Is the U.S. LOSING the AI race to China?
China and the U.S. are neck and neck in the AI race for global dominance. Former OpenAI board member Helen Toner (now at Georgetown’s CSET) joins us in Washington, D.C. to break down China vs U.S. strategies—open-source diffusion vs big tech global dominance— and what “winning” actually means.
Helen has recently spent time in China and works at the center of U.S. AI policy—offering a rare inside view of both ecosystems and who’s truly ahead.
Helen explains:
- Who’s ahead right now and how to measure it (frontier AI vs adoption/diffusion)
- Open-source vs closed: DeepSeek, Qwen, Kimi, Gemma, Llama vs OpenAI, Anthropic, Google
- Compute & chips: NVIDIA dependence, export controls, and why compute concentration matters
- AGI timelines: whether “AI 2027” holds up and why short timelines cooled after GPT-5
- “AI+” strategy: applying AI to manufacturing, healthcare, and finance vs pure frontier bragging rights
- What governments should do now: transparency, auditing, AI literacy, and measurement science
Who do you think is winning and WHY – China or the U.S.? Drop one evidence-backed reason (links welcome). We’ll pin the best reply.
Don’t forget to like and subscribe for more unfiltered conversations on AI, tech, and society.
Chapters
00:00 – Two strategies, one AI race
01:00 – Open-source China vs Big-Tech USA
03:37 – Not one race: choose your finish line
04:04 – Who’s actually open? DeepSeek, Qwen/Kimi, Llama, Gemma, GPT-OSS
06:26 – Frontier bragging rights vs real-world adoption
07:46 – China’s “AI Plus” play (AI + industry)
10:06 – Is the US still ahead at the frontier?
12:04 – GPT-5 reality check & AGI timelines
20:58 – Compute decides: chips, export controls, auto-ML engineers
23:04 – What we need now: transparency, audits, AI literacy
28:02 – Standards in practice: de-facto beats de-jure
30:56 – Next 5 years: closed peaks, open bow wave
37:55 – Final take: which path wins?
#OpenAI #HelenToner #ai #GPT5 #OpenSource #podcast #China #DeepSeek
Is the U.S. LOSING the AI race to China?
China and the U.S. are neck and neck in the AI race for global dominance. Former OpenAI board member Helen Toner (now at Georgetown’s CSET) joins us in Washington, D.C. to break down China vs U.S. strategies—open-source diffusion vs big tech global dominance— and what “winning” actually means.
Helen has recently spent time in China and works at the center of U.S. AI policy—offering a rare inside view of both ecosystems and who’s truly ahead.
Helen explains:
- Who’s ahead right now and how to measure it (frontier AI vs adoption/diffusion)
- Open-source vs closed: DeepSeek, Qwen, Kimi, Gemma, Llama vs OpenAI, Anthropic, Google
- Compute & chips: NVIDIA dependence, export controls, and why compute concentration matters
- AGI timelines: whether “AI 2027” holds up and why short timelines cooled after GPT-5
- “AI+” strategy: applying AI to manufacturing, healthcare, and finance vs pure frontier bragging rights
- What governments should do now: transparency, auditing, AI literacy, and measurement science
Who do you think is winning and WHY – China or the U.S.? Drop one evidence-backed reason (links welcome). We’ll pin the best reply.
Don’t forget to like and subscribe for more unfiltered conversations on AI, tech, and society.
Chapters
00:00 – Two strategies, one AI race
01:00 – Open-source China vs Big-Tech USA
03:37 – Not one race: choose your finish line
04:04 – Who’s actually open? DeepSeek, Qwen/Kimi, Llama, Gemma, GPT-OSS
06:26 – Frontier bragging rights vs real-world adoption
07:46 – China’s “AI Plus” play (AI + industry)
10:06 – Is the US still ahead at the frontier?
12:04 – GPT-5 reality check & AGI timelines
20:58 – Compute decides: chips, export controls, auto-ML engineers
23:04 – What we need now: transparency, audits, AI literacy
28:02 – Standards in practice: de-facto beats de-jure
30:56 – Next 5 years: closed peaks, open bow wave
37:55 – Final take: which path wins?
#OpenAI #HelenToner #ai #GPT5 #OpenSource #podcast #China #DeepSeek
Has OpenAI made the WRONG bet?
