Redefining AI - Artificial Intelligence with Squirro

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

Spotlight Seventeen is a snippet from our upcoming episode: Damien Benveniste PhD - Machine Learning 101. Listen to the full episode, as soon as it comes out by subscribing to Redefining AI. Who is Damien Benveniste PhD? 10 years ago, after a Ph.D. in theoretical Physics, Damien started his career in Machine Learning and Data Science. He has been a Data Scientist, Machine Learning Engineer, and a Software Engineer. In these roles he has led various machine learning projects in diverse industry sectors such as: AdTech, Market Research, Financial Advising, Cloud Management, Online Retail, Marketing, Credit Score Modeling, Data Storage, Healthcare and Energy Valuation. Recently, he was a machine learning tech lead at Meta on the automation at scale of model optimisation for Ads ranking. He is also a machine learning top voice on LinkedIn. At present, Damien focuses on a more entrepreneurial journey where he builds tech businesses and writes about his experience. If you are interested in reading about his experience then check out his newsletter: The AI Edge. Why this Episode? 🎙️ Get ready to embark on an enlightening journey through the world of Machine Learning 101! 🤖 In our upcoming episode, we're diving deep into the fundamental concepts of machine learning and navigating the complexities of this ever-evolving field. Join us as Lauren and Damien explore: 🤔 What confuses people when discussing machine learning, and how can we untangle the web of differences in learning? 🌟 Discover the essential distinctions between supervised, unsupervised, and reinforcement learning, and see how they tackle real-world problems head-on. 🧠 Uncover the secrets of neural networks and explore the magic of CNNs and RNNs in solving diverse problems. 📸 Delve into the world of unstructured data, from images to text and audio, and uncover the challenges and considerations in ML tasks. 📊 Learn how to handpick and evaluate the perfect performance metrics for various machine learning tasks. 🤯 Delve into the trade-offs between model complexity and interpretability, with a spotlight on model explainability in real-world applications. 💡 Explore the ethical considerations and potential risks of deploying machine learning models, and discover how to ensure responsible AI development. 🤖 As well as: can Machines Learn Morality? Dive into the exciting world of ethical reasoning in AI, and uncover the challenges and opportunities that lie ahead. Don't miss this episode where we unravel the fascinating world of Machine Learning 101! Tune in for a journey of knowledge and insight into the heart of artificial intelligence. 🚀 #RedefiningAI #MachineLearning101

In this episode Lauren Hawker Zafer is joined by Damien Benveniste PhD⁠  Who is Damien Benveniste PhD? 10 years ago, after a Ph.D. in theoretical Physics, Damien started his career in Machine Learning and Data Science. He has been a Data Scientist, Machine Learning Engineer, and a Software Engineer. In these roles he has led various machine learning projects in diverse industry sectors such as: AdTech, Market Research, Financial Advising, Cloud Management, Online Retail, Marketing, Credit Score Modeling, Data Storage, Healthcare and Energy Valuation.  Recently, he was a machine learning tech lead at Meta on the automation at scale of model optimisation for Ads ranking. He is also a machine learning top voice on LinkedIn. At present, Damien focuses on a more entrepreneurial journey where he builds tech businesses and writes about his experience. If you are interested in reading about his experience then check out his newsletter: ⁠The AI Edge.⁠ Why this Episode? 🎙️ Get ready to embark on an enlightening journey through the world of Machine Learning 101! 🤖 In our upcoming episode, we're diving deep into the fundamental concepts of machine learning and navigating the complexities of this ever-evolving field.  Join us as Lauren and Damien explore: 🤔 What confuses people when discussing machine learning, and how can we untangle the web of differences in learning? 🌟 Discover the essential distinctions between supervised, unsupervised, and reinforcement learning, and see how they tackle real-world problems head-on. 🧠 Uncover the secrets of neural networks and explore the magic of CNNs and RNNs in solving diverse problems. 📸 Delve into the world of unstructured data, from images to text and audio, and uncover the challenges and considerations in ML tasks. 📊 Learn how to handpick and evaluate the perfect performance metrics for various machine learning tasks. 🤯 Delve into the trade-offs between model complexity and interpretability, with a spotlight on model explainability in real-world applications. 💡 Explore the ethical considerations and potential risks of deploying machine learning models, and discover how to ensure responsible AI development. 🤖 As well as: can Machines Learn Morality? Dive into the exciting world of ethical reasoning in AI, and uncover the challenges and opportunities that lie ahead. Don't miss this episode where we unravel the fascinating world of Machine Learning 101! Tune in for a journey of knowledge and insight into the heart of artificial intelligence. 🚀 #RedefiningAI #MachineLearning101  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.

In this episode Lauren Hawker Zafer is joined by Kyle Harrison Who is Kyle Harrison? Kyle Harrison is a General Partner at Contrary, where he leads Series A and growth-stage investing.  He joined Contrary from Index where he was a Partner, and before that he was a growth investor at Coatue. His portfolio includes iconic startups and public companies including Ramp, Replit, Cohere, Snowflake, and Databricks.  He also regularly shares his analysis on the venture capital landscape via his Substack Investing 101.  Why this Episode? 🎙️ Get ready to dive into the dynamic world of venture and AI on the latest episode of Redefining AI! Join Lauren as she sits down with Kyle Harrison, a General Partner at Contrary Capital, to explore the evolving landscape of AI investments, the balance between open-source and competitive advantage, and the future of accessible technology.  Discover how the journey of accessibility, democratization, and collaboration is shaping the tech industry. Tune in for insights that redefine the AI landscape! 🚀 #RedefiningAI #VentureInnovation 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.