Episodios

  • 35: From Page to Blueprint: Discovering humanity future with AI in science fiction with Rae Muhlstock
    Apr 1 2025

    In this episode of "AI Snacks," Anastassia and Professor Rae Muhlstock explore human nature in the age of AI through the lens of science fiction while also hinting at the introspective journey of understanding human identity in the face of advancing technology. The conversation reflects the dual nature of AI portrayals in science fiction movies and books, from helpers to threats, and how these narratives make us question what truly defines our humanity. While fantasy offers images of different worlds, science fiction applies scientific methods to the world we are currently living in. Learning from sci-fi might become an integral part of teaching AI literacy and AI ethics.

    Rae Muhlstock is a Lecturer of Writing and Critical Inquiry at the University at Albany, SUNY. Her expertise is in 20th—and 21st-century fiction, narrative theory, experimental fiction, and film. She is also the chief organizer of the annual WCI Film Festival in Albany.


    Takeaways:


    Science fiction might be considered as a blueprint for our possible future with AIs.

    As a genre, science fiction applies scientific methods to the world around us. This is its difference from fantasy, which creates imaginary worlds.

    Filmmakers and writers question the nature of humanity while developing their storylines and characters.

    The original Star Trek series questions our understanding of AIs, such as who owns them and whether they have rights.

    Today's students consider AIs 'just' tools. Still, their views on possible scenarios of human-AI coexistence are influenced by fears of AI taking over, as shown in many books and movies.

    AI ethics might evolve similarly to animal ethics.

    Today's technologists might give AI reasoning only if we change how AI systems are built/ architected.

    Humans need to learn how to coexist with intelligence that is very different from their own.

    The brain and the mind aren't the same thing.


    Chapters:


    1:20 Teaching StarTrack in creating writing courses

    5:13 Human response to AI

    8:31 Definition of Science-Fiction

    9:17 AI as a different form of intelligence/ non-human intelligence

    11:57 Human fears of AI are shaped by Sci-Fi

    15:03 Analyzing the original StarTrek Episode "The Ultimate Computer" and value alignment between humans and machines

    18:38 Is AI just a tool?

    23:24 The brain and the mind are different

    24:53 Who owns AI? Who owns Data from StarTrek?

    26:19 Diversity in humanity and in AIs: What does it mean?

    32:35 Giving AI possibilities to reason via implementing different technology architectures

    37:40 Importance to learn from AI when we define our humanity/ reading from the work of students


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    50 m
  • 34: Parenting in Code: The Snorble Story of Child-Centric AI with Mike Rizkalla
    Mar 18 2025

    In this episode of AI Snacks, Anastassia interviews Mike Rizkalla, an entrepreneur who transitioned from the entertainment industry to robotics, focusing on AI in children's education.


    Mike is the CEO and co-founder of Snorble, a startup that develops interactive robotic companions designed to help children develop healthy habits and improve their educational experiences. He studied computer and electrical engineering and spent multiple years in the entertainment and creative industry. Mike's vision for Snorble involves leveraging AI-driven technology to inspire learning, nurture development, and foster curiosity in young minds. His work has been recognized with several awards, reflecting his innovative approach to combining technology with child development.


    Anastassia and Mike discuss the development of Snorble and the purpose of child-centric AIs. Mike shares insights on the technology stack, challenges of AI on edge devices, and the importance of human-centric design. The conversation also touches on building trust with parents, the role of AI companions in child development, and the significance of dedicated content labs in creating educational experiences.


    Takeaways


    • Snorble is designed to enhance children's learning experiences.
    • The technology stack includes proprietary hardware and software.
    • AI on edge devices offers advantages like reduced latency.
    • Privacy and security are prioritized in Snorble's design.
    • Human-centric design is crucial for product success.
    • Understanding young children's language is a key challenge in developing a proprietary language model.
    • Parents have concerns about AI replacing human interaction.
    • Snorble can help children learn math and reading. The robot is aligned with what parents expect from a companion, and parents fully control its implementation.


