaggle Grand Master, Konrad Banachewicz, for a hilarious journey into the zany world of data science trends. From algorithm acrobatics to AI, creativity, Hollywood movies, and music, we just can't get…

AI and Video Game Development: Navigating the Future Frontier

In this episode we delve into the dynamic realm of game development and the transformative role of artificial intelligence (AI). Join Frag, Jim and Mike as they explore the current landscape of game development processes, from initial…

LLMs: Totally Not Making Stuff Up (they promise)

In this episode, we dive into the wild world of Large Language Models (LLMs) and their knack for… making things up. Can they really generalize without throwing in some fictional facts? Or is hallucination just part of their charm? Let’s…

AI: The Bubble That Might Pop—What’s Next?

The hype around Generative AI is real, but is the bubble about to burst? Join me as we dissect the recent downturn in AI investments and what it means for the tech giants like OpenAI and Nvidia. Could this be the end of the AI gold rush…

Data Guardians: How Enterprises Can Master Privacy with MetaRouter

In this insightful episode, we dive deep into the pressing issue of data privacy, where 86% of U.S. consumers express growing concerns and 40% don't trust companies to handle their data ethically. Join us as we chat with the Vice President…

Low-Code Magic: Can It Transform Analytics?

Join us as David Marom, Head of Panoply Business, explores the benefits of all-in-one data platforms. Learn how tech stack consolidation boosts efficiency, improves data accuracy, and cuts costs. David shares insights on overcoming common…

Do you really know how GPUs work?

Join us in this exciting episode of the Data Science at Home podcast. It's all about GPUs. We'll take you on a journey through the inner workings of these powerful processors, explaining how they handle complex computations and drive…

Harnessing AI for Cybersecurity: Expert Tips from QFunction

In this episode, we sit down with Ryan Smith, Founder of QFunction LLC, to explore how AI and machine learning are revolutionizing cybersecurity. With over 8 years of experience, including work at NASA's Jet Propulsion Laboratory, Ryan…

Rust in the Cosmos Part 4: What happens in space?

In this last episode of the series "Rust in the Cosmos" we speak about what happens in space, what projects are currently active and what happened in the past that we can learn from? What about Rust and space applications? As always, let's…

Rust in the Cosmos Part 3: Embedded programming for space

In this episode of "Rust in the Cosmos" we delve into the challenges of building embedded applications for space. Did you know that once you ship your app to space... you can't get it back?:P What role is Rust playing here? Let's find…

Rust in the Cosmos Part 2: testing software in space

In this episode of "Rust in the Cosmos" we delve into the challenge of testing software for... ehm... space How can Rust help? Let's find out;) Sponsors Arctic Wolf Learn what the new year holds for ransomware as a service, Active…

Rust in the Cosmos Part 1: Decoding Communication

In this inaugural episode of "Rust in the Cosmos," we delve into the intricacies of communication in space and some of the challenges in space application development. Sponsors Intrepid AI ( is an AI assisted all-in-one platform for…

AI and Video Game Development: Navigating the Future Frontier

In this episode we delve into the dynamic realm of game development and the transformative role of artificial intelligence (AI). Join Frag, Jim and Mike as they explore the current landscape of game development processes, from initial…

Kaggle Kommando's Data Disco: Laughing our Way Through AI Trends

In this episode, join me and the Kaggle Grand Master, Konrad Banachewicz, for a hilarious journey into the zany world of data science trends. From algorithm acrobatics to AI, creativity, Hollywood movies, and music, we just can't get…

Revolutionizing Robotics: Embracing Low-Code Solutions

In this episode of Data Science at Home, we explore the game-changing impact of low-code solutions in robotics development. Discover how these tools bridge the coding gap, simplify integration, and enable trial-and-error development. We'll…

Is SQream the fastest big data platform?

Join us in a dynamic conversation with Yori Lavi, Field CTO at SQream, as we unravel the data analytics landscape. From debunking the data lakehouse hype to SQream's GPU-based magic, discover how extreme data challenges are met with…

OpenAI CEO Shake-up: Decoding December 2023

In this episode from a month ago, join me as we unravel the controversial CEO firing at OpenAI in December 2023. I share my insights on the events, decode the intricacies, and explore what lies ahead for this influential organization…

Careers, Skills, and the Evolution of AI

!!WARNING!! Due to some technical issues the volume is not always constant during the show. I sincerely apologise for any inconvenienceFrancesco In this episode, I speak with Richie Cotton, Data Evangelist at DataCamp, as he delves into…

Open Source Revolution: AI’s Redemption in Data Science

Dive into the world of Data Science at Home with our latest episode, where we explore the dynamic relationship between Artificial Intelligence and the redemption of open source software. In this thought-provoking discussion, I share my…

Money, Cryptocurrencies, and AI: Exploring the Future of Finance with Chris Skinner

In this captivating podcast episode, join renowned financial expert Chris Skinner as he delves into the fascinating realm of the future of money. From cryptocurrencies to government currencies, the metaverse to artificial intelligence…

Debunking AGI Hype and Embracing Reality

In this thought-provoking episode, we sit down with the renowned AI expert, Filip Piekniewski, Phd, who fearlessly challenges the prevailing narratives surrounding artificial general intelligence (AGI) and the singularity. With a…

Destroy your toaster before it kills you. Drama at OpenAI and other stories

Brace yourselves, dear friends! In this episode, we delve into the earth-shattering revelation that OpenAI might have stumbled upon AGI (lol) and we're all just seconds away from being replaced by highly sophisticated toasters (lol lol)…

The AI Chip Chat 🤖💻

Dive into the cool world of AI chips with us! 🚀 We're breaking down how these special computer chips for AI have evolved and what makes them different. Think of them like the superheroes of the tech world! Don't miss out! 🎙️🔍 #AIChips…

Rolling the Dice: Engineering in an Uncertain World

Hey there, engineering enthusiasts! Ever wondered how engineers deal with the wild, unpredictable twists and turns in their projects? In this episode, we're spilling the beans on uncertainty and why it's the secret sauce in every…