Gary Marcus argues that OpenAI is taking the wrong approach - and the AI bubble is real. We walk through why GPT-5 underwhelmed, where the scaling paradigm breaks, and what might really get us to AGI.
Gary explains:
– Why the economics don’t add up for current AI
– Why GPT-5 isn’t as good as expected
– The core LLM limitations and why the scaling paradigm fails
– Why AI won’t take your job in the near term
– A practical path to AGI (hybrid / neuro-symbolic, world models)
We also debate whether investors are over- or under-valuing AI, what productivity gains are real, and how long it will take before AI truly replaces jobs.
References discussed in this episode:
– Gary Marcus, The Algebraic Mind: Integrating Connectionism and Cognitive Science (2001)
– Gary Marcus, “Deep Learning Is Hitting a Wall” (Nautilus, 2022)
– Gary Marcus, The Next Decade in AI (arXiv, 2020)
– Mike Dash, Tulipomania
Do you think Gary is right—or are we just getting started? Drop one strong piece of evidence either way (links welcome). We’ll pin the best reply. Don’t forget to like and subscribe for more unfiltered conversations on AI, tech, and society.
Chapters
00:00 – Is AI in a bubble?
00:30 – AI hype vs. reality
01:10 – GPT-5 launch: disappointment or progress?
03:50 – Can AI be both a revolution and a bubble?
05:40 – Productivity gains and investment hype
08:00 – Gary Marcus joins the conversation
09:30 – Why Gary calls himself a skeptic
11:15 – GPT-5 and the limits of scaling
14:00 – Financial reality of large language models
17:20 – “Deep Learning Is Hitting a Wall”
19:00 – Why hallucinations won’t go away
21:00 – Neuro-symbolic AI explained
24:00 – Building world models for AI
27:00 – Are AI valuations sustainable?
29:30 – Lessons from Tulipomania
31:30 – Will AI take all our jobs?
36:00 – What comes next for AI research
38:30 – Final thoughts
#OpenAI #GaryMarcus #ai #GPT5 #scaling #podcast
AI agents can’t easily talk to each other. To solve this, Cisco has joined forces with Google, Dell, Oracle, and Red Hat to launch AGNTCY, the open-source Internet of Agents. It’s designed so agents from different organizations can discover, trust, and work together - and it’s now donated to the Linux Foundation for neutral governance.
Vijoy Pandey, Senior VP and GM of Outshift by Cisco, explains how AGNTCY tackles interoperability, why secure messaging (via SLIM) matters, and how enterprises are already using multi-agent systems in the real world. We also look ahead to quantum networking - the next frontier Cisco and its partners are preparing for, connecting processors and data centers across vast distances.
👉 Tell us in the comments how you see open-source agents changing your industry.
Visit AGNTCY.org
Visit Outshift.com
Chapters
00:00 Cold open
00:34 Welcome and hosts
01:45 Why interoperability is the bottleneck
03:10 What AGNTCY enables
05:55 Trust, identity, and evaluation
12:40 SLIM and secure agent messaging
16:45 Real-world deployments
20:10 From pilots to production
21:55 Open source and Linux Foundation
25:20 Quantum networking outlook
28:50 Final thoughts and CTA
Guest:
Vijoy Pandey, SVP and GM, Outshift by Cisco
#AI #Agents #Cisco #AGNTCY #Interoperability #OpenSource #LinuxFoundation #Quantum #AgenticAI #Outshift
AI is changing the way we do biology. But can it crack one of the toughest challenges in science — drug discovery?
In this episode of Agents of Tech, we speak with Professor Charlotte Deane, MBE, University of Oxford, one of the UK’s leading computational biologists. As a co-lead of OpenBind, Charlotte is helping build the global data infrastructure needed to accelerate drug discovery with AI.
From the role of open science to the cultural gap in innovation between the US and UK, Charlotte explains why the UK, despite its size, continues to punch well above its weight in AI and computational biology.
📍 Recorded live at ISMB/ECCB in Liverpool, the world’s leading computational biology conference.
🔔 Subscribe to Agents of Tech for more conversations with the people shaping the future of AI, science, and society: https://www.youtube.com/@AgentsOfTech
#AI #DrugDiscovery #CharlotteDeane #UKAI #Biology #AgentsOfTech
00:00 Intro: AI’s toughest challenge – drug discovery
00:27 Welcome to Agents of Tech at ISMB/ECCB, Liverpool
01:00 Why is drug discovery so hard for AI?
