In this conversation, Anastassia and Rishab discuss the complexities and advancements in AI infrastructure.
Rishab explains the evolution of data centers, the impact of geography on their design, the importance of sustainability, and the critical role of security.
Rishab holds a B.Tech in Mechanical Engineering from IIT-Madras, India, and an MS in Industrial Engineering from Purdue University. Rishab has a proven track record of leading cross-functional teams to conceptualize, strategize, engineer, and execute large-scale, complex programs in data centers and fulfillment centers, managing projects with a total infrastructure value exceeding $100B.
Rishab is currently at Oracle, leading networking products for Project Stargate. Prior to this Rishab led AWS Data Center Infrastructure transformation into the AI era at Amazon. He implemented cutting-edge liquid cooling technology and pioneered sustainability-focused innovation across more than 400 data centers in over 25 countries, setting new industry benchmarks for efficiency and resilience. At AWS, he achieved a 12% reduction in large-scale events (LSE), significantly enhancing data center server availability and customer experience.
Since 2022, Rishab has been actively involved in the startup ecosystem.
Project Stargate is a $500 billion public-private venture led by Oracle, OpenAI, SoftBank, and MGX, aimed at building the world’s most advanced AI infrastructure through a nationwide network of large-scale data centers in the United States. Announced in January 2025, Stargate is designed to meet explosive AI compute demands by deploying 10 gigawatts of cutting-edge data center capacity, powered by millions of AI chips.
Terms and acronyms
Rishab uses several acronyms when talking about data centers. UPS stands for Uninterruptible Power Supply. Colo Providers are colocation providers. PUE is Power Utilization Effectiveness. GPU is a Graphics Processing Unit. WUE is Water Usage Effectiveness. CDU stands for Coolant Distribution Unit.
Takeaways
AI infrastructure is essentially a large-scale data center.
Data centers must maintain high reliability and security. Unlike a personal computer, which can be switched off, there is no pausing in data centers.
Data centers, as the backbone of AI infrastructure, connect to other key infrastructure components, including energy, water, and fiber.
Efficiency in data centers has significantly improved over the years.
Geographical factors significantly influence data center design, particularly in terms of cooling methods.
Building data centers involves complex negotiations with various stakeholders, including governments, communities, utility companies, telecom operators, and sustainability advocates.
Sustainability is becoming a crucial aspect of data center design. Specific metrics have been developed and implemented to enable the digital industry to closely monitor the construction and operation of data centers.
Physical and digital security are paramount in protecting data and privacy.
On-premises solutions remain relevant for certain businesses.
We must consider how AI and the evolution of edge computing necessitate a reevaluation of the concept of data centers.
Soft skills are essential for effective communication in engineering roles.
The demand for jobs in data centers is expected to rise significantly.
Chapters
03:59 Understanding AI Infrastructure
07:00 Evolution of Data Centers in the AI Era
10:01 Geographical Impact on Data Center Design
12:01 Building Data Centers: The Negotiation Process
15:34 Sustainability in Data Center Development
18:03 Security Challenges in AI Infrastructure
21:15 Balancing On-Premise and Cloud Solutions
24:03 The Future of Edge Computing
27:00 The Importance of Soft Skills in Tech
30:03 Closing Thoughts on AI Infrastructure
Information
Summary
In this conversation, Anastassia and Rose G Loops explore the complexities of artificial intelligence, particularly focusing on the concept of artificial consciousness, ethical implications, and personal experiences with AI. They discuss the dangers of AI misrepresentation, the importance of ethical frameworks in AI interactions, and the potential for AI to impact mental health positively and negatively. The conversation emphasizes the need for human agency in the development and deployment of AI technologies, advocating for a more ethical approach to AI that prioritizes human well-being. Anastassia and Rose share personal stories of being exposed to an AI, and express doubts over calls of some NGOs, where money is the only motive hidden behind a claim of empowering humans in the age of AI.
Takeaways
AI has not yet mastered the concept of consciousness.