How Language Models Are the Ultimate Database

In this episode, dive deep into the world of Language Models as we decode their intricate structure, revealing how these powerful algorithms exploit concepts from the past. But... what if LLMs were just a database? References

Elon is right this time: Rust is the language of AI

In this episode, I delve into Elon Musk's foresight on the future of AI as he champions Rust programming language. Here is why Rust stands at the forefront of AI technology and the potential it holds. References

Attacking LLMs for fun and profit

As a continuation of Episode 238, I explain some effective and fun attacks to conduct against LLMs. Such attacks are even more effective on models served locally, that are hardly controlled by human feedback. Have great fun and learn them…

Unlocking Language Models: The Power of Prompt Engineering

Join me on an enlightening journey through the world of prompt engineering. Explore the multifaceted skills and strategies involved in harnessing the potential of large language models for various applications. From enhancing safety…

Erosion of Software Architecture Quality in the Age of AI Code Generation

In this era of AI-powered code generation, software architects are facing a concerning decline in the quality of their creations. The once meticulously crafted software architectures are now being compromised. Should LLMs be responsible?…

The new dimension of AI: Vector Databases

Let's delve into the emerging trend in database design – or is it really a new trend? The realm of vector databases and their revolutionary influence on AI and ML is making headlines. Come along as we investigate how these groundbreaking…

Building Self Serve Business Intelligence With AI and LLMs at Zenlytic

In this episode, we dive into the world of data analytics and artificial intelligence with Ryan, the CEO, and Paul, the CTO of Zenlytic. Having graduated from Harvard and with extensive backgrounds in venture capital, consulting, and data…

Money, Cryptocurrencies, and AI: Exploring the Future of Finance with Chris Skinner

In this captivating podcast episode, join renowned financial expert Chris Skinner as he delves into the fascinating realm of the future of money. From cryptocurrencies to government currencies, the metaverse to artificial intelligence…

Debunking AGI Hype and Embracing Reality

In this thought-provoking episode, we sit down with the renowned AI expert, Filip Piekniewski, Phd, who fearlessly challenges the prevailing narratives surrounding artificial general intelligence (AGI) and the singularity. With a…

Full steam ahead! Unraveling Forward-Forward Neural Networks

In this exciting episode, we dive into the world of Forward-Forward Neural Networks, unveiling their mind-boggling power and potential. Join us as we demystify these advanced AI algorithms and explore how they're reshaping industries and…

The LLM Battle Begins: Google Bard vs ChatGPT

Brace yourselves as we uncover the mind-blowing AI model, Google Bard, that's poised to challenge ChatGPT and other conversational AI systems. Join us as we explore the revolutionary features of Bard, its cutting-edge architecture, and its…

Unleashing the Force: Blending Neural Networks and Physics for Epic Predictions

In this enlightening episode of our podcast, we delve into the fascinating realm of Physics Informed Neural Networks (PINNs) and explore how they combine the extraordinary prediction capabilities of neural networks with the unparalleled…

AI’s Impact on Software Engineering: Killing Old Principles?

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…

Warning! Mathematical Mayhem Ahead: Demystifying Liquid Time-Constant Networks

Hold on to your calculators and buckle up for a wild mathematical ride in this episode! Brace yourself as we dive into the fascinating realm of Liquid Time-Constant Networks (LTCs), where mathematical content reaches new heights of…

Efficiently Retraining Language Models: How to Level Up Without Breaking the Bank

Get ready for an eye-opening episode! 🎙️ In our latest podcast episode, we dive deep into the world of LoRa (Low-Rank Adaptation) for large language models (LLMs). This groundbreaking technique is revolutionizing the way we approach…

Revolutionize Your AI Game: How Running Large Language Models Locally Gives You an Unfair Advantage Over Big Tech Giants

This is the first episode about the latest trend in artificial intelligence that's shaking up the industry - running large language models locally on your machine. This new approach allows you to bypass the limitations and constraints of…

Rust: A Journey to High-Performance and Confidence in Code at Amethix Technologies

The journey of porting our projects to Rust was intense, but it was a decision we made to improve the quality of our software. The migration was not an easy task, as it required a considerable amount of time and resources. However, it was…

The Power of Graph Neural Networks: Understanding the Future of AI - Part 2/2

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…

The Power of Graph Neural Networks: Understanding the Future of AI - Part 1/2

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…

Leveling Up AI: Reinforcement Learning with Human Feedback

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…

The promise and pitfalls of GPT-4

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…

AI’s Impact on Software Engineering: Killing Old Principles?

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…

Edge AI applications for military and space

Prove It Without Revealing It: Exploring the Power of Zero-Knowledge Proofs in Data Science

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…

Deep learning vs tabular models

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…

Online learning is better than batch, right? Wrong!

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…

Chatting with ChatGPT: Pros and Cons of Advanced Language AI

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…

Accelerating Perception Development with Synthetic Data

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…

Edge AI applications for military and space

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, work across devices, even with the other members of your team, or whenever you need…

From image to 3D model

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…

Machine learning is physics

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…

Autonomous cars cannot drive. Here is why.

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…

Evolution of data platforms

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…

Is studying AI in academia a waste of time?

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…

Private machine learning done right

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…

Edge AI for applications in military and space

Our Sponsors Ready to advance your career in data science? University of Cincinnati Online offers nationally recognized educational programs in business analytics and information systems. Predictive Analytics Today named UC as the No.1 MS…

What are generalist agents and why they can change the AI game

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…

LIDAR, cameras and autonomous vehicles

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…

Predicting Out Of Memory Kill events with Machine Learning

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…

Is studying AI in academia a waste of time?

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…

Zero-Cost Proxies: How to find the best neural network without training

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

Online learning is better than batch, right? Wrong!

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…

What are generalist agents and why they can change the AI game

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…

Streaming data with ease. With Chip Kent from Deephaven Data Labs

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 of the Deephaven platform. Links Deephaven - Deephaven Community Core Documentation…

Learning from data to create personalized experiences with Matt Swalley from Omneky

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. We speak about the way AI is used for generating customized…

State of Artificial Intelligence 2022

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 Artificial Intelligence (HAI) Enjoy! References

Improving your AI by finding issues within data pockets

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 AI monitoring so different from monitoring classic software?How to reduce the…

Fake data that looks, feels, and behaves like production.