02:00 The UK and AI: overlooked but world-class
05:57 Innovation culture: risk-taking in the UK vs US
08:00 Introducing Professor Charlotte Deane
09:12 What is the OpenBind consortium?
13:00 Pharma data vs open science data
15:59 How the UK punches above its weight in AI
19:20 Training the next generation of AI-literate scientists
22:00 How AI will change the way science is done
25:00 Can AI ask better scientific questions?
27:40 How AI is changing drug discovery workflows
32:00 Final thoughts from Charlotte Deane
34:00 Host debrief: UK AI, OpenBind, and the future of biology
Can artificial intelligence replace scientists? At Stanford University, Professor James Zou is leading research on AI scientists, virtual labs, and digital researchers that are already transforming biology and medicine.
In this episode of Agents of Tech, recorded live at ISMB/ECCB in Liverpool, James explains how his lab is building virtual research teams powered by AI. These “digital scientists” act like a real lab, with specialized roles in immunology, chemistry, and computational biology. They collaborate, design experiments, and even help discover potential Covid vaccine candidates.
We discuss:
How AI schools train agents to become domain experts in days
Why virtual conferences run by AI could change scientific publishing
What James’s team learned from designing nanobody therapies with AI
The future of human and AI collaboration in science
Read James Zou’s recent Nature paper on AI scientist agents: https://www.nature.com/articles/s41586-025-09442-9
Subscribe for more conversations with global AI and science leaders: https://www.youtube.com/@AgentsOfTech
#AI #Science #JamesZou #Stanford #VirtualLabs #ComputationalBiology #ArtificialIntelligence #MachineLearning
Chapters (time-coded)
00:00 – AI isn’t just a tool, it’s becoming the scientist
00:17 – Meet Professor James Zou of Stanford
00:41 – What are AI “virtual labs”?
01:07 – Can AI replace human researchers?
02:00 – The promise and fear of agentic AI
03:15 – Building AI teams with different expertise
04:45 – Human creativity vs virtual collaboration
05:36 – James Zou explains the concept of virtual labs
06:40 – Early success: AI scientists design Covid nanobody candidates
08:20 – Why virtual labs are more than large language models
09:40 – Specialized AI agents with domain expertise
11:05 – Human collaboration with AI scientists
12:20 – Filling critical expertise gaps with AI
13:45 – How virtual labs “teach themselves” through AI schools
15:20 – The problem of agreeable AIs and why critics are needed
17:00 – Bias in literature and how AI agents learn
18:45 – Trust and experimental validation in AI science
20:20 – Why human scientists still matter in the lab
21:10 – Next steps for Stanford’s virtual lab research
22:20 – Potential applications in biology, medicine, and beyond
23:20 – The future of AI-run conferences and publishing
25:10 – Explosion of research papers and the role of AI reviewers
26:00 – Reactions: Are AI scientists partners or competitors?
29:20 – What does AI mean for the future of human discovery?
30:00 – Closing thoughts and thanks to James Zou
In this exclusive Agents of Tech interview from ISMB/ECCB in Liverpool, we sit down with Dr. John Jumper, Nobel Laureate and leader of the groundbreaking AlphaFold project at Google DeepMind.
Discover how AlphaFold reshaped molecular biology by accurately predicting protein structures, and hear Jumper's vision for using AI to not just predict biology, but design it. Join us as we explore the future of computational biology, scientific reasoning with AI, and what’s next for this Nobel Prize-winning scientist.
00:00 - Introduction to John Jumper and AlphaFold
00:29 - ISMB/ECCB Liverpool Overview
01:00 - AlphaFold's Impact on Structural Biology
02:10 - Understanding Protein Structures with AlphaFold
04:14 - Google's Role in Scientific Innovation
05:20 - AlphaFold’s Influence Beyond Biology
05:55 - Welcoming John Jumper
06:23 - Why ISMB/ECCB Conference?
06:55 - How Does AlphaFold Work?