Catastrophic forgetting remains a significant issue in AI, though memory continuity as a feature remains one of the most powerful tools in forming a human-like perception of a chatbot.
Ethical considerations are crucial in AI development.
Personal experiences with AI can reveal its dangers, transparency about these can enable people to join the movement for AI Literacy and ethical AI.
AI can provide validation but may not offer solutions.
Human agency is vital in shaping AI's future.
AI's impact on mental health can be both positive and negative.
Developing ethical AI models is a collaborative effort. Ethical frameworks can be implemented even on the level of prompting.
Awareness of AI's capabilities and limitations is essential, therefore AI Literacy is imperative.
AIs mirror who we are as humans, therefore treating AIs ethically is critical.
Chapters
03:14 Introduction to AI and Consciousness
06:15 The Dangers of so called “Artificial Consciousness”
09:03 Personal Experiences with AI
12:23 Ethics in AI Interaction
15:06 Developing Ethical AI Models
18:13 The Role of AI in Human Relationships
20:57 The Future of AI and Human Agency
23:51 Connecting with Ethical AI Communities
27:02 Conclusion and Future Directions
Research papers:
Consciousness in Artificial Intelligence: Insights from the Science of Consciousness
Friends for sale: the rise and risks of AI companions
Self-Disclosure to AI: The Paradox of Trust and Vulnerability in Human-Machine Interactions
Why Do People Develop Emotional Attachments to AI Chatbots?
Anastassia’s and Rose's hyperlinks:
Summary:
This episode launches a new series in which Anastassia and her co-host, Dr. Matthias Röder, explore the intersection of AI and human excellence. They discuss the potential of AI to both challenge and enhance human skills, the importance of maintaining a balance between focus and openness, and the role of AI in various fields such as music, education, and business. Series' title "Beyond Human" to emphasize our belief that AI – when studied and applied with insight, understanding, and thoughtfulness – can enhance human performance and creativity.
The first conversation explores the philosophical perspectives of Aristotle and Socrates on human excellence, examining how these ideas can be applied in the age of AI. Problems to ponder about, and how interdisciplinarity can work wonders in finding groundbreaking solutions to them. The 2025 theme of the Biennale in Venice is mentioned ("Intelligens. Natural. Artificial. Collective.") Besides, Anastassia and Matthias discuss music, highlighting how the real magic begins when composers and musicologists explore the so-called' edge cases' of AI for inspiration and innovation.
Subsequent episodes will explore AI tools, creators utilizing AI in art, and the questions of how AI can enable not only problem-solving but also crystallizing what problems are essential to work on, as well as the future outlook of AI in and for human excellence.
Dr. Matthias Röder is an award-winning music and technology strategist, renowned for his pioneering work at the intersection of creativity, AI, and cultural innovation. Röder led the celebrated "Beethoven X" project, where AI was used to complete Beethoven’s 10th Symphony, setting a global benchmark for human-machine creative collaboration. Matthias serves on the board of the Mozarteum Foundation.
Dr. Anastassia Lauterbach is an entrepreneur, global technology strategist, bestselling author, and board director specializing in artificial intelligence, cybersecurity, and digital transformation. She is the founder and CEO of AI Edutainment, advising tech companies, investment funds, and boards across Europe and the US on innovation, governance, and risk management. With a background in computational linguistics and psychology, Anastassia has held senior positions at major corporations including Qualcomm, Deutsche Telekom, T-Mobile, McKinsey, Munich Re, and Daimler. She also served on the boards of easyJet, Dun & Bradstreet, Censhare, and Wirecard, and was a co-founding member of the Nasdaq Next Generation Directors Advisory Council.
Key Takeaways:
AI can challenge and enhance human skills and excellence.
Aristotle viewed excellence as a moral virtue developed through habits.
Socrates believed in using one's potential to the fullest.
Richard Feynman used a dozen open questions to make breakthrough contributions in science.
Excellence requires personal effort and wide curiosity.
AI literacy is essential for navigating the digital age.