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 computer science, from Tonic.ai. We speak about data. Fake data. But all…

Batteries and AI in Automotive

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 batteries for a long time. His point of views are absolutely a must to listen…

Collect data at the edge

In this episode I speak with Manavalan Krishnan from Tsecond about capturing massive amounts of data at the edge with security and reliability in mind. This episode is brought to you by NordVPN NordVPN protects your privacy while you are…

Bayesian Machine Learning with Ravin Kumar

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 uses data to inform decisions. He has previously worked at Sweetgreen…

What is spatial data science? With Matt Forest from Carto

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 GIS (Geographic Information System).Enjoy the show! This episode is brought to you by…

Connect. Collect. Normalize. Analyze. An interview with the people from Railz AI

In this episode I am with Pasha Zavari - Director of Data Science and Derek Manuge - Co-founder and CTO at Railz. Railz is a very interesting company with an incredible mission: normalizing and extracting insights from the most tedious…

History of data science

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 Triveni Gandhi, Senior Data Scientist and Shaun McGirr, AI Evangelist at Dataiku. We cover…

Artificial Intelligence and Cloud Automation with Leon Kuperman from Cast.ai

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 at Oracle, Leon’s professional experience spans across tech companies such as IBM…

Embedded Machine Learning: Part 5 - Machine Learning Compiler Optimization

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 much greater detail. Enjoy the episode! Chat with me Join us on Discord community chat to…

Embedded Machine Learning: Part 4 - Machine Learning Compilers

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 architectures. There are several compilers one can choose. Before that…

Embedded Machine Learning: Part 3 - Network Quantization

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 depending on several factors that are all important to…

Embedded Machine Learning: Part 2

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 helps preserving most of the accuracy with a model orders of magnitude smaller…

Embedded Machine Learning: Part 1

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 machine learning models. Join us on Discord community chat to discuss the show, suggest new…

History of Data Science

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 Triveni Gandhi, Senior Data Scientist and Shaun McGirr, AI Evangelist at Dataiku. We cover…

Capturing Data at the Edge

In this episode I speak with Manavalan Krishnan from Tsecond about capturing massive amounts of data at the edge with security and reliability in mind. This episode is brought to you by Tsecond The growth of data being created at static…

Composable Artificial Intelligence

If you think deep learning is a method to get to AGI, think again. Humans, as well as all mammals think in a... composable way. Come chat with us on Discord Sponsors This episode is brought to you by Amethix Technologies Amethix use…

What is a data mesh and why it is relevant

Sponsors This episode is brought to you by Amethix Technologies Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals…

Environmentally friendly AI

Sponsors This episode is brought to you by Advanced RISC Machines (ARM). ARM is a family of reduced instruction set computing architectures for computer processors Amethix use advanced Artificial Intelligence and Machine Learning to build…

Do you fear of AI? Why?

This episode summarizes a study about trends of AI in 2021, the way AI is perceived by people of different background and some other weird questions. For instance, would you have sexual intercourse with a robot? Would you be in a…

Composable models and artificial general intelligence

If you think deep learning is a method to get to AGI, think again. Humans, as well as all mammals think in a... composable way. Sponsors This episode is brought to you by Advanced RISC Machines (ARM). ARM is a family of reduced instruction…

Ethics and explainability in AI with Erika Agostinelli from IBM

AI, ethics, and explainability. Are these topics that only large corporations can spend resources on? Can product-focused startups even think about them? We answer such questions in this amazing episode with Erika Agostinelli from the AI…

Is neural hash by Apple violating our privacy?

Sponsor This episode is brought to you by Advanced RISC Machines (ARM). ARM is a family of reduced instruction set computing architectures for computer processors

Fighting Climate Change as a Technologist

The content of this episode has been created by Sylvain Kerkour Feel free to subscribe to his newsletter at Projects worth considering Open Source Ecology: are building a set of Open Source and reusable blueprints for a civilization that…

AI in the Enterprise with IBM Global AI Strategist Mara Pometti

IBM Global AI Strategist Mara Pometti is IBM’s first AI Strategist. She defines and designs the strategy for AI solutions by revealing overlooked insights hidden in enterprises’ data. In this episode we speak about strategy, explainable AI…

Speaking about data with Mikkel Settnes from Dreamdata.io

In this episode Mikkel and Francesco have a really interesting conversation about some key differences between large and small organization in approaching machine learning. Listen to the episode to know more. References

Send compute to data with POSH data-aware shell

Our Sponsors Quantum Metric Stay off the naughty list this holiday season by reducing customer friction, increasing conversions, and personalizing the shopping experience. Want a sneak peak? Visit us at quantummetric.com/podoffer and see…

How are organisations doing with data and AI?

A few weeks ago I was the guest of a very interesting show called "AI Today". In that episode I talked about some of the biggest trends emerging in AI and machine learning today as well as how organizations are dealing with and managing…

Don't fight! Cooperate. Generative Teaching Networks

Remember GANs? Generative Adversarial Networks for synthetic data generation? There is a new method called Generative Teaching Networks, that uses similar concepts - just quite the opposite:P - to train models faster, better and with less…

CSV sucks. Here is why.

It's time we get serious about replacing the CSV format with something that, guess what? it has been around for so long. In this episode I explain the good parts of CSV files and the not so good ones. It's time we evolve to something…

Reinforcement Learning is all you need. Or is it?

Is reinforcement learning sufficient to build truly intelligent machines? Listen to this episode to find out. Our Sponsors Quantum Metric Stay off the naughty list this holiday season by reducing customer friction, increasing conversions…

What's happening with AI today?

In this episode I have a wonderful chat with Ronald Schmelzer and Kathleen Walch, authors of "AI Today" the top podcast for those wanting a no-hype, practical, real-world insight into what enterprises, public sector agencies, thought…

2 effective ways to explain your predictions

Our Sponsor Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and…

The Netflix challenge. Fair or what?