08:46 - Surprising Applications of AlphaFold
09:17 - Importance of Protein Databank (PDB)
12:00 - Industrial Science and the Nobel Prize
14:14 - Ingredients of AI: Data, Compute, Research
17:38 - Collaborative Teams in Modern Science
18:50 - Responsibility as a Public Intellectual
22:02 - Jumper’s Next Big Research Question
25:56 - Public Trust in AI
31:56 - Scientific Method and AI Predictions
34:01 - Concluding Thoughts
#AlphaFold #JohnJumper #GoogleDeepMind #AgentsOfTech #AI #ArtificialIntelligence #MachineLearning #ComputationalBiology #StructuralBiology #ScienceInnovation #ISMB #ISCB2025 #ECCB2025 #LiverpoolScience #NobelPrize #NobelPrize2024 #NobelLaureate #Podcast
In this episode of Agents of Tech, we dive into agentic AI, a new kind of artificial intelligence designed to enhance human agency rather than automate people out of the loop.
We’re joined by Dr. Niloufar Salehi, Assistant Professor at UC Berkeley and Chief Product Officer at Across AI. Her work spans healthcare, education, criminal justice, and the creative industries. She explains why most AI systems misunderstand how people actually work, and what it will take to build systems that empower rather than override human judgment.
Topics include:
- The rise of agentic AI and what it means for work
- Case studies in medicine, law, and content creation
- Why most automation fails in the real world
- The hidden risks of synthetic data and algorithmic bias
- What we can learn from creatives trying to outsmart YouTube’s algorithm
This is a must-watch if you’re thinking about AI and ethics, human-computer interaction, or the future of decision-making in high-stakes settings.
00:00 Intro to Agentic AI
00:16 Meet Dr. Niloufar Salehi
00:24 What is Agentic AI?
00:48 Hosts Discuss Human-AI Interaction
04:00 Guest Interview Begins
04:40 HCI and Interdisciplinary Design
06:34 Algorithmic Misconceptions
07:11 Xerox PARC & HCI Origins
10:48 AI in Healthcare: What Works
13:26 Translation Risk in Medicine
16:08 AI in the Courtroom
19:02 Synthetic Data: Power & Pitfalls
21:00 YouTube Creators & Algorithm Personas
26:00 Designing Interfaces Around Human Strengths
29:00 AI in Hiring, Policing & Due Process
31:00 AI That Offers Options, Not Orders
32:30 Future of AI & Human Collaboration
📘 Plans and Situated Actions – Lucy A. Suchman
• Chapter “Situated Actions” in Human Machine Reconfigurations
DOI: 10.1017/CBO9780511808418.008 (asmepublications.onlinelibrary.wiley.com, Cambridge University Press & Assessment)
📘 AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference – Arvind Narayanan & Sayash Kapoor
• DOI for an excerpt in Stanford Social Innovation Review: 10.48558/0Z9Z DR86 (Stanford Social Innovation Review)
• DOI for a full-length review article: 10.1215/2834703X 11700273 (Cambridge University Press & Assessment, Duke University Press)
📕 Study: Effect of Prior Diagnoses on Dermatopathologists' Interpretations…
• DOI: 10.1001/jamadermatol.2022.0000
📕 Study: Disparities in Dermatology AI: Assessments Using Diverse Clinical Images
• DOI: 10.1126/sciadv.abq6147 (Science)
Artificial intelligence is revolutionizing scientific research—but can it really replace human scientists? In this episode of Agents of Tech, we speak with Professor Jose Panadas and Dr. Tiago Costa from Imperial College London about their groundbreaking collaboration with Google's Gemini 2.0 AI co-scientist.
Within just two days, AI unraveled a scientific mystery they'd spent years exploring. But what does this rapid success mean for human researchers and the future of science itself?
🔑 Key highlights:
How Google's AI co-scientist generates novel scientific hypotheses
Why AI may accelerate—but not replace—human discovery
The surprising ways AI avoids human biases in scientific research
Subscribe for more cutting-edge insights from Agents of Tech!
#AI #ArtificialIntelligence #ScienceInnovation #GoogleAI #AIResearch #AgentsOfTech.
Research Paper: https://storage.googleapis.com/coscientist_paper/ai_coscientist.pdf
0:00 – Intro: The AI Era in Science
0:20 – The Problem AI Solved in 2 Days
0:52 – What Are AI Co-Scientists?
1:16 – Can AI Generate Entirely New Hypotheses?