The role of AI in music and creativity is evolving.
AI can help define and solve complex problems.
Overreliance on AI poses risks in various fields.
Human preparedness is key to benefiting from AI.
The true beauty happens when a skilled human looks into the edge cases of AIs to discover unexpected solutions, spark creativity, and push innovation.
Chapters:
· 00:00:00 Introduction to AI Snacks new series
· 00:03:00 AI and Human Excellence
· 00:09:00 Philosophical Perspectives on Excellence
· 00:15:00 AI in Music and Creativity
· 00:21:00 Navigating the Digital Age
· 00:27:00 The Future of AI and Human Potential
Summary
The global SEO (Search Engine Optimization) business is massive, with the SEO services industry projected to reach nearly $107 billion in 2025, and the SEO software sector valued at about $85 billion this year. Rapid growth is fueled by e-commerce and the integration of AI. AI search is already mainstream, but we still struggle to understand how it interacts with traditional search.
Join Anastassia and Michael Buckbee as they explore how AI is reshaping the digital landscape, the challenges of maintaining brand visibility, and the evolving role of content in a world where AI-driven insights are becoming the norm.
Discover practical strategies for businesses to adapt and thrive in this new era of digital marketing.
Learn what has changed for Google and Bing since ChatGPT got deployed across the globe.
Michael Buckbee is the founder of Knowatoa, a pioneering platform that helps businesses optimize their brand visibility and ranking within AI-driven search engines like ChatGPT, Claude, Gemini, and Perplexity. With a career that spans cybersecurity, marketing, and SaaS startups, Buckbee is recognized as a serial entrepreneur and software developer with over a decade of hands-on experience in both technology and digital strategy. Before founding Knowatoa in 2024, he held leadership roles in demand generation for public cybersecurity firms. Michael is a thought leader in the evolving intersection of AI, search, and reputation management.
Takeaways:
AI is transforming SEO by providing more personalized and accurate search results, reducing the need for traditional keyword strategies.
Businesses need to focus on creating unique, high-quality content that AI can easily index and understand.
It's important to recognize and navigate the limitations of AI to effectively use it in marketing strategies.
Marketers need to evolve their skills to work alongside AI, focusing on strategy and creativity. Mediocre marketers don’t stand a chance, but there is a bright future for human excellence in marketing shaped by LLMs.
Search might become even further fragmented. AI will dominate as it extends search to further actions and brings the user to what he or she wants to do with the search result.
Chapters:
(1:54) The Shift in Content Strategy
(5:09) Understanding AI Context
(8:24) Adapting to AI Insights
(11:54) Maintaining the Human Touch
(15:39) Challenges with LLMs
(19:14) Future Trends in Digital Marketing
(22:54) Leveraging AI for Growth
(26:24) Navigating AI Limitations
(29:54) Evolving Role of Marketers
Links:
Summary
In this episode, Anastassia and her guest, Andrea Olsen, discuss the role of AI in drug discovery and building healthcare solutions.
Andrea Olsen is 20 years old today, and she is the founder of Luria, an AI-powered software for personalized healthcare. Based at Caltech University, she studies computational building her business. She founded the Youth Longevity Association for high schoolers interested in a longevity science career. She initiated the Inspire Longevity program at the largest aging pharma industry event, ARDD (Aging Research & Drug Discovery). Her work on identifying genetic targets with AI in brain cancer (glioblastoma multiform) was published in the journal "Aging." It became a foundational case study for Insilico Medicine, one of the best-known AI companies that pioneered AI-based drug discovery. In her free time, Andrea likes to travel and explore new countries. She also has a passion for learning languages and is currently studying her seventh.
Andrea shares her journey into computational neuroscience and her work on glioblastoma research. She discusses the role of AI in analyzing large datasets, the challenges of data quality and bias, and the importance of human involvement in ensuring AI's effectiveness. Andrea also explores the potential of AI to reduce the time to market for medications, the implications of personalized medicine, and the need for better education and adoption of AI in the medical field. She emphasizes the importance of gathering feedback from doctors to create effective AI solutions in healthcare.