Remember the Netflix challenge? It was a ton of money for the one who would have cracked the problem of recommending the best possible movie. Was it a fair challenge? Did it work?Let me tell you what happened... Sponsors Get one of the…

Artificial Intelligence for Blockchains with Jonathan Ward CTO of Fetch AI

In this episode Fetch AI CTO Jonathan Ward speaks about decentralization, AI, blockchain for smart cities and the enterprise.Below some great links about collective learning, smart contracts in Rust and the Fetch AI ecosystem…

Apache Arrow, Ballista and Big Data in Rust with Andy Grove RB

Do you want to know the latest in big data analytics frameworks? Have you ever heard of Apache Arrow? Rust? Ballista? In this episode I speak with Andy Grove one of the main authors of Apache Arrow and Ballista compute engine.Andy explains…

GitHub Copilot: yay or nay?

It made already quite some noise in the news, GitHub copilot promises to be your pair programmer for life.In this episode I explain how and what GitHub copilot does. Should developers be happy, scared or just keep coding the traditional…

Pandas vs Rust

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A simple trick for very unbalanced data

Data from the real world are never perfectly balanced. In this episode I explain a simple yet effective trick to train models with very unbalanced data. Enjoy the show! Sponsors Get one of the best VPN at a massive discount with coupon…

Time to take your data back with Tapmydata

In this episode I am with Gilbert Hill, head of strategy at We speak about personal data, blockchain and the ability to control it and monetize with another simple yet effective app in the ecosystem. References

True Machine Intelligence just like the human brain

In this episode I have a really interesting conversation with Karan Grewal, member of the research staff at Numenta where he investigates how biological principles of intelligence can be translated into silicon.We speak about the thousand…

Delivering unstoppable data with Streamr

Delivering unstoppable data to unstoppable apps is now possible with Streamr Network Streamr is a layer zero protocol for real-time data which powers the decentralized Streamr pub/sub network. The technology works in tandem with companion…

MLOps: the good, the bad and the ugly

Our Sponsor Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and…

MLOps: what is and why it is important Part 2

Our Sponsor Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and…

MLOps: what is and why it is important

If you think that knowing Tensorflow and Scikit-learn is enough, think again.MLOps is one of those trendy terms today. What is MLOps and why is it important? In this episode I speak about the undeniable evolution of the data scientist in…

Can I get paid for my data? With Mike Andi from Mytiki

Your data is worth thousands a year. Why aren’t you getting your fair share? There is a company that has a mission: they want you to take back control and get paid for your data. In this episode I speak about knowledge graphs, data…

Building high-growth data businesses with Lillian Pierson

In this episode I have an amazing conversation with Lillian Pierson from data-mania.com This is an action-packed episode on how data professionals can quickly convert their data expertise into high-growth data businesses, all by selecting…

Learning and training in AI times

Is there a gap between life sciences and data science?What's the situation when it comes to interdisciplinary research?In this episode I am with Laura Harris, Director of Training for the Institute of Cyber-Enabled Research (ICER) at…

You are the product

In this episode I am with George Hosu from Cerebralab and we speak about how dangerous it is not to pay for the services you use, and as a consequence how dangerous it is letting an algorithm decide what you like or not. Our Sponsors This…

Polars: the fastest dataframe crate in Rust - with Ritchie Vink

In this episode I speak with Ritchie Vink, the author of Polars, a crate that is the fastest dataframe library at date of speaking:) If you want to participate to an amazing Rust open source project, this is your change to collaborate to…

Apache Arrow, Ballista and Big Data in Rust with Andy Grove

Do you want to know the latest in big data analytics frameworks? Have you ever heard of Apache Arrow? Rust? Ballista? In this episode I speak with Andy Grove one of the main authors of Apache Arrow and Ballista compute engine.Andy explains…

Pandas vs Rust

Pandas is the de-facto standard for data loading and manipulation. Python is the de-facto programming language for such operations. Rust is the underdog. Or is it?In this episode I am showing you why that is no longer the case. Our…

Concurrent is not parallel - Part 2

In plain English, concurrent and parallel are synonyms. Not for a CPU. And definitely not for programmers. In this episode I summarize the ways to parallelize on different architectures and operating systems. Rock-star data scientists must…

Concurrent is not parallel - Part 1

In plain English, concurrent and parallel are synonyms. Not for a CPU. And definitely not for programmers. In this episode I summarize the ways to parallelize on different architectures and operating systems. Rock-star data scientists must…

Backend technologies for machine learning in production

This is one of the most dynamic and fascinating topics: API technologies for machine learning. It's always fun to build ML models. But how about serving them in the real world? In this episode I speak about three must-know technologies to…

You are the product

In this episode I am with George Hosu from Cerebralab and we speak about how dangerous it is not to pay for the services you use, and as a consequence how dangerous it is letting an algorithm decide what you like or not. Our Sponsors This…

How to reinvent banking and finance with data and technology

The financial system is changing. It is becoming more efficient and integrated with many more services making our life more... digital. Is the old banking system doomed to fail? Or will it just be disrupted by the smaller players of the…

What's up with WhatsApp?

Have you clicked the button? Accepted the new terms? It's time we have a talk.

Is Rust flexible enough for a flexible data model?

In this podcast I get inspired by Paul Done's presentation about The Six Principles for Building Robust Yet Flexible Shared Data Applications, and show how powerful of a language Rust is while still maintaining the flexibility of less…

Is Apple M1 good for machine learning?

In this episode I explain the basics of computer architecture and introduce some features of the Apple M1 Is it good for Machine Learning tasks? References Computer architectures book Performance

Rust and deep learning with Daniel McKenna

In this episode I speak with Daniel McKenna about Rust, machine learning and artificial intelligence. You can find Daniel from Don't forget to come join me in our Discord channel speaking about all things data science. Subscribe to the…

Scaling machine learning with clusters and GPUs

Let's finish this year with an amazing episode about scaling ML with clusters and GPUs. Kind of as a continuation of Episode 112 I have a terrific conversation with Aaron Richter from Saturn Cloud about, well, making ML faster and scaling…

What is data ethics?

