Coded bias, intersectionality in AI, and computer vision: Founder of the Algorithmic Justice League Joy Buolamwini talks to host Jon Krohn about the impact of exclusion and inclusion in datasets, the need to address intersectionality when identifying racial, age, or gender-based prejudice in machine learning tools, protections for artists and creative practitioners against AI, and the role that AI may have in combating systemic racism.

This episode is brought to you by Gurobi (https://gurobi.com/sds), the Decision Intelligence Leader, and by CloudWolf (https://www.cloudwolf.com/sds), the Cloud Skills platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• What coded bias is [06:49]
• The problem with bias in machine learning datasets [18:41]
• The Incoding Movement [42:08]
• About the Pilot Parliaments Benchmark [52:07]
• Ethics and the future of AI [1:20:10]
• The potential for AI to end systemic racism [1:32:59]

Additional materials: www.superdatascience.com/727

The Super Data Science Podcast: Machine Learning | AI | Success

727: Unmasking A.I. Injustice, with Dr. Joy Buolamwini

Chaque année, les équipes du Loria s'enrichissent avec l'arrivée de nouveaux chercheurs et enseignants-chercheurs. Nous leur souhaitons la bienvenue et nous vous invitons à découvrir en quelques minutes leurs parcours et projets !

Vincent Gaudillière est spécialiste en vision par ordinateur et nouveau Maître de Conférences de l’Université de Lorraine. Il enseigne à la Faculté des Sciences et Technologies et mène ses travaux de recherche au Loria, dans l’équipe Tangram depuis septembre 2024.

Il s’intéresse au problème de l’identification automatique du point de vue d’une caméra à partir des éléments présents dans une image. Dans ses travaux actuels, il intègre l’utilisation de grands modèles vision-langage pour soumettre les images à des analyses multimodales. Celles-ci, combinées éventuellement à des analyses purement visuelles, lui permettent d’envisager une étude des images plus précise et efficace, notamment lorsqu’il s’agit d’environnements complexes et inconnus. 

Originaire de Dijon, son parcours professionnel l’a fait passer par Grenoble, Lausanne, Nancy et le Luxembourg, avant de retourner à Nancy, en tant que membre permanent du Loria.

Découvrez dans ce podcast son parcours et ses recherches.

Bienvenue à bord ! - Interview de Vincent Gaudillière

Welcome to AI with Shaily, hosted by Shailendra Kumar, where the latest breakthroughs in artificial intelligence are explored with enthusiasm and insight! 🎙️ Today’s episode dives into an exciting intersection of AI and baseball, showcasing how technology is revolutionizing the sport in ways you might never have imagined. ⚾🤖

Shailendra introduces a remarkable AI-powered tool developed by PitcherNet that’s currently being used by the Baltimore Orioles. What makes this tool extraordinary is its ability to analyze pitch velocity and precisely identify the release point of a pitcher’s throw using just smartphone footage. 📱✨ Traditionally, teams relied on expensive, stadium-grade systems like Hawk-Eye, which come with hefty price tags. But now, thanks to AI, similar high-quality insights can be gleaned from everyday videos captured on a simple phone camera. This is a huge leap toward making advanced sports analytics accessible to everyone! 💡💸

One of the biggest challenges in analyzing baseball pitches is motion blur—fast-moving balls often appear blurry on low-resolution video, making it hard to study the mechanics. Yet, PitcherNet’s AI uses sophisticated computer vision techniques to penetrate this blur, extracting detailed data about player biomechanics and pitching mechanics. This isn’t just a win for Major League Baseball stars; it’s a game-changer for scouts and coaches at the minor league and college levels who previously lacked access to such technology. Now, scouting and coaching can happen anywhere, anytime, with just a smartphone in hand. 🌍📊

Shaily emphasizes how this democratization of sports technology is more than a fleeting trend. With the Orioles investing joint funding to expand this tech in 2025, it’s clear that AI is becoming a vital tool not only for enhancing performance but also for preventing injuries by closely monitoring player mechanics. 🏥⚙️

For coaches and scouts working with limited resources, Shailendra offers practical advice: start recording regular practice sessions with your phone and experiment with motion analysis apps. Even if you don’t have access to PitcherNet’s system, adopting video-based biomechanical assessments can help uncover hidden potential in athletes and reduce injury risks. 🎥📈

To spark further thought, Shaily invites listeners to imagine other sports or fields where this kind of low-cost, AI-driven innovation could take hold. The idea of turning everyday devices into powerful analytical tools opens a world of possibilities beyond baseball. 🌟🤔

Closing the episode, Shailendra shares an inspiring quote from Steve Jobs: "Technology alone is not enough. It’s technology married with liberal arts, married with the humanities, that yields us the results that make our hearts sing." This reminds us that human creativity combined with AI’s capabilities is the true driver of meaningful progress. ❤️🧠