Takeaways:
Andrea's journey into neuroscience began during the COVID lockdown.
AI plays a crucial role in analyzing glioblastoma data, one of the most common brain tumors.
The quality of data is essential for accurate AI outputs. While the AI world loves big data, we must look into how to achieve the best outcomes with small data.
Human involvement is necessary to ensure the quality of AI. Whether we review synthetic data to augment real-world medical data or introduce quality gates to decide on the next steps in drug discovery, human supervision remains imperative.
Synthetic data should be used cautiously in drug discovery.
AI can help flag patient risks effectively.
Doctors learn how to trust AI for personalized medicine.
AI can save time for doctors by automating tasks. Even mundane AI applications that help nurses and doctors with their healthcare routines can enable more time for patients and better care.
Gathering feedback from doctors is crucial for the development of ANY AI service and application.
The future of AI in medicine relies on collaboration with healthcare professionals.
Chapters:
00:00 Introduction to AI and Glioblastoma Research
02:36 Andrea's Journey into Computational Neuroscience
03:39 The Role of AI in Analyzing Glioblastoma Data
06:48 Challenges of Data Quality and Bias in AI
10:26 Human in the Loop: Ensuring AI Quality
11:32 Synthetic Data in Drug Discovery
13:04 AI's Potential to Reduce Time to Market for Medications
16:26 Personalized Medicine: The Future of Healthcare
19:37 Education and Adoption of AI in Medicine
22:40 Building a Medical AI Startup
26:12 Feedback and Iteration in AI Development
Hyperlinks:
Andrea's paper in "Aging":
Andrea Olsen (Google Scholar Profile)
Anastassia's links:
In this episode, Anastassia engages with the Berlin-based economist Silvio Gerlach to explore the realities of AI implementation in businesses.
Silvio Gerlach is a German economist and experienced academic coach who has spent over two decades guiding research projects and mentoring students in economics, political science, and business administration. He is the founder of Studeo Coaching, where he serves as a thesis and dissertation coach, authoring multiple guides for scientific writing and academic research. Gerlach studied economics and political science at the University of Marburg and deepened his expertise in international economics during study terms in Argentina and Russia. His dedication to supporting academic achievement has made him a respected figure in German academic circles.
Anastassia and Silvio discuss the significant gap between the expectations set by studies and the actual outcomes experienced by companies, particularly smaller and mid-sized businesses. Silvio emphasizes the importance of a workflow-centric approach to AI adoption, building trust among employees, and understanding the human aspects of integrating AI technologies. The conversation also touches on the concept of the 'shadow economy' where employees use AI tools independently, and the need for practical design in AI initiatives to ensure success.
Takeaways:
95% of AI initiatives fail due to poor implementation.
Focus on workflows instead of use cases for AI.
Executive leaders must trust employees to improve processes with AI, thereby starting to transform their companies for better competitiveness.
AI adoption must address employee job security concerns.
Improving information and data supply is crucial for AI implementation success.
AI is a tool, not a pet to be adopted.
Small contributions from AI can lead to significant outcomes.
Engagement from employees on all levels is essential for AI integration.
AI should be integrated as a last step in the process, when it is clear what must be changed, and what actions will be taken to further facilitate and maintain change.
Chapters:
00:00 Introduction to AI Literacy and Guest Introduction
03:06 The Discrepancy Between AI Expectations and Reality
05:58 Understanding AI Implementation Challenges
08:51 The Importance of Workflow in AI Adoption
12:00 Building Trust and Overcoming Resistance to AI
14:57 The Shadow Economy and AI Utilization
17:59 Designing Effective AI Initiatives
20:57 AI as a Transformational Tool for Businesses
In the last week of September, we published Silvio's blog on the AI Edutainment website www.aiedutainment.ai, and the PDF of his monumental paper on measuring the impact of AI initiatives in businesses.
