Redefining AI: The Award Winning Tech Podcast

In this video episode, Alysia Silberg - Unemployable - How AI Transformed My Work and Life- ⁠⁠⁠Lauren Hawker Zafer⁠⁠⁠ is joined by Alysia Silberg⁠ Who is Alysia Silberg? Alysia Silberg is a cross between a survivalist and an industrialist – someone who has had to innovate and use whatever resources are available because they had to, and someone who sees opportunities in the marketplace and capitalizes on those. Alysia was born to blaze trails. As the daughter of a Hollywood makeup artist who worked with screen legends like Marilyn Monroe, Natalie Wood, and Marlon Brando, she grew up with a dream of making her own mark in a world far away. A math and science prodigy, she nurtured her entrepreneurial instincts while still in grade school, starting her first business, an import-export agency, at age 11. Today, Alysia is a leading venture capitalist in Silicon Valley, where she mentors tech startups and helps them go public. She is CEO & General Partner of the investment firm Street Global. As a thought-and-knowledge leader, Alysia earned acclaim for her groundbreaking online radio show, Global Fireside Chats, bringing together global industry titans to share insights on our fast-changing world.  She is a UN Women Empower Women Global Champion, and an international board director with sovereign wealth fund experience. Alysia’s recently released first book, Unemployable: How AI Transformed My Work and Life details her harrowing and inspiring life story and is a guide to infinite success and personal development. Why this episode? 🤝 Empowerment and Possibility: Be part of a conversation that celebrates the limitless possibilities when humans leverage AI as a tool for personal and collective empowerment. Discover how AI isn't just a technological advancement but a catalyst for positive change and growth. #ai #techpodcast #futureofwork #prediction 

In this Episode, Alysia Silberg - Unemployable - How AI Transformed My Work and Life- ⁠⁠Lauren Hawker Zafer⁠⁠ is joined by Alysia Silberg Who is Alysia Silberg? Alysia Silberg is a cross between a survivalist and an industrialist – someone who has had to innovate and use whatever resources are available because they had to, and someone who sees opportunities in the marketplace and capitalizes on those. Alysia was born to blaze trails. As the daughter of a Hollywood makeup artist who worked with screen legends like Marilyn Monroe, Natalie Wood, and Marlon Brando, she grew up with a dream of making her own mark in a world far away. A math and science prodigy, she nurtured her entrepreneurial instincts while still in grade school, starting her first business, an import-export agency, at age 11. Today, Alysia is a leading venture capitalist in Silicon Valley, where she mentors tech startups and helps them go public. She is CEO & General Partner of the investment firm Street Global. As a thought-and-knowledge leader, Alysia earned acclaim for her groundbreaking online radio show, Global Fireside Chats, bringing together global industry titans to share insights on our fast-changing world.  She is a UN Women Empower Women Global Champion, and an international board director with sovereign wealth fund experience. Alysia’s recently released first book, Unemployable: How AI Transformed My Work and Life details her harrowing and inspiring life story and is a guide to infinite success and personal development. Why this episode? 🤝 Empowerment and Possibility: Be part of a conversation that celebrates the limitless possibilities when humans leverage AI as a tool for personal and collective empowerment. Discover how AI isn't just a technological advancement but a catalyst for positive change and growth. #ai #techpodcast #futureofwork #prediction

Spotlight Twenty One is a snippet from our upcoming episode: Alysia Silberg - Unemployable - How AI Transformed My Work and My Life. Who is Alysia Silberg? Alysia Silberg is a cross between a survivalist and an industrialist – someone who has had to innovate and use whatever resources are available because they had to, and someone who sees opportunities in the marketplace and capitalizes on those. Alysia was born to blaze trails. As the daughter of a Hollywood makeup artist who worked with screen legends like Marilyn Monroe, Natalie Wood, and Marlon Brando, she grew up with a dream of making her own mark in a world far away. A math and science prodigy, she nurtured her entrepreneurial instincts while still in grade school, starting her first business, an import-export agency, at age 11. Today, Alysia is a leading venture capitalist in Silicon Valley, where she mentors tech startups and helps them go public. She is CEO & General Partner of the investment firm Street Global. As a thought-and-knowledge leader, Alysia earned acclaim for her groundbreaking online radio show, Global Fireside Chats, bringing together global industry titans to share insights on our fast-changing world. She is a UN Women Empower Women Global Champion, and an international board director with sovereign wealth fund experience. Alysia’s recently released first book, Unemployable: How AI Transformed My Work and Life details her harrowing and inspiring life story and is a guide to infinite success and personal development. Listen to the full episode, as soon as it comes out by subscribing to Redefining AI and please do share your excitement about the episode with your own network! #automation #ai #techpodcast #futureofwork