Don’t forget to follow Shailendra Kumar on YouTube, Twitter, LinkedIn, and Medium for more cutting-edge AI news and insights. Subscribe to AI with Shaily and share your thoughts on how AI is reshaping your favorite sport or hobby—Shaily loves hearing from his audience! 📲💬

This has been AI with Shaily, bringing the future right to your ears. Until next time, keep exploring the amazing world of AI! 🚀🎧

AI at the Ballpark: How Smartphones and AI Are Revolutionizing Baseball Scouting

Welcome to your Weekly AI News Roundup! 🤖 Hosted by Shailendra Kumar (Shaily), this week’s episode (Week starting March 23, 2025) is packed with the latest machine learning developments and deep learning breakthroughs reshaping industries worldwide.

We kick off with Databricks unveiling Databricks One—a groundbreaking platform putting data analytics and Artificial Intelligence in the hands of everyone (not just techies!), radically accelerating business innovation. 🏢 Shaily explores how this democratization lets every employee use AI-driven analytics, upping your team’s data intelligence.

Next, we spotlight CVPR 2025’s advances in 3D evaluation and computer vision—from smarter robots to autonomous vehicles, AI is bridging the gap between perception and decision-making. For researchers and developers, Frontiers research into neural network sharpness and black-box adversarial attacks brings vital insights on making AI models more robust and reliable.

Machine Learning Week 2025 celebrates how generative AI and predictive AI now work hand-in-hand, transforming fields from finance to healthcare. Special focus lands on healthcare partnerships like X-Chem and Orion Pharma: AI-driven drug discovery is boosting outcomes and speeding up breakthroughs! 💊

Shaily’s expert take? When AI is practical and accessible, real impact follows. || Don’t miss out! Subscribe for crisp, weekly Artificial Intelligence and machine learning updates, and follow for more on YouTube, Twitter, LinkedIn, or Medium. 🚀

🚀 AI News with Shaily for Week starting June 16: Is Databricks One the Key to Democratizing AI?

Hey there! 👋 You’re tuned into *AI with Shaily*, hosted by Shailendra Kumar, your go-to guy for the latest and greatest in artificial intelligence news and breakthroughs. 🤖✨

Shailendra kicks off by sharing a fascinating real-life story: a medical researcher friend showed him an AI-analyzed MRI scan that detected a brain tumor with near-perfect accuracy in just minutes. 🧠🩺 This mind-blowing example highlights how far computer vision has advanced—almost like sci-fi becoming reality!

On August 29, 2025, the AI world buzzed with excitement over major leaps in generative models. These models now create ultra-photorealistic images nearly four times faster than before, enabling stunning, immersive 3D environments for augmented reality (AR) and virtual reality (VR) that rival Hollywood effects. 🌳🎥 Imagine exploring a virtual jungle so real you’d swear you’re there! The secret? Smarter, more controllable AI models pushing the boundaries of creativity and realism.

But it’s not just about eye candy. Inspired by the human brain’s selective focus, researchers developed innovative brain-like adaptive filters called Lp-Convolution methods. 🧠⚙️ These filters are lightweight, adaptable, and super robust—ideal for healthcare robots working in sterile environments or for monitoring endangered animals in the wild. It’s AI doing more with less, perfect for places with limited computing power.

The magic intensifies when visual data merges with semantic and spatial information. Transformers and graph neural networks are joining forces to power everything from self-driving cars 🚗💨 to advanced medical diagnostics. For example, AI frameworks like CE-RS-SBCIT are revolutionizing brain tumor MRI analysis by delivering real-time insights and optimizing treatment plans, including precise cardiac ablation procedures. Meanwhile, OccluNet’s breakthrough in detecting blocked vessels speeds up emergency care, potentially saving countless lives. 🚑❤️

AI’s impact stretches beyond healthcare too! In agriculture and environmental science, AI-driven remote sensing acts like a supercharged farmer’s eye, spotting pests and diseases early to protect crops and support global reforestation efforts. 🌾🌍 Plus, adaptable models like ADAPT and BioTune help AI systems quickly adjust to unpredictable conditions—a game-changer for autonomous vehicles and industrial vision systems navigating the chaotic real world.

What excites Shailendra most is the shift from theoretical lab work to practical AI tools that operate efficiently with limited resources, emphasize ethical transparency, and truly transform industries. 🌟 It’s AI stepping out of the “black box” and becoming a part of everyday life, touching areas that matter to all of us.