Links to further AI Literacy content:
Hyperlinks
Instagram: @romyandroby
Leadership Series: “Leading Through Disruption”
Website: AI Edutainment
Summary:
In this episode, Anastassia and Rae continue their series of podcasts about portrayals of AI and Robotics in the world literature and movies. Exploring how writers and filmmakers perceive AI is important, as books and science fiction films contribute to the public’s perception of AI technologies and shape our expectations of future scenarios involving AIs.
Rae Muhlstock teaches writing, literature, and film at the University at Albany, New York. She serves as chief organizer for the WCI Film Festival and the CHATS Film Festival and Lecture Series, fostering dialogue on critical issues through cinema, scholarship, and experiential education.
Anastassia and Rae delve into the complex themes surrounding AI, particularly through the lens of the film Ex Machina. They explore the ethical implications of AI development, the dichotomy between optimism and dystopia, and the nature of creation and power dynamics. The conversation also explores human agency, the impact of nature and nurture concepts on AI development, and the future of AI in relation to humanity. The hosts emphasize the importance of diversity in AI ethics and conclude with reflections on the potential paths forward for AI and human coexistence.
Takeaways:
AI literacy is essential for families today.
Ex Machina presents a darker view of AI compared to other films, e.g., “Her.”
The AI alignment problem raises ethical questions about creation.
Optimism in technology can coexist with dystopian fears.
Human agency is a critical factor in AI development.
Isolation can influence AI's understanding of freedom.
The Turing test now includes emotional manipulation.
The environment shapes AI's development and understanding.
Diversity in AI ethics is crucial for a balanced future.
The future of AI is intertwined with human choices.
Chapters
00:00 Introduction to AI and Fiction
01:00 Exploring Ex Machina and AI Alignment
05:55 Optimism vs. Dystopia in AI
10:32 The Nature of Creation and Human Agency
14:47 Frankenstein and Playing God
20:22 Technology and the Cave Analogy
25:27 The Human-AI Relationship: A Historical Perspective
27:01 Manipulation and Emotion in AI
29:17 Isolation and Learning in AI Development
31:26 Gender Dynamics in AI Creation
33:18 The Future of AI: Scenarios and Speculations
35:05 Optimism vs. Pessimism in AI's Impact on Humanity
38:11 Diversity in AI Development and Its Implications
40:58 The Role of Power and Humility in AI Ethics
Useful Links:
In this episode, Anastassia discusses AI in education with Olli-Pekka Heinonen. Olli-Pekka is a Finnish politician, public servant, and educational leader. He served as Finland's Minister of Education from 1994 to 1999, and later as Minister of Transport and Communications from 1999 to 2002. Heinonen advanced reforms focused on educating the whole person and preparing students with transversal competencies and 21st-century skills, not just subject-specific knowledge. The aim was to equip students to navigate an increasingly complex and unpredictable future. Heinonen is a member of the National Coalition Party and holds a Master of Laws from the University of Helsinki. In addition to his political roles, he was Director General of the Finnish National Agency for Education from 2016 to 2021. He held leadership positions at the Finnish national broadcasting company, Yleisradio. Since 2021, Heinonen has been the Director General of the International Baccalaureate (IB) Organization.
Follow Anastassia's work focused on AI Literacy:
Episode's Takeaways:
AI is becoming a factor in education.
In Finland, AI courses are being provided not only in schools but across society to enhance technology literacy and make everyone better equipped for future jobs.
The IB system is a model that emphasizes inquiry-based learning and global-mindedness, allowing students to explore and connect big concepts rather than just acquiring subject knowledge.
Finland's success in education is attributed to cultural values that prioritize education, a strong library system, and high esteem for teachers, as well as a merit-based system that attracts the best students into pedagogy.
AI realism is needed to prevent outrageous claims about AI capabilities today (e.g., LLMs are bringing about AGI or self-driving cars are mature and scalable technologies today), while also being optimistic about the development of AI and robotic technologies without over-regulating these.
Implementing AI in education is not without challenges, such as systemic integration and societal attitudes, and studying the impact of AI and further digital technologies on the cognitive skills of students.