What is data ethics? In this episode I have an interesting chat with Denny Wong from FaqBot and Muna. Our Sponsor Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain…

A Standard for the Python Array API

Our Links Come join me in our Discord channel speaking about all things data science. Subscribe to the official Newsletter and never miss an episode Follow me on Twitch during my live coding sessions usually in Rust and Python Our Sponsors…

What happens to data transfer after Schrems II?

In this episode Adam Leon Smith, CTO of DragonFly and expert in data regulations explains some of the consequences of Schrems II and data transfers from EU to US. For very interesting references and a practical example, subscribe to our…

Test-First Machine Learning

Our Links Come join me in our Discord channel speaking about all things data science. Subscribe to the official Newsletter and never miss an episode Follow me on Twitch during my live coding sessions usually in Rust and Python Our Sponsors…

Similarity in Machine Learning

Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in Rust and Python Subscribe to the official Newsletter and never miss an episode Our Sponsors…

Distill data and train faster, better, cheaper

Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in Rust and Python Our Sponsors Amethix use advanced Artificial Intelligence and Machine Learning to…

Machine Learning in Rust: Amadeus with Alec Mocatta

Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in Rust and Python Our Sponsors ProtonVPN offers a simple and trusted solution to protect your internet…

Top-3 ways to put machine learning models into production

Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in Rust and Python Our Sponsors physicspodcast.com is not just a physics podcast. But also interviews…

Remove noise from data with deep learning

Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in Rust and Python Our Sponsors ProtonMail is a secure and private email provider that protects…

What is contrastive learning and why it is so powerful?

Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in Rust and Python Our Sponsors The Monday Apps Challenge is bringing developers around the world…

Neural search

Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in Rust and Python This episode is supported by Monday.com The Monday Apps Challenge is bringing…

Let's talk about federated learning

Let's talk about federated learning. Why is it important? Why large organizations are not ready yet? Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in…

How to test machine learning in production

Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in Rust and Python This episode is supported by Monday.com Monday.com bring teams together so you can…

Why synthetic data cannot boost machine learning

Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in Rust and Python This episode is supported by Women in Tech by Manning Conferences

Machine learning in production: best practices [LIVE from twitch.tv]

Hey there! Having the best time of my life;) This is the first episode I record while I am live on my new Twitch channel:) So much fun! Feel free to follow me for the next live streaming. You can also see me coding machine learning stuff…

Testing in machine learning: checking deeplearning models

In this episode I speak with Adam Leon Smith, CTO at DragonFly and expert in testing strategies for software and machine learning.We cover testing with deep learning (neuron coverage, threshold coverage, sign change coverage, layer…

Testing in machine learning: generating tests and data

In this episode I speak with Adam Leon Smith, CTO at DragonFly and expert in testing strategies for software and machine learning. On September 15th there will be a live@Manning Rust conference. In one Rust-full day you will attend many…

Why you care about homomorphic encryption

After deep learning, a new entry is about ready to go on stage. The usual journalists are warming up their keyboards for blogs, news feeds, tweets, in one word, hype.This time it's all about privacy and data confidentiality. The new words…

Test-First machine learning

In this episode I speak about a testing methodology for machine learning models that are supposed to be integrated in production environments. Don't forget to come chat with us in our Discord channel Enjoy the show! -- This episode is…

GPT-3 cannot code (and never will)

The hype around GPT-3 is alarming and gives and provides us with the awful picture of people misunderstanding artificial intelligence. In response to some comments that claim GPT-3 will take developers' jobs, in this episode I express some…

Make Stochastic Gradient Descent Fast Again

There is definitely room for improvement in the family of algorithms of stochastic gradient descent. In this episode I explain a relatively simple method that has shown to improve on the Adam optimizer. But, watch out! This approach does…

What data transformation library should I use? Pandas vs Dask vs Ray vs Modin vs Rapids

In this episode I speak about data transformation frameworks available for the data scientist who writes Python code. The usual suspect is clearly Pandas, as the most widely used library and de-facto standard. However when data volumes…

It’s cold outside. Let’s speak about AI winter

In this episode 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…

Rust and machine learning #4: practical tools

In this episode I make a non exhaustive list of machine learning tools and frameworks, written in Rust. Not all of them are mature enough for production environments. I believe that community effort can change this very quickly. To make a…

Rust and machine learning #3 with Alec Mocatta

In the 3rd episode of Rust and machine learning I speak with Alec Mocatta. Alec is a +20 year experience professional programmer who has been spending time at the interception of distributed systems and data analytics. He's the founder of…

Rust and machine learning #2 with Luca Palmieri

In the second episode of Rust and Machine learning I am speaking with Luca Palmieri, who has been spending a large part of his career at the interception of machine learning and data engineering. In addition, Luca contributed to several…

Rust and machine learning #1

This is the first episode of a series about the Rust programming language and the role it can play in the machine learning field. Rust is one of the most beautiful languages I have ever studied so far. I personally come from the C…

Protecting workers with artificial intelligence (with Sandeep Pandya CEO Everguard.ai)

In this episode I have a chat with Sandeep Pandya, CEO at Everguard.ai a company that uses sensor fusion, computer vision and more to provide safer working environments to workers in heavy industry.Sandeep is a senior executive who can…

Compressing deep learning models: rewinding

As a continuation of the previous episode in this one I cover the topic about compressing deep learning models and explain another simple yet fantastic approach that can lead to much smaller models that still perform as good as the…

Compressing deep learning models: distillation

Using large deep learning models on limited hardware or edge devices is definitely prohibitive. There are methods to compress large models by orders of magnitude and maintain similar accuracy during inference. In this episode I explain one…

Pandemics and the risks of collecting data

Codiv-19 is an emergency. True. Let's just not prepare for another emergency about privacy violation when this one is over. Join our new Slack channel This episode is supported by Proton. You can check them out at protonmail.com or…

Why average can get your predictions very wrong

Whenever people reason about probability of events, they have the tendency to consider average values between two extremes. In this episode I explain why such a way of approximating is wrong and dangerous, with a numerical example. We are…

Activate deep learning neurons faster with Dynamic RELU

In this episode I briefly explain the concept behind activation functions in deep learning. One of the most widely used activation function is the rectified linear unit (ReLU). While there are several flavors of ReLU in the literature, in…

WARNING!! Neural networks can memorize secrets

One of the best features of neural networks and machine learning models is to memorize patterns from training data and apply those to unseen observations. That's where the magic is. However, there are scenarios in which the same machine…

Attacks to machine learning model: inferring ownership of training data

In this episode I explain a very effective technique that allows one to infer the membership of any record at hand to the (private) training dataset used to train the target model. The effectiveness of such technique is due to the fact…

Don't be naive with data anonymization

Masking, obfuscating, stripping, shuffling. All the above techniques try to do one simple thing: keeping the data private while sharing it with third parties. Unfortunately, they are not the silver bullet to confidentiality. All the…

Why sharing real data is dangerous

There are very good reasons why a financial institution should never share their data. Actually, they should never even move their data. Ever.In this episode I explain you why.