    Chapters:


    00:00Introduction to AI in Children's Rooms

    01:03Mike's Journey to Robotics and AI

    02:40Current State of Snorble and Market Position

    04:11Technology Stack of Snorble: Hardware and Software

    10:34Challenges and Advantages of AI on Edge Devices

    14:06NLP and Child-Centric Technology Development

    18:56Human-Centric Product Design in AI

    21:22Overcoming Unknowns in Product Development

    24:15Collaboration with Research Facilities

    25:02Building Trust with Parents

    32:24Vision for AI Companions in Child Development

    35:23Content Lab and Educational Focus

    37:51Snorble's Role in Learning Math and Writing


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    40 m
  • 33: Ink Meets Code: AI in Writing with Naomi S. Baron
    Mar 4 2025
    Summary In this episode of AI Snacks, Anastassia and Naomi Baron explore the intersection of artificial intelligence and writing. They discuss AI's capabilities in generating text, its implications for authorship and creativity, and the historical context of writing and plagiarism. The conversation delves into the cognitive effects of relying on AI for reading and writing, the evolving nature of literature, and the future of AI in these domains.Naomi S. Baron is a linguist and professor emerita of linguistics at the Department of World Languages and Cultures at American University in Washington D.C. Baron earned a PhD in linguistics at Stanford University. She taught at Brown University, the Rhode Island School of Design, Emory University, and Southwestern University before coming to American University. Her areas of research and interest include computer-mediated communication, writing, and technology, language in a social context, language acquisition, and the history of English. She was a Guggenheim Fellow, Fulbright Fellow, and Semiotic Society of America president. Her book, "Always On: Language in an Online and Mobile World," published in 2008, won the English-Speaking Union's HRH The Duke of Edinburgh ESU English Language Book Award. Anastassia recommends her excellent new book, "Who Wrote This?" Takeaways AI can write poetry and prose, but is it literature?Large language models process statistical token streams. They lack an understanding of language and human reasoning.AI's role in writing raises questions about creativity and authorship. However, it is uncertain whether writers who sue LLM makers over copyright infringements will win their cases. This is due to the nature of LLMs, which process tokens rather than words or sentences.Historical perspectives show that plagiarism was once accepted.Writers today may use AI as a tool, but it doesn't replace their voice.Reading experiences shape our understanding of language and culture.AI can summarize texts, but it may reduce profound reading experiences.The future of writing may involve collaboration between humans and AI.Understanding the evolution of reading is crucial in the digital age.Chapters 00:00Introduction to AI and Writing03:14Understanding AI in Writing and Literature06:20The Role of AI in Creative Processes12:36Historical Perspectives on Writing and Plagiarism19:48Copyright Issues and AI's Impact on Authors24:41The Writer's Journey and Reader Engagement30:00The Evolution of Reading and Cognitive Impact40:45Future of AI in Writing and ReadingReading Material and Sources: Biography Naomi S. BaronWho Wrote This? How AI and the Lure of Efficiency Threaten Human WritingHow ChatGPT robs students of motivation to write and think for themselves5 Touch Points Students Should Consider About AIWhy Human Writing Is Worth Defending In the Age of ChatGPTMedium Matters for Reading: What We Know about Learning with Print and Digital ScreensAI Edutainment Website“Romy&Roby” Book WebsiteAmazon.com “Romy, Roby and the Secrets of Sleep”
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    42 m
  • 32: Vector Magic: Transforming Data into Intelligence with Ilya Meyzin
    Feb 18 2025
    In this episode of "AI Snacks," Anastassia and Ilya Meyzin, SVP of Data Science at Dun & Bradstreet, delve into the significance of vectors in AI and data science. Ilya Meyzin is a data science executive with experience in corporate strategy and data science across multiple industries and countries. He currently serves as the SVP and Head of Data Science at Dun & Bradstreet. He has a B.A. in Philosophy from Yale University. He has participated in briefings to the President's National Security Telecommunications Advisory Committee on Big Data analytics. He has presented to U.S. government audiences on AI trends in the private sector. His expertise in data science and AI has led to his appointment as a member of the Network of Experts for OECD.AI.Anastassia and Ilya explore how vectors serve as numerical representations of data, enabling machines to process and understand information. Ilya shares his unconventional journey into data science, emphasizing that a background in statistics isn't mandatory for success in the field. The conversation highlights the importance of vectors in machine learning, natural language processing, and discovering patterns in data. They also touch on the emerging trends in multimodal AI and the applications of vector technology in real-world scenarios. Ilya discusses the rapid evolution of data dictionaries and – in applications related to business identities - the challenges of mapping companies to relevant codes. He explains how advanced natural language processing and vector representation of data can significantly improve search results. The discussion then shifts to the capabilities of large language models (LLMs) and their implications for understanding human language. Ilya emphasizes the importance of autonomous AI agents in solving complex problems and the potential for these agents to evolve in the coming years. The conversation concludes with reflecting on the ethical considerations surrounding AI and the necessity for technology literacy in society.Takeaways:Vectors are crucial for representing data in AI and allow machines to analyze and understand information.NLP relies on high-dimensional vector spaces.Similarity is a key factor in utilizing vector technology effectively.Vectors can encode complex relationships between objects.Multimodal AI combines different data types using vectors.Understanding vectors can enhance AI applications in various fields, including search.AI can discover patterns that humans may overlook. Traditional data dictionaries become outdated quickly, impacting data accuracy.NLP can enhance the understanding of company functions in business identity applications.LLMs have demystified human language processing.The future of AI lies in autonomous agents tackling complex problems.Memory in AI systems can enhance user experience but raises privacy concerns.The evolution of AI agents will lead to more sophisticated applications.Ethical considerations in AI development are crucial for responsible innovation.AI literacy is essential for societal advancement and understanding of technology.Collaboration and sharing technologies can drive innovation in AI.Chapters:00:00Introduction to AI Snacks and Vectors03:21Ilya's Journey into Data Science05:20Understanding Vectors in AI08:33The Importance of Vectors for Machine Understanding11:15Natural Language and Computer Understanding15:34The Role of Vectors in Discovering Patterns17:09Finding Similarities with Vectors21:31Multimodal AI and Vector Technology23:14Applications of Vectors in Data Science24:48The Evolution of Data Dictionaries27:30Transforming Company Data into Vectors30:00Demystifying Human Language with LLMs35:56The Future of Autonomous AI Agents42:45Ethics and the Future of AILinks:Dun & BradstreetAI Edutainment Website“Romy&Roby” Book WebsiteAmazon.com “Romy, Roby and the Secrets of Sleep”
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    49 m
  • 31: Swiss AI Peaks: Lucerne’s Digital Ascent with Donnacha Daly
    Feb 6 2025