This is the video episode of our audio podcast conversation: How to Use Retrieval Augmented Generation(RAG) in an Enterprise Setting with Dr. Moritz Müller Who is Dr. Moritz Müller? Dr. Moritz Müller currently focuses on delivering successful digital transformation projects to corporate clients in financial services, manufacturing, the public sectors for Squirro in APAC.  With a PhD in Geophysics and extensive work experience in oil & gas exploration, as well as IT project implementation exposure, he has a strong technical background to support the use of emerging technologies in enterprise settings. What is Retrieval Augmented Generation (RAG)? Retrieval-augmented generation refers to a combination of two powerful natural language processing techniques: retrieval-based models and generative models. The approach is gaining significance and increasing attention for several reasons: Improved Content Generation: retrieval-augmented generation allows generative models to access and integrate information from a broader context. By retrieving relevant information from a database or the internet, generative models can produce more accurate, coherent, and contextually relevant content. Better Understanding and Contextualization: retrieval helps generative models understand the context and topic more comprehensively. It enables the model to draw upon a wide range of knowledge sources, which is particularly important when dealing with complex or specialized topics. Enhanced Abstraction and Creativity: by combining retrieval and generation, AI models can exhibit both the creativity of generative models and the grounded information retrieval capabilities. This leads to more creative content generation while maintaining accuracy. This episode is also available as an audio option. Join Dr. Moritz Müller and our host Lauren Hawker Zafer to discover what RAG is and how it can be used in an enterprise setting.

In this Episode, Dr. Moritz Müller - How to Use Retrieval Augmented Generation (RAG) in an Enterprise Setting - ⁠Lauren Hawker Zafer⁠ is joined by Dr. Moritz Müller Who is Dr. Moritz Müller? Dr. Moritz Müller currently focuses on delivering successful digital transformation projects to corporate clients in financial services, manufacturing, the public sectors for Squirro in APAC.With a PhD in Geophysics and extensive work experience in oil & gas exploration, as well as IT project implementation exposure, he has a strong technical background to support the use of emerging technologies in enterprise settings. What is Retrieval Augmented Generation (RAG)? Retrieval-augmented generation refers to a combination of two powerful natural language processing techniques: retrieval-based models and generative models. The approach is gaining significance and increasing attention for several reasons: Improved Content Generation: retrieval-augmented generation allows generative models to access and integrate information from a broader context. By retrieving relevant information from a database or the internet, generative models can produce more accurate, coherent, and contextually relevant content. Better Understanding and Contextualization: retrieval helps generative models understand the context and topic more comprehensively. It enables the model to draw upon a wide range of knowledge sources, which is particularly important when dealing with complex or specialized topics. Enhanced Abstraction and Creativity: by combining retrieval and generation, AI models can exhibit both the creativity of generative models and the grounded information retrieval capabilities. This leads to more creative content generation while maintaining accuracy. This episode will also be available as a video episode and can be accessed both as a video and audio file.  Join Dr. Moritz Müller and our host Lauren Hawker Zafer to discover what RAG is and how it can be used in an enterprise setting. #retrievalaugmentedgeneration #ai #techpodcast #llms #generativeai