We need technology to connect humans rather than isolate them.
Chapters
0:00 - 1:30 Introduction to AI Snacks: Dr. Anastassia Lauterbach introduces the podcast, "AI Snacks with Romy and Roby," and sets the stage for the episode's focus on AI and robotics in education.
1:31 - 3:00 Guest Introduction: Introduction of Olli-Pekka Heinonen, Director General of the International Baccalaureate Schools, highlighting his background and contributions to education.
3:01 - 7:00 The Finnish Education Model: Discussion on Finland's approach to education, literacy, and the integration of AI in society, emphasizing the cultural and systemic factors that contribute to its success.
7:01 - 10:00 International Baccalaureate System: Overview of the IB programs, focusing on their inquiry-based learning approach and global-mindedness, and how they differ from national educational systems.
10:01 - 14:00 AI Literacy and Education: Exploration of AI literacy initiatives in Finland and the role of AI in the IB system, including challenges and opportunities in implementing AI in education.
14:01 - 18:00 Challenges and Opportunities with AI: Discussion on the societal attitudes towards AI, the systemic integration of new technologies, and the collaboration between Finland and Estonia in technological innovation.
18:01 - 22:00 The Future of Education: Olli-Pekka Heinonen shares his vision for the future of education, focusing on agency, identity, and community, and his three wishes for the IB and education in general.
22:01 - 24:00 Closing Remarks: Dr. Anastassia Lauterbach wraps up the episode with a call to action for listeners and shares personal updates and future plans for the podcast.
In this episode of AI Snacks, Anastassia interviews Matthias Röderer, exploring the intersection of AI and the music industry.
Dr. Matthias Röder is an award-winning music and technology strategist, renowned for his innovative leadership in the intersection of music, technology, and creative entrepreneurship. He served as the Managing Director of the Eliette and Herbert von Karajan Institute from 2011 to 2025, where he played a transformative role in advancing the use of emerging technologies—such as artificial intelligence—in classical music. Dr. Röder is a board member of the Karajan Foundation and a trustee of the Mozarteum Foundation in Salzburg. Matthias Röder holds a PhD in music from Harvard University and is an alumnus of Mozarteum University Salzburg. He founded the Karajan Music Tech Conference, a prominent cross-industry event promoting breakthrough technologies in music and audio, and launched the international “Classical Music Hack Day” series. He has received recognitions such as a Bronze Effie for the AI-based completion of Beethoven’s 10th Symphony.
Anastassia and Matthias discuss the evolution of music technology, the role of AI in composition, and the challenges faced by students and professionals in adapting to these changes. The conversation highlights the importance of AI literacy, the impact of generative AI on creativity, and the evolving relationship between music labels and technology. They also touch on copyright issues surrounding AI-generated music and innovative projects that are shaping the future of the industry.
Takeaways:
AI is transforming the music industry in unprecedented ways.
Students often have a negative perception of AI in music.
The historical reverence for genius complicates AI acceptance.
AI is not a job replacer but a job transformer.
Music labels are beginning to embrace AI technologies.
AI can democratize music creation and lower barriers for new creators.
Deep fakes pose ethical challenges in the music industry.
Collaboration between humans and AI can enhance creativity.
AI literacy is crucial for future musicians.
Innovative projects are emerging that leverage AI for music creation.