    Summary


    In this episode, Anastassia talks to Donnacha Daly, a technology executive and Professor of artificial intelligence and machine learning. Donnacha currently serves as the Co-Founder, President & COO of Gopf and Head of AI & Machine Learning Studies at Lucerne University of Applied Sciences and Arts in Switzerland. With over 25 years of experience, Daly has an impressive professional background spanning technology innovation, research, and entrepreneurship. He is a Senior Member of IEEE and a Founding Board member of the Lucerne AI & Cognitive Community LAC2. Daly is passionate about applying technology and engineering to solve significant societal and economic challenges, with a strong belief in AI's potential to address humanity's problems.


    Anastassia and Donnacha discuss the evolution of AI and robotics technologies, focusing on the importance of local ecosystems in fostering innovation. Donnacha shares his journey in AI, defines artificial intelligence, and explores the shift of AI research from Europe to the US. They delve into the challenges European AI ecosystems face, venture capitalists' role, and Switzerland's unique advantages in the AI landscape. The discussion culminates in the success story of the Lucerne AI and Cognitive Sciences Hub, highlighting the power of community and collaboration in driving AI advancements.

    Takeaways


    • AI is defined as the capability of machines to perform cognitive tasks better, faster, and cheaper than humans.
    • Switzerland consistently ranks high in global innovation due to its strong infrastructure and resources.
    • The US has a more risk-taking culture that fosters AI innovation than Europe.
    • European AI ecosystems face challenges in scaling and attracting venture capital.
    • Venture customers can provide startups with essential support and validation.
    • Procurement rules, compliance hurdles, and culture often impede startups from integrating into larger companies.
    • Switzerland's small size allows for easier access to decision-makers in large companies.
    • The Lucerne AI Hub is a successful model for fostering AI innovation in regional areas.
    • Community engagement is crucial for uncovering local talent and opportunities in AI.
    • AI and robotics will play a significant role in shaping future economies.