Spotlight Twenty is a snippet from our upcoming episode: How to Use Retrieval Augmented Generation (RAG) in an Enterprise Setting Listen to the full episode, as soon as it comes out by subscribing to Redefining AI. What is Retrieval Augmented Generation (RAG)? Retrieval-augmented generation refers to a combination of two powerful natural language processing techniques: retrieval-based models and generative models. The approach is gaining significance and increasing attention for several reasons: Improved Content Generation: Retrieval-augmented generation allows generative models to access and integrate information from a broader context. By retrieving relevant information from a database or the internet, generative models can produce more accurate, coherent, and contextually relevant content. Better Understanding and Contextualization: Retrieval helps generative models understand the context and topic more comprehensively. It enables the model to draw upon a wide range of knowledge sources, which is particularly important when dealing with complex or specialized topics. Enhanced Abstraction and Creativity: By combining retrieval and generation, AI models can exhibit both the creativity of generative models and the grounded information retrieval capabilities. This leads to more creative content generation while maintaining accuracy. This episode will also be available as a video episode and can be accessed both as a video and audio file. Join Dr. Moritz Müller and our host Lauren Hawker Zafer to discover what RAG is and how it can be used in an enterprise setting. #retrievalaugmentedgeneration #ai #techpodcast

In this Episode, Juliette Powell & Art Kleiner - The AI Dilemma - 7 Principles for Responsible Technology - Lauren Hawker Zafer is joined by Juliette Powell & Art Kleiner Who are Juliette Powell & Art Kleiner? Juliette Powell is an author, a television creator with 9,000 live shows under her belt, and a technologist and sociologist.  She is also a commentator on Bloomberg TV/ Business News Networks and a speaker at conferences organized by the Economist and the International Finance Corporation. Her TED talk has 130K views on YouTube.  Juliette identifies the patterns and practices of successful business leaders who bank on ethical AI and data to win. She is on faculty at NYU's ITP where she teaches four courses, including Design Skills for Responsible Media, a course based on her book. Art Kleiner is a writer, editor and futurist. His books include The Age of Heretics, Who Really Matters, Privilege and Success, and The Wise. He was editor of strategy+business, the award-winning magazine published by PwC.  Art is also a longstanding faculty member at NYU-ITP and IMA, where his courses include co-teaching Responsible Technology and the Future of Media. Why this Episode?🎙️ Embark on a voyage into the moral depths of AI!  Join us on Redefining AI as we unravel the profound wisdom within "The AI Dilemma - 7 Principles for Responsible Technology."  Authors Juliette Powell and Art Kleiner illuminate the path to ethical AI practices. Who should heed this tome, and what worldly wisdom can they weave into their daily tapestry?  Plunge into the enigma of the "closed box"—can we unveil AI's secrets and whom shall it serve? Can and how can non-technical souls challenge the norm - discover the alchemy of transforming "closed-box" entities into open-hearted pioneers.  Unearth the magic of "creative friction"—can we break free from the siren song of seamless experiences? Don't miss this captivating conversation! #AIethics #TechResponsibility #RedefiningAI #TechPodcast #AIRevolution

Spotlight Nineteen is a snippet from our upcoming episode: Juliette Powell & Art Kleiner - The AI Dilemma - 7 Principles for Responsible Technology. Listen to the full episode, as soon as it comes out by subscribing to Redefining AI. Who are Juliette Powell & Art Kleiner? Juliette Powell is an author, a television creator with 9,000 live shows under her belt, and a technologist and sociologist. She is also a commentator on Bloomberg TV/ Business News Networks and a speaker at conferences organized by the Economist and the International Finance Corporation. Her TED talk has 130K views on YouTube. Juliette identifies the patterns and practices of successful business leaders who bank on ethical AI and data to win. She is on faculty at NYU's ITP where she teaches four courses, including Design Skills for Responsible Media, a course based on her book. Art Kleiner is a writer, editor and futurist. His books include The Age of Heretics, Who Really Matters, Privilege and Success, and The Wise. He was editor of strategy+business, the award-winning magazine published by PwC.  Art is also a longstanding faculty member at NYU-ITP and IMA, where his courses include co-teaching Responsible Technology and the Future of Media. Why this Episode?🎙️ Embark on a voyage into the moral depths of AI! Join us on Redefining AI as we unravel the profound wisdom within "The AI Dilemma - 7 Principles for Responsible Technology." Authors Juliette Powell and Art Kleiner illuminate the path to ethical AI practices. Who should heed this tome, and what worldly wisdom can they weave into their daily tapestry? Plunge into the enigma of the "closed box"—can we unveil AI's secrets and whom shall it serve? Can and how can non-technical souls challenge the norm - discover the alchemy of transforming "closed-box" entities into open-hearted pioneers. Unearth the magic of "creative friction"—can we break free from the siren song of seamless experiences? Don't miss this captivating conversation! #AIethics #TechResponsibility #RedefiningAI #TechPodcast #AIRevolution