Building reproducible machine learning in production

Building reproducible models is essential for all those scenarios in which the lead developer is collaborating with other team members. Reproducibility in machine learning shall not be an art, rather it should be achieved via a methodical…

Bridging the gap between data science and data engineering: metrics

Data science and data engineering are usually two different departments in organisations. Bridging the gap between the two is essential to success. Many times the brilliant applications created by data scientists don't find a match in…

A big welcome to Pryml: faster machine learning applications to production

Why so much silence? Building a company! That's why:) I am building pryml, a platform that allows data scientists build their applications on data they cannot get access to. This is the first of a series of episodes in which I will speak…

It's cold outside. Let's speak about AI winter

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…

The dark side of AI: bias in the machine

This is the fourth and last episode of mini series "The dark side of AI". I am your host Francesco and I’m with Chiara Tonini from London. The title of today’s episode is Bias in the machine C: Francesco, today we are starting with an…

The dark side of AI: metadata and the death of privacy

Get in touch with us Join the discussion about data science, machine learning and artificial intelligence on our Discord server Episode transcript We always hear the word “metadata”, usually in a sentence that goes like this Your Honor, I…

The dark side of AI: recommend and manipulate

In 2017 a research group at the University of Washington did a study on the Black Lives Matter movement on Twitter. They constructed what they call a “shared audience graph” to analyse the different groups of audiences participating in the…

The dark side of AI: social media and the optimization of addiction

Chamath Palihapitiya, former Vice President of User Growth at Facebook, was giving a talk at Stanford University, when he said this: “I feel tremendous guilt. The short-term, dopamine-driven feedback loops that we have created are…

More powerful deep learning with transformers

Some of the most powerful NLP models like BERT and GPT-2 have one thing in common: they all use the transformer architecture. Such architecture is built on top of another important concept already known to the community: self-attention.In…

How to improve the stability of training a GAN

Generative Adversarial Networks or GANs are very powerful tools to generate data. However, training a GAN is not easy. More specifically, GANs suffer of three major issues such as instability of the training procedure, mode collapse and…

What if I train a neural network with random data? (with Stanisław Jastrzębski)

What happens to a neural network trained with random data? Are massive neural networks just lookup tables or do they truly learn something? Today’s episode will be about memorisation and generalisation in deep learning, with Stanislaw…

Deeplearning is easier when it is illustrated (with Jon Krohn)

In this episode I speak with Jon Krohn, author of Deeplearning Illustrated a book that makes deep learning easier to grasp. We also talk about some important guidelines to take into account whenever you implement a deep learning model, how…

How to generate very large images with GANs

Join the discussion on our Discord server In this episode I explain how a research group from the University of Lubeck dominated the curse of dimensionality for the generation of large medical images with GANs. The problem is not as…

More powerful deep learning with transformers

Some of the most powerful NLP models like BERT and GPT-2 have one thing in common: they all use the transformer architecture. Such architecture is built on top of another important concept already known to the community: self-attention.In…

Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan)

Join the discussion on our Discord server In this episode, I am with Aaron Gokaslan, computer vision researcher, AI Resident at Facebook AI Research. Aaron is the author of OpenGPT-2, a parallel NLP model to the most discussed version that…

What is wrong with reinforcement learning?

Join the discussion on our Discord server After reinforcement learning agents doing great at playing Atari video games, Alpha Go, doing financial trading, dealing with language modeling, let me tell you the real story here.In this episode…

Have you met Shannon? Conversation with Jimmy Soni and Rob Goodman about one of the greatest minds in history

Join the discussion on our Discord server In this episode I have an amazing conversation with Jimmy Soni and Rob Goodman, authors of “A mind at play”, a book entirely dedicated to the life and achievements of Claude Shannon. Claude Shannon…

Attacking machine learning for fun and profit (with the authors of SecML Ep. 80)

Join the discussion on our Discord server As ML plays a more and more relevant role in many domains of everyday life, it’s quite obvious to see more and more attacks to ML systems. In this episode we talk about the most popular attacks…

How to scale AI in your organisation

Join the discussion on our Discord server Scaling technology and business processes are not equal. Since the beginning of the enterprise technology, scaling software has been a difficult task to get right inside large organisations. When…

Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan)

Join the discussion on our Discord server In this episode, I am with Aaron Gokaslan, computer vision researcher, AI Resident at Facebook AI Research. Aaron is the author of OpenGPT-2, a parallel NLP model to the most discussed version that…

Training neural networks faster without GPU

Join the discussion on our Discord server Training neural networks faster usually involves the usage of powerful GPUs. In this episode I explain an interesting method from a group of researchers from Google Brain, who can train neural…

How to generate very large images with GANs

Join the discussion on our Discord server In this episode I explain how a research group from the University of Lubeck dominated the curse of dimensionality for the generation of large medical images with GANs. The problem is not as…

Complex video analysis made easy with Videoflow

In this episode I am with Jadiel de Armas, senior software engineer at Disney and author of Videflow, a Python framework that facilitates the quick development of complex video analysis applications and other series-processing based…

Validate neural networks without data with Dr. Charles Martin

In this episode, I am with Dr. Charles Martin from Calculation Consulting a machine learning and data science consulting company based in San Francisco. We speak about the nuts and bolts of deep neural networks and some impressive findings…