    Chapters


    00:00 Introduction to AI and Robotics

    02:06 Donnacha's Journey in AI

    04:53 Defining Artificial Intelligence

    07:39 The Shift of AI Research to the US

    10:42 Understanding AI Ecosystems

    12:07 Challenges in European AI Ecosystems

    16:22 The Role of Venture Customers

    20:39 Navigating Corporate Hurdles in Innovation

    22:15 Scaling Challenges in Switzerland

    27:51 The Lucerne AI and Cognitive Sciences Hub

    34:35 Conclusion and Future of AI in Local Ecosystems


    About Donnacha Daly:


    HSLU Donnacha Daly

    Gopf

    Study “Artificial Intelligence in Central Switzerland”


    About Anastassia Lauterbach:


    AI Edutainment Website

    “Romy&Roby” Book Website

    Amazon.com “Romy, Roby and the Secrets of Sleep”

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    36 m
  • 30: From Bits to Brücken: Key Steps for Successful AI Adoption with Christian Nabert
    Jan 21 2025

    "AI Snacks with Romy&Roby" is a podcast to the book series, aiming at explaining AI and robotics in simple language. In this episode, Anastassia talks with Dr. Christian Nabert, a German AI Researcher and Practioner.

    Dr. Christian Nabert studied physics at the Technical university of Braunschweig and received his doctorate in the area of analysis and modeling of space data at the Institute for Geophysics and Astrophysics. He heads the IAV Tech Hub and is responsible for the industrialization of new technologies, including AI and machine learning. IAV is a German Automotive and transport Engineering Company.

    Takeaways:

    AI is becoming more accessible to non-experts.

    Cultural readiness is crucial for AI adoption.

    Germany has a vibrant startup landscape for AI.

    AI ethics must be considered in implementation.

    Training employees is essential for successful AI use.

    Communication skills are vital in AI projects.

    Prototyping is a key step in AI implementation.

    Calculating ROI for AI projects is challenging but necessary.

    A hybrid infrastructure is common for AI deployment.

    Continuous learning is vital in the fast-evolving AI field.

    Key moments:


    00:00Introduction to AI and Its Democratization

    06:12Cultural and Technological Aspects of AI Adoption

    12:16Phases of AI Project Implementation

    20:46Challenges in Scaling AI Solutions

    26:16AI Ethics and Implementation

    32:01Advice for Mid-Sized Companies on AI

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    36 m
  • 29: AI or Die: Implementing AI Conversation with Florin Rotar
    Jan 7 2025

    "AI Snacks with Romy and Roby" introduces concepts of AI, Robotics, and quantum computing in easy-to-understand language and is part of the “Science Behind” section of the Romy & Roby Book series for people without a computer science and mathematics background.

    In this episode, Anastassia and Florin Rotar discuss the evolution of AI, its implications for businesses, and the importance of human accountability in AI development. Florin shares his journey in AI, the rapid advancements in technology, and the challenges of generalization in contemporary AI models. They explore the role of a Chief AI Officer, practical steps for AI implementation, and the balance between the benefits and risks associated with AI.

    Florin Rotar is a seasoned technology executive, currently serving as the Chief AI Officer at Avanade, a leading software solutions provider. Recognized for his expertise, Rotar was named one of the “Top 10 CTOs to Watch in 2023” by Entrepreneur Magazine and is a member of the Forbes Technology Council. Flor co-authored “We The People: Human Purpose in a Digital Age,” which explores ethics in the digital era. Florin also co-authored “The Handbook for Chief AI Officers.” It covers topics such as building AI teams, navigating the AI technology landscape, and crafting AI implementation roadmaps for businesses.


    Takeaways


    AI is a field that has existed for decades, but its rapid evolution is surprising.

    The success of AI implementation heavily relies on people, not just a particular AI technology.