In this Episode Open Source Unleashed: A Conversation on the Power of Community-Driven Tech Lauren Hawker Zafer is joined by Piero Molino PhD Who is Piero Molino PhD? Piero Molino, Ph.D., is CEO and co-founder of Predibase, a low-code AI platform that makes it easy for engineers to build, optimize and deploy state-of-the-art models - from linear regressions to large language models - with just a few lines of code.  He previously worked as a research scientist exploring machine learning and natural language processing at Stanford University, Yahoo, IBM Watson, Geometric Intelligence, and Uber, where he was a founding member of the Uber AI organization.  He is the creator of Ludwig, a Linux-Foundation-backed open-source declarative deep learning framework with more than 9000 stars on GitHub. Why this Episode? Dive into the world of AI democratization with our latest podcast episode featuring Piero Molino PhD, CEO of Predibase! Join host Lauren Hawker Zafer as she discusses intriguing facts about the world of AI that will captivate tech enthusiasts and novices alike. Discover the secrets behind "Ludwig" and learn how this open-source project is revolutionizing AI democratization. Explore the concept of universal access to AI technologies and how it benefits users who crave free access to cutting-edge tools. Piero unveils the shift in the AI landscape, where data collection and labeling are no longer the initial hurdles. Explore the implications of this transformation on the democratization of AI and the security measures in place to protect sensitive data. Find out how smaller organizations and individual developers are now empowered to harness the power of AI models through user-friendly APIs. Uncover the integration of classic machine learning techniques with large language models and how it's becoming accessible to a broader audience. Get a glimpse of the evolving role of digital assistants in the tech world and how they fit into the changing dynamics of AI democratization.  Don't miss out on real-world examples of AI in action, from text classification to information extraction, and the transition from structured to unstructured data.  Join us on this captivating journey through the exciting landscape of AI democratization. Tune in now to redefine your understanding of AI! 🚀🤖 #RedefiningAI #TechPodcast #AIRevolution REDEFINING AI is powered by The Squirro Academy - learn.squirro.com. Try our free courses on AI, ML, NLP and Cognitive Search at the Squirro Academy and find out more about Squirro here!

Spotlight Eighteen is a snippet from our upcoming episode: Piero Molino - Open Source Unleashed: A Conversation on the Power of Community-Driven Tech Listen to the full episode, as soon as it comes out by subscribing to Redefining AI. Who is Piero Molino PhD? Piero Molino, Ph.D., is CEO and co-founder of Predibase, a low-code AI platform that makes it easy for engineers to build, optimize and deploy state-of-the-art models - from linear regressions to large language models - with just a few lines of code. He previously worked as a research scientist exploring machine learning and natural language processing at Stanford University, Yahoo, IBM Watson, Geometric Intelligence, and Uber, where he was a founding member of the Uber AI organization. He is the creator of Ludwig, a Linux-Foundation-backed open-source declarative deep learning framework with more than 9000 stars on GitHub. Why this Episode? Dive into the world of AI democratization with our latest podcast episode featuring Piero Molino PhD, CEO of Predibase! Join host Lauren Hawker Zafer as she discusses intriguing facts about the world of AI that will captivate tech enthusiasts and novices alike. Discover the secrets behind "Ludwig" and learn how this open-source project is revolutionizing AI democratization. Explore the concept of universal access to AI technologies and how it benefits users who crave free access to cutting-edge tools. Piero unveils the shift in the AI landscape, where data collection and labeling are no longer the initial hurdles. Explore the implications of this transformation on the democratization of AI and the security measures in place to protect sensitive data. Find out how smaller organizations and individual developers are now empowered to harness the power of AI models through user-friendly APIs. Uncover the integration of classic machine learning techniques with large language models and how it's becoming accessible to a broader audience. Get a glimpse of the evolving role of digital assistants in the tech world and how they fit into the changing dynamics of AI democratization. Don't miss out on real-world examples of AI in action, from text classification to information extraction, and the transition from structured to unstructured data. Join us on this captivating journey through the exciting landscape of AI democratization. Tune in now to redefine your understanding of AI! 🚀🤖 #RedefiningAI #TechPodcast #AIRevolution