For tech enthusiasts, Shailendra offers a golden nugget: dive into multimodal learning techniques that combine image data with contextual info. This approach significantly boosts model accuracy and resilience—definitely the future of computer vision! 📊🔍

He wraps up with an inspiring quote from AI pioneer Yann LeCun: *"The future of AI is not just making smarter machines, but making machines that help us become smarter humans."* 🤝💡

Don’t forget to follow Shailendra Kumar on YouTube, Twitter, LinkedIn, and Medium by searching for *AI with Shaily* for more cutting-edge AI insights. Subscribe, share your thoughts, and join the conversation about the coolest upcoming uses of computer vision! 🎙️💬

Thanks for listening! Until next time, keep questioning, keep learning, and keep imagining the incredible possibilities AI can bring to all our lives. 🚀🌈

AI with Shaily: How Computer Vision is Revolutionizing Healthcare, Environment, and Beyond

You’re tuning into "AI with Shaily," hosted by Shailendra Kumar, a knowledgeable guide who brings you the freshest and most impactful advancements in artificial intelligence. 🎙️🤖

In this episode, Shaily dives deep into a groundbreaking innovation in computer vision called Lotus. 🌸👁️ This model tackles one of the toughest challenges in AI: dense prediction tasks. These tasks involve estimating detailed pixel-level information like depth and surface normals, which traditionally have been difficult due to inefficiency, the need for enormous datasets, and long training times. ⏳📊

Lotus revolutionizes this by changing how predictions are made. Instead of the common diffusion-based models that generate images by predicting noise step-by-step, Lotus predicts the actual annotations directly — think of it as coloring a complex painting with the exact colors from the start, eliminating guesswork and reducing variance. 🎨✨ This direct annotation approach significantly boosts precision.

What’s truly remarkable is Lotus’s speed: it condenses a process that used to require multiple diffusion steps into just one. This single-step diffusion model is hundreds of times faster than previous models like Marigold, without sacrificing accuracy. 🚀⚡ Shaily, having experienced slow training times himself, emphasizes how this leap in speed and efficiency is a game-changer for AI practitioners.

The model’s success hinges on three key techniques: direct annotation prediction, a one-step diffusion formulation that demands far less training data, and a smart detail-preserving “task switcher” mechanism. 🧠🔧 Using only about 59,000 synthetic images — a tiny fraction compared to the millions other models require — Lotus achieves state-of-the-art zero-shot depth and normal estimation. 📉📈

Why is this important? Beyond its technical sophistication, Lotus unlocks practical applications that could transform industries: autonomous vehicles gaining real-time environmental awareness, augmented reality headsets understanding surroundings better, and robots confidently navigating complex spaces. 🚗🕶️🤖

This breakthrough is the product of collaboration among leading institutions — HKUST (Guangzhou), University of Adelaide, Huawei Noah’s Ark Lab, and HKU — and was recently presented at the prestigious International Conference on Learning Representations (ICLR). 🌍🎓 The AI community is buzzing because Lotus represents a paradigm shift, not just a small step forward in visual perception AI.

Shaily offers a valuable tip for AI enthusiasts and professionals: when evaluating new AI models, look beyond accuracy. Consider efficiency factors like inference speed and training data requirements, as these often dictate real-world usability more than headline accuracy numbers. ⚖️🔍

He closes with inspiration from Alan Turing: “We can only see a short distance ahead, but we can see plenty there that needs to be done.” Lotus embodies this spirit by helping us see further and faster in the field of AI. 🌟🔭

For more AI insights, Shailendra Kumar invites you to follow him on YouTube, Twitter, LinkedIn, and Medium. Don’t forget to subscribe and join the conversation by sharing your thoughts on how faster, more efficient vision AI could reshape our future. 💬📲

Until next time, this is Shaily reminding you to stay curious and inspired on your AI journey! 🌐✨

Lotus: The AI Model Revolutionizing Real-Time Computer Vision

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Le Loria, Laboratoire lorrain de Recherche en Informatique et ses Applications est une Unité Mixte de Recherche (UMR 7503), commune à plusieurs établissements : le CNRS, l’Université de Lorraine et Inria.

Depuis sa création en 1997, le Loria a pour mission la recherche fondamentale et appliquée en sciences informatiques.

Plus d'informations sur notre site : Loria.fr

***

Loria, the Lorraine Laboratory for Research in Computer Science and its Applications, is a Joint Research Unit (UMR 7503), shared by several institutions: the CNRS, the University of Lorraine and Inria.

Since its creation in 1997, Loria's mission is to conduct fundamental and applied research in computer science.

For more information, please visite our website : Loria.fr

Unlock the secrets of data mastery with Shailendra, a 27-year veteran in AI, ML, and Data Science, driving AU$ 6 Billion in transformative value. As the author of 'Making Money out of Data,' their strategies redefine digital success. With expertise honed at IBM and Accenture, they drive innovation and data monetization. Explore how loyalty programs like Flybuys and Everyday Rewards revolutionize business—connect with Shaily today.

InovarTech is a digital transformation consultancy built on the core values of quality, commitment, and perseverance. We utilize Design Thinking and advanced AI technologies, including Vision AI, Agentic AI, and Generative AI, to deliver human-centered, future-ready solutions that address real business challenges.

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

New tracks tagged #Computer Vision