    Human accountability is crucial in the development and deployment of AI.

    Generative AI models are powerful but require careful oversight.

    AI's ability to generalize is still a challenge that needs addressing.

    Training and upskilling employees is essential for successful AI integration.

    Different industries are at varying levels of AI maturity and adoption.

    The role of a Chief AI Officer focuses on people and business value.

    Organizations must balance between consuming, customizing, and creating AI solutions.

    AI presents both opportunities and risks that need to be managed thoughtfully.


    Chapters


    00:00 Introduction to AI and Robotics

    01:51 Florin's Journey in AI

    04:36 The Rapid Evolution of AI

    09:05 Human Accountability in AI

    13:14 The Challenge of AI Generalization

    18:38 AI in Various Industries

    22:25 The Role of a Chief AI Officer

    25:10 Practical Steps for AI Implementation

    29:29 Balancing AI Benefits and Risks


    Find More from Anastassia Lauterbach:

    

    YouTubeChannel

    LinkedIn

    Instagram

    TikTok

    AI Edutainment Website

    Romy and Roby Books and Community Website

    Romy, Roby and the Secrets of Sleep by Anastassia Lauterbach



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    37 m
  • 28: Vision Quest: The Future Through AI’s Eyes with Dr Dimitry Fisher
    Dec 17 2024

    Summary


    This podcast introduces concepts of AI and robotics in easy-to-understand language. It is a part of "The Science Behind" section of "Romy and Roby" book series, an AI adventure for the whole family.


    In this episode, Anastassia and Dr Dimitry Fisher discuss computer vision technologies and their evolution. Dimitry explains that computer vision is the ability of artificial systems to acquire, process, and act upon visual input. He highlights the three main directions from which computer vision emerged: pre-World War II television, early computers, and the study of animal and human vision. Dimitry also discusses the most critical technologies in computer vision, such as convolutional neural networks (CNNs), generative adversarial networks (GANs), and transformers. He emphasizes the importance of labeled data and using pre-trained models in computer vision. The conversation also touches on the ethics and future of computer vision technologies.


    Dimitry Fisher is a distinguished AI scientist with extensive experience and neuroscience, machine learning, and data science. He serves as the Senior Vice President of Data Science at Aicadium (https://aicadium.ai/), an AI company committed to build AI products across industries and business functions.

    Dimitry earned his PhD in Plasma and High-Temperature Physics, atomic physics, and hot-dense matter from the Weizmann Institute of Science. He was a Senior Scientist at Brain Corporation, where he developed large-scale vision models and researched sensory-motor learning algorithms for robots and AI. His postdoctoral work at UC Davis and the Weizmann Institute of Science further solidified his expertise in neuroscience and computational algorithms of the brain cortex.


    Takeaways


    Computer vision is the ability of artificial systems to acquire, process, and act upon visual input.

    Computer vision emerged from three main directions: pre-World War II television, early computers, and the study of animal and human vision.

    Groundbreaking technologies in computer vision include convolutional neural networks, GANs, and transformers.

    Labeled data is essential in computer vision, and pre-trained models are often used to reduce the need for large amounts of labeled data.

    Ethics play a crucial role in developing and deploying computer vision technologies.

    The future of computer vision involves advancements in co-bots, autonomous machines, and multimodal AI.


    Chapters


    00:00 Introduction to Computer Vision

    02:03 The Three Directions of Computer Vision Emergence

    05:16 Groundbreaking Technologies in Computer Vision

    07:37 The Importance of Labeled Data and Pre-Trained Models

    18:35 Ethics and the Future of Computer Vision

    21:14 Advancements in Co-bots, Autonomous Machines, and Multimodal AI

    Find More From Dr. Anastassia Lauterbach:

    

    Romy & Roby | Website

    Romy & Roby | TikTok

    Romy & Roby | Instagram

    AI Edutainment GmbH | YouTube

    Dr. Anastassia Lauterbach | X

    Dr. Anastassia Lauterbach | LinkedIn

    Book (Amazon): Romy, Roby and the Secrets of Sleep by Anastassia Lauterbach


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    40 m