How to cluster tabular data with Markov Clustering

In this episode I explain how a community detection algorithm known as Markov clustering can be constructed by combining simple concepts like random walks, graphs, similarity matrix. Moreover, I highlight how one can build a similarity…

Waterfall or Agile? The best methodology for AI and machine learning

The two most widely considered software development models in modern project management are, without any doubt, the Waterfall Methodology and the Agile Methodology. In this episode I make a comparison between the two and explain what I…

Training neural networks faster without GPU

Training neural networks faster usually involves the usage of powerful GPUs. In this episode I explain an interesting method from a group of researchers from Google Brain, who can train neural networks faster by squeezing the hardware to…

Validate neural networks without data with Dr. Charles Martin

In this episode, I am with Dr. Charles Martin from Calculation Consulting a machine learning and data science consulting company based in San Francisco. We speak about the nuts and bolts of deep neural networks and some impressive findings…

Complex video analysis made easy with Videoflow

In this episode I am with Jadiel de Armas, senior software engineer at Disney and author of Videflow, a Python framework that facilitates the quick development of complex video analysis applications and other series-processing based…

AI and the future of banking with Chris Skinner

In this episode I have a wonderful conversation with Chris Skinner. Chris and I recently got in touch at The banking scene 2019, fintech conference recently held in Brussels. During that conference he talked as a real trouble maker…

Classic Computer Science Problems in Python

Today I am with David Kopec, author of Classic Computer Science Problems in Python, published by Manning Publications. His book deepens your knowledge of problem solving techniques from the realm of computer science by challenging you with…

More intelligent machines with self-supervised learning

In this episode I talk about a new paradigm of learning, which can be found a bit blurry and not really different from the other methods we know of, such as supervised and unsupervised learning. The method I introduce here is called…

AI knows biology. Or does it?

The successes of deep learning for text analytics, also introduced in a recent post about sentiment analysis and published here are undeniable. Many other tasks in NLP have also benefitted from the superiority of deep learning methods over…

Get the best shot at NLP sentiment analysis

The rapid diffusion of social media like Facebook and Twitter, and the massive use of different types of forums like Reddit, Quora, etc., is producing an impressive amount of text data every day. There is one specific activity that many…

Financial time series and machine learning

In this episode I speak to Alexandr Honchar, data scientist and owner of blog has written very interesting posts about time series analysis for financial data. His blog is in my personal list of best tutorial blogs. We discuss about…

AI and the future of banking with Chris Skinner

In this episode I have a wonderful conversation with Chris Skinner. Chris and I recently got in touch at The banking scene 2019, fintech conference recently held in Brussels. During that conference he talked as a real trouble maker…

The 4 best use cases of entropy in machine learning

It all starts from physics. The entropy of an isolated system never decreases… Everyone at school, at some point of his life, learned this in his physics class. What does this have to do with machine learning? To find out, listen to the…

Predicting your mouse click (and a crash course in deeplearning)

Deep learning is the future. Get a crash course on deep learning. Now! In this episode I speak to Oliver Zeigermann, author of Deep Learning Crash Course published by Manning Publications at Oliver (Twitter: @DJCordhose) is a veteran of…

How to fool a smart camera with deep learning

In this episode I met three crazy researchers from KULeuven (Belgium) who found a method to fool surveillance cameras and stay hidden just by holding a special t-shirt. We discussed about the technique they used and some consequences of…

There is physics in deep learning!

There is a connection between gradient descent based optimizers and the dynamics of damped harmonic oscillators. What does that mean? We now have a better theory for optimization algorithms.In this episode I explain how all this works. All…

Neural networks with infinite layers

How are differential equations related to neural networks? What are the benefits of re-thinking neural network as a differential equation engine? In this episode we explain all this and we provide some material that is worth learning…

The graph network

Since the beginning of AI in the 1950s and until the 1980s, symbolic AI approaches have dominated the field. These approaches, also known as expert systems, used mathematical symbols to represent objects and the relationship between them…

Beyond deep learning

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…

Reproducible machine learning

In this episode I speak about how important reproducible machine learning pipelines are. When you are collaborating with diverse teams, several tasks will be distributed among different individuals. Everyone will have good reasons to…

Estimating uncertainty with neural networks

Have you ever wanted to get an estimate of the uncertainty of your neural network? Clearly Bayesian modelling provides a solid framework to estimate uncertainty by design. However, there are many realistic cases in which Bayesian sampling…

why do machine learning models fail?

The success of a machine learning model depends on several factors and events. True generalization to data that the model has never seen before is more a chimera than a reality. But under specific conditions a well trained machine learning…

Decentralized machine learning in the data marketplace (part 2)

In this episode I am completing the explanation about the integration fitchain-oceanprotocol that allows secure on-premise compute to operate in the decentralized data marketplace designed by Ocean Protocol. As mentioned in the show, this…

Decentralized machine learning in the data marketplace

In this episode I briefly explain how two massive technologies have been merged in 2018 (work in progress:) - one providing secure machine learning on isolated data, the other implementing a decentralized data marketplace. In this episode…

The promises of Artificial Intelligence

It's always good to put in perspective all the findings in AI, in order to clear some of the most common misunderstandings and promises. In this episode I make a list of some of the most misleading statements about what artificial…

Coffee, Machine Learning and Blockchain

In this episode - which I advise to consume at night, in a quite place - I speak about private machine learning and blockchain, while I sip a cup of coffee in my home office.There are several reasons why I believe we should start thinking…

Are you 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…

why do machine learning models fail? (Part 2)

In this episode I continue the conversation from the previous one, about failing machine learning models. When data scientists have access to the distributions of training and testing datasets it becomes relatively easy to assess if a…

why do machine learning models fail?