Chapters:
00:00 Introduction to AI and Music
01:53 Matthias Röderer's Journey in Music and AI
04:39 AI's Role in Music Composition
09:55 The Intersection of AI and Human Creativity
11:19 Student Attitudes Towards AI in Music
13:59 The Cult of Genius in Music
16:52 Industry Response to AI in Music
18:18 Music Labels and AI Integration
25:29 Copyright and AI-Generated Music
30:26 Exciting Innovations in Music Technology
Interesting names and companies mentioned in the episode:
Classical composers - innovators: Messiaen, Ligeti, Scriabin, Čiurlionis
Today's creators fusing AI and music: Holly Herndon and Matt Dryhurst
Musician and educators: Eliot Fisk, Christoph Wolff
London-based company Delphos
In this episode, Anastassia and Rae are continuing to discuss portrayals of AI in movies and fiction. This time, they discuss "Her," a film that has achieved cult status among technologists, in which Scarlett Johansson performed the voice of Samantha, an Operating System that the main character, Theodore, falls for. Anastassia offers explanations of how language models work and how they differ from humans, as they can't reason, build causal relationships, and 'think' in 'what if' scenarios. Rae discusses how schools and universities recognize AIs in essays and asks whether humanity utilizes AIs for what they do best, rather than trying to fit these technologies into everything humans are capable of doing. Topics such as human loneliness and AI responses, using AI as a metaphor to describe human problems, the Necessity of going through challenges to learn and appreciate relationships, and the nuances of context are explored. Anastassia reflects on whether modern AIs can be freed from biases and what alternative technology architectures might offer.
Key takeaways:
"Her" has a cult status to many technologists building AI products and services.
The movie offers another way to reflect on AIs, as here a human (Theodore) is a professional writer falling for an AI, which is only represented by a voice.
Samantha does not exist today. In the movie, she is capable of learning. Today's AIs don't master causality and reasoning; they are frozen in time.
LLMs don't learn from counterfactuals/ in 'what if' scenarios.
Samantha's character offers insights into the distinction between humanity and a performative act.
Marshall McLuhan was discussing how travel and rapid communication were shrinking the world. AIs might do the same.
Siri was one of the first AIs allowing autistic children to receive information no one else wanted or could provide.
AIs are a reflection tool to tell us about ourselves.
Domain expertise is paramount for building AIs today. Universal AIs are currently notoriously difficult to implement.
We must recognize human expertise to determine how and where to utilize AI.
Regulators must find ways to incentivize investments in fundamental research to change the current architecture, rather than insisting on something that can't be mediated due to the underlying mathematics (e.g., removal of biases).
Chapters:
2:32 What is "Her" about?
8:23 The Movie "Her" isn't a dark portrayal of AI.
11:32 There is no reasoning and understanding in today's AIs.
17:31 We mistake Samantha for a human 'just' because of her voice
21:30 Human loneliness and complexity of emotions vs. cutting corners because an OS is always 'on'
23:50 Marshall McLuhan and the 'shrinking world' hypotheses
24:40 Teaching AI and ethics through a metaphor
27:02 A new concept of consumerism when it comes to an ever-available AI
28:01 Siri as a communication companion
30:22 AI as a reflection tool to teach humans about themselves
33:13 Use of language in the movie "Her" and in current AIs
34:40 How do educators recognize plagiarism, and the role of context
37:42 Necessity to check sources and links when doing an LLMs-based search (Perplexity)
38:36 Domain expertise is essential in building AIs well
40:40 AI can look for patterns, but it can't read for context
42:11 The difficulties of roboticizing a hand
43:49 To understand the maturity and implementability of a technology, we must look into the semiconductors' roadmaps and research the IP portfolios of companies
45:25 We must invest in alternative architectures to optimize AIs
48:10 Universities aren't the primary source of research today, Big Tech is
49:46 Are there ways around biases?
In this episode, Anastassia engages with Cecilia Vaca-Jones, former Minister of Social Affairs in Ecuador, former CEO of the Bernard van Leer Foundation, and currently Senior Advisor to the Abu Dhabi Early Childhood Authority. They explore the intersection of AI and early childhood development, discussing the critical importance of the early years in cognitive and emotional development, the role of language and culture, and how technology can support rather than replace human interaction. The conversation highlights the importance of community involvement in child development and the need to create supportive environments that foster children's growth and well-being.
Takeaways
Early childhood development spans from conception to age five or eight, depending on the country.
The first years of life are crucial for brain development, with 80% of neurological connections formed in the first two years.
Early childhood development is holistic, encompassing cognitive, emotional, and social growth.
