Practical AI
Practical AI LLC
Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more).
The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!
The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!
Episodes
Mentioned books
Sep 17, 2019 • 48min
Worlds are colliding - AI and HPC
Chris Benson, Principal AI Strategist at Lockheed Martin, dives into the fascinating world where High Performance Computing (HPC) meets AI. He explains how HPC outshines traditional infrastructure and shares unique challenges in combining the two. The conversation highlights the complexity of HPC clusters and the environmental impact of machine learning models. Chris also emphasizes the evolving relationship between AI/ML and HPC, showcasing the importance of strategic partnerships in advancing technology.
Sep 9, 2019 • 59min
AutoML and AI at Google
Sherol Chen, a machine learning developer at Google, shares her journey into AI, starting from her childhood passion for gaming. She dives into how different AI teams within Google collaborate and explains the practical applications of AutoML. Listeners will learn step-by-step how to get started with AutoML, including dataset preparation and model training. Sherol also highlights the balance between user-friendly interfaces and technical expertise, making AI more accessible.
Aug 26, 2019 • 56min
On being humAIn
David Yakobovitch, a principal data scientist at Galvanize and host of the HumAIn podcast, dives deep into the evolution of data science and the tools shaping its future. He shares insights from his journey from math competitions to AI, emphasizing the importance of practical skills in tech education. The conversation highlights the need for empathetic design in AI as automation reshapes job markets, and explores how human-centered approaches can bridge the gap between technology and society.
Aug 12, 2019 • 46min
Serving deep learning models with RedisAI
Pieter Cailliau, a Senior Product Manager at Redis Labs, dives into the world of RedisAI and its groundbreaking applications. He explains how RedisAI integrates deep learning models into the Redis ecosystem, enhancing AI deployment efficiency. The discussion also covers Redis's versatility as an open-source database and shares insights on using RedisAI for chatbot conversation management and dynamic knowledge graphs. Pieter emphasizes community involvement in developing RedisAI, inviting developers to contribute and collaborate for future advancements.
Jul 30, 2019 • 55min
AI-driven studies of the ancient world and good GANs
Explore how AI is revolutionizing the study of ancient civilizations, with exciting advancements in deciphering long-lost languages. Dive into the world of Generative Adversarial Networks (GANs) and their unexpected applications, such as improving cancer detection. The hosts share insights on AI in gaming, discussing AI bots designed for fairness. Plus, discover valuable resources for leveling up your AI skills and strategies to align AI learning more closely with human capabilities.
Jul 19, 2019 • 53min
AI code that facilitates good science
Joel Grus, author of 'Data Science from Scratch' and senior research engineer at the Allen Institute for AI, chats about his journey into AI and data science. He shares insights on the importance of coding best practices and how tools like Jupyter Notebooks can enhance collaboration. The conversation also delves into the exciting AI projects at AI2, such as Aristo and Mosaic, and the role of open-source initiatives like AllenNLP in advancing research. Plus, get tips for writing clean, maintainable code in machine learning!
Jul 3, 2019 • 51min
Celebrating episode 50 and the neural net!
The hosts celebrate a milestone while diving into the exciting world of neural networks. They share personal experiences and the evolution of AI, marking key milestones in neural network development. Various perspectives on AI are explored, emphasizing the practical tools like Jupyter Notebooks for data teams. The discussion makes complex concepts accessible, detailing how neural networks learn and adapt. Listeners are encouraged to engage with rich resources for further exploration of AI and machine learning. Join this lively conversation about the future of technology!
Jun 25, 2019 • 55min
Exposing the deception of DeepFakes
Delve into the unsettling world of deepfake technology and its dangerous implications for truth in media. Learn how these manipulated videos can influence public perception and pose risks in political contexts. The discussion highlights the challenges of detecting deepfakes and the need for legislative measures to combat misinformation. Gain insights on safeguarding against these threats while exploring the dual nature of AI technology in both positive and negative applications. It's a vital conversation about a modern menace that everyone should hear.
Jun 17, 2019 • 44min
Model inspection and interpretation at Seldon
Janis Klaise, a data scientist at Seldon, sheds light on the complexities of model interpretation in AI. He discusses the significance of the Alibi open-source project, designed to make sense of intricate models. Key topics include the integration of Alibi into Seldon’s platform for enhanced explainability, the use of innovative techniques like LIME, and the challenges of deploying machine learning models in real-world scenarios. Janis emphasizes the importance of collaboration between engineering and data science to improve AI's accessibility.
Jun 11, 2019 • 52min
GANs, RL, and transfer learning oh my!
Delve into the fascinating world of generative adversarial networks (GANs) and uncover how they create stunning artworks and music. Explore the power of deep reinforcement learning, where machines learn to navigate complex environments through rewards. Discover the magic of transfer learning, enabling AI models to adapt with minimal data in fields like computer vision. The discussion is enriched by ethical considerations and the human touch needed in AI, making this a captivating journey through the realms of creativity and technology.