The success of a machine learning model depends on several factors and events. True generalization to data that the model has never seen before is more a chimera than a reality. But under specific conditions a well trained machine learning…

The predictive power of metadata

In this episode I don't talk about data. In fact, I talk about metadata. While many machine learning models rely on certain amounts of data eg. text, images, audio and video, it has been proved how powerful is the signal carried by…

Applied Text Analysis with Python (interview with Rebecca Bilbro)

Today’s episode is about text analysis with python. Python is the de facto standard in machine learning. A large community, a generous choice in the set of libraries, at the price of less performant tasks, sometimes. But overall a decent…

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…

How can deep neural networks reason

Today’s episode will be about deep learning and reasoning. There has been a lot of discussion about the effectiveness of deep learning models and their capability to generalize, not only across domains but also on data that such models…

Deep learning and image compression

Today’s episode will be about deep learning and compression of data, and in particular compressing images. We all know how important compressing data is, reducing the size of digital objects without affecting the quality. As a very general…

What is L1-norm and L2-norm?

In this episode I explain the differences between L1 and L2 regularization that you can find in function minimization in basically any machine learning model.

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…

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…

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…

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…

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…

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…

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…

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…

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…

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…

Neural networks and genetic evolution: an unfeasible approach

Despite what researchers claim about genetic evolution, in this episode we give a realistic view of the field.

Fail your AI company in 9 steps

In order to succeed with artificial intelligence, it is better to know how to fail first. It is easier than you think.Here are 9 easy steps to fail your AI startup.

Towards Artificial General Intelligence: preliminary talk

The enthusiasm for artificial intelligence is raising some concerns especially with respect to some ventured conclusions about what AI can really do and what its direct descendent, artificial general intelligence would be capable of doing…

Techstars accelerator and the culture of fireflies

In the aftermath of the Barclays Accelerator, powered by Techstars experience, one of the most innovative and influential startup accelerators in the world, I’d like to give back to the community lessons learned, including the need for…

Deep Learning and Alzheimer

In this episode I speak about Deep Learning technology applied to Alzheimer disorder prediction. I had a great chat with Saman Sarraf, machine learning engineer at Konica Minolta, former lab manager at the Rotman Research Institute at…

How to become data scientist

In this episode, I speak about the requirements and the skills to become data scientist and join an amazing community that is changing the world with data analyticsa

How to handle imbalanced datasets

In machine learning and data science in general it is very common to deal at some point with imbalanced datasets and class distributions. This is the typical case where the number of observations that belong to one class is significantly…

Why do ensemble methods work?

Ensemble methods have been designed to improve the performance of the single model, when the single model is not very accurate. According to the general definition of ensembling, it consists in building a number of single classifiers and…

Parallelising and distributing Deep Learning

Continuing the discussion of the last two episodes, there is one more aspect of deep learning that I would love to consider and therefore left as a full episode, that is parallelising and distributing deep learning on relatively large…

Additional optimisation strategies for deep learning

In the last episode How to master optimisation in deep learning I explained some of the most challenging tasks of deep learning and some methodologies and algorithms to improve the speed of convergence of a minimisation method for deep…

How to master optimisation in deep learning

The secret behind deep learning is not really a secret. It is function optimisation. What a neural network essentially does, is optimising a function. In this episode I illustrate a number of optimisation methods and explain which one is…

How to completely change your data analytics strategy with deep learning

Over the past few years, neural networks have re-emerged as powerful machine-learning models, reaching state-of-the-art results in several fields like image recognition and speech processing. More recently, neural network models started to…

Machines that learn like humans

Artificial Intelligence allow machines to learn patterns from data. The way humans learn however is different and more efficient. With Lifelong Machine Learning, machines can learn the way human beings do, faster, and more efficiently

Protecting privacy and confidentiality in data and communications

Talking about security of communication and privacy is never enough, especially when political instabilities are driving leaders towards decisions that will affect people on a global scale

2017 Predictions in Data Science

We strongly believe 2017 will be a very interesting year for data science and artificial intelligence. Let me tell you what I expect and why.

Statistical analysis of phenomena that smell like chaos

Is the market really predictable? How do stock prices increase? What is their dynamics? Here is what I think about the magics and the reality of predictions applied to markets and the stock exchange.

The minimum required by a data scientist

Why the job of the data scientist can disappear soon. What is required by a data scientist to survive inflation.

Data Science and Fraud Detection at iZettle

Data science is making the difference also in fraud detection. In this episode I have a conversation with an expert in the field, Engineer Eyad Sibai, who works at iZettle, a fraud detection company

EU Regulations and the rise of Data Hijackers

Extracting knowledge from large datasets with large number of variables is always tricky. Dimensionality reduction helps in analyzing high dimensional data, still maintaining most of the information hidden behind complexity. Here are some…

Representative Subsets For Big Data Learning

How would you perform accurate classification on a very large dataset by just looking at a sample of it

History and applications of Deep Learning

What is deep learning?If you have no patience, deep learning is the result of training many layers of non-linear processing units for feature extraction and data transformation e.g. from pixel, to edges, to shapes, to object…

Markov Chain Montecarlo with full conditionals

At some point, statistical problems need sampling. Sampling consists in generating observations from a specific distribution.

Frequentists and Bayesians

There are statisticians and data scientists... Among statisticians, there are some who just count. Some others who… think differently. In this show we explore the old time dilemma between frequentists and bayesians.Given a statistical…

30 min with data scientist Sebastian Raschka

In this show I interview Sebastian Raschka, data scientist and author of Python Machine Learning.In addition to the fun we had offline, there are great elements about machine learning, data science, current and future trends, to keep an…

How to be data scientist

In this episode, we tell you how to become data scientist and join an amazing community that is changing the world with data analytics.

Development and Testing Practices in Data Science

Should data scientists follow the old good practices of software engineering? Data scientists make software after all.

Predictions in Data Science for 2016

It’s time to experiment with Data Science at home. Since we are still dealing with our hosting service, consider the first episode purely experimental, even though the content might be of your interest, no matter what.

BigData on your desk

Have you ever thought to get a Big Data infrastructure on your desk? That’s right! On your desk.

Networks and Graph Databases

Have you ever thought to get a Big Data infrastructure on your desk? That’s right! On your desk.

Data Science and Bio-Inspired Algorithms

In this episode I meet Dr Eliseo Ferrante, formerly at the University of Leuven, currently researcher at the Université de Technologie de Compiègne, who studies self-organization and evolution.