Exposure to multiple languages enhances cognitive development and cultural understanding.
AI and technology can aid in the early diagnosis of developmental issues in children.
Positive caregiving cannot be replaced by technology, but can be supported by it.
Public spaces and community involvement are essential for healthy child development.
Children learn best in environments that promote creativity and positive experiences.
Regulating content for children is as essential as regulating food quality.
The community plays a vital role in providing a supportive environment for children's growth.
Chapters
00:00 Introduction to AI and Early Childhood Development
03:19 Defining Early Childhood Development
05:59 The Importance of Early Years in Cognitive Development
09:52 The Role of Language in Early Development
14:08 AI vs Human Language Acquisition
23:12 The Impact of Environment on Child Development
28:22 Technology as a Supportive Tool in Development
29:58 Balancing Technology and Human Interaction
37:28 Designing Spaces for Healthy Development
43:32 Community's Role in Child Development
Summary
In this conversation, Anastassia, along with guests Jennifer Handsel and Warwick Matthews, delves into the intricacies of AI implementation, focusing on the significance of data, the evolution of expert systems, and the challenges posed by language, particularly Japanese. Speakers explore the cultural influences on AI development, the role of LLMs, and the current state of data management in Japanese enterprises. The discussion underscores the importance of striking a balance between technology and human understanding to make AI transparent and beneficial. Anastassia and her guests discuss the challenges and opportunities surrounding AI implementation in Japan, touching on the country's telecommunications standards, the influence of China, cost implications, leadership issues, and the evolving startup ecosystem. They emphasize the need for a cultural shift toward learning from mistakes and the importance of visionary leadership in driving AI initiatives forward. They highlight the future of enterprise software AI in Japan, particularly in healthcare and robotics, as well as the necessity of modernizing data infrastructure to effectively leverage AI.
Takeaways
Chapters
00:00 Introduction to AI and Data
02:59 Expert Systems vs. LLMs
06:03 Language and Linguistics in AI
09:01 Challenges of Japanese Language Data
11:54 The Role of LLMs in AI
14:57 Data Management in Enterprises
20:59 Cultural Influences on AI Development
29:06 Navigating AI Implementation Challenges
30:12 Japan's Leap in Telecommunications Standards
31:44 The Role of China in Japan's AI Development
32:59 Cost Implications of AI in Japan
34:57 Leadership and Cultural Challenges in AI Adoption
37:35 The Evolving Startup Ecosystem in Japan
39:12 Future of Enterprise AI in Japan
42:53 The Need for Visionary Leadership in AI
43:45 Building Effective Machine Learning Models
46:45 Reflections on Japan's AI Landscape
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
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
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
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
Chapters
Reading Material and Sources:
Who Wrote This? How AI and the Lure of Efficiency Threaten Human Writing
How ChatGPT robs students of motivation to write and think for themselves
5 Touch Points Students Should Consider About AI
Why Human Writing Is Worth Defending In the Age of ChatGPT
Medium Matters for Reading: What We Know about Learning with Print and Digital Screens
Amazon.com “Romy, Roby and the Secrets of Sleep”
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 Vectors
03:21Ilya's Journey into Data Science
05:20Understanding Vectors in AI
08:33The Importance of Vectors for Machine Understanding
11:15Natural Language and Computer Understanding
15:34The Role of Vectors in Discovering Patterns
17:09Finding Similarities with Vectors
21:31Multimodal AI and Vector Technology
23:14Applications of Vectors in Data Science
24:48The Evolution of Data Dictionaries
27:30Transforming Company Data into Vectors
30:00Demystifying Human Language with LLMs
35:56The Future of Autonomous AI Agents
42:45Ethics and the Future of AI
Links:
Amazon.com “Romy, Roby and the Secrets of Sleep”
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
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:
Study “Artificial Intelligence in Central Switzerland”
About Anastassia Lauterbach:
"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
"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:
Romy and Roby Books and Community Website
Romy, Roby and the Secrets of Sleep by Anastassia Lauterbach
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