1:43 – Hosts Discuss the Implications of AI Collaboration
2:34 – Difference Between AI Bots and AI Co-Scientists
3:33 – Skepticism About AI’s Scientific Creativity
5:27 – Could AI Break Free from Outdated Knowledge?
7:45 – Interview Start: José Penadés & Tiago Costa
9:00 – How AI Avoids Human Bias in Science
10:06 – AI’s Ability to Generate Original Hypotheses
12:41 – Overcoming Human Scientific Biases
14:03 – Will AI Accelerate Discovery or Complicate Science?
15:25 – Obstacles to AI-generated Breakthroughs
16:12 – Can AI Innovate Across Disciplines?
18:23 – Human Intuition vs. AI-generated Hypotheses
21:01 – Could AI Ever Formulate Revolutionary Ideas?
23:36 – The Human Role: Asking the Right Questions
25:52 – AI and the Future of Peer Review
27:52 – Advice for Young Scientists Using AI
29:00 – Final Thoughts: AI's Role in Future Science
30:39 – Closing & Credits
Is generative AI replacing workers—or helping them thrive? In this episode of Agents of Tech, we explore how AI is transforming the global workforce. Economist Lindsey Raymond (Microsoft Research), co-author of a groundbreaking study with Erik Brynjolfsson and Danielle Li, joins us to unpack how AI tools are boosting productivity, equalizing skills, and reshaping the modern job.We cover:• AI’s impact on job creation and automation (World Economic Forum’s 2025 forecast)• Why AI helps junior workers most—but might demotivate top performers• How “editor over producer” is becoming the new workplace model• Whether AI narrows or widens global inequality• What skills will remain uniquely human• How AI tools can power faster business scaling—and redesign the nature of jobs🎧 Featuring:• Lindsey Raymond, Microsoft Research• Autria Godfrey, Laila Rizvi & Stephen Horn, Agents of Tech hostsSubscribe for more deep dives into AI, tech, and the future of work.🔔 Don’t forget to like, comment, and share.Papers and Reportshttps://academic.oup.com/qje/article/140/2/889/7990658?login=falsehttps://www.weforum.org/publications/the-future-of-jobs-report-2025/?gad_source=1&gclid=Cj0KCQjw4cS-BhDGARIsABg4_J3j8i_TwZLC_yzLxuOzrfHphxgBT02X0IWMRTUUYM27PICz30xiJRsaAvEUEALw_wcB#GenerativeAI #FutureOfWork #ArtificialIntelligence #AIandJobs #AIAutonomy #WorkplaceTransformation #ErikBrynjolfsson #LindseyRaymond #AIProductivity #AgentsOfTech
Can AI help us survive extreme weather and climate change—or is it part of the problem?
In this episode of Agents of Tech, we speak to Professor Auroop Ganguly, Director of AI for Climate and Sustainability at Northeastern University, about how artificial intelligence is being used to predict disasters, improve infrastructure resilience, and shape sustainable climate policy.
🌀 We discuss:
• How AI predicts floods, wildfires, and extreme weather
• The rising energy cost of AI and the push for green computing
• Challenges in low-data regions and climate modelling
• Why AI needs governance to support sustainability goals
• Using AI to build infrastructure that can withstand climate shocks
🚨 AI is powerful, but not a magic bullet. Tune in for a grounded look at the promises, limits, and risks of AI in the climate fight.
📍 Guest: Professor Auroop Ganguly, Northeastern University
🎙️ Hosts: Autria Godfrey & Laila Rizvi
📺 Produced by WebsEdge
🔗 Subscribe for more on the future of AI, climate tech, and innovation.
#ClimateChange #AI #Sustainability #ClimateTech #AuroopGanguly #GreenComputing #DisasterResilience #AgentsOfTech #ExtremeWeather #MachineLearning #AIClimateModels #TVA #FloodPrediction #ClimateAdaptation #NetZero #AIethics #aigovernance
CHAPTERS
00:33 – The climate crisis and the AI dilemma
01:30 – Can AI help or harm the planet?
02:45 – Guest intro: Professor Auroop Ganguly
04:10 – How AI supports climate resilience
06:00 – Case study: NASA-funded flood prediction with AI
08:30 – Improving infrastructure with predictive models
10:00 – AI’s limits in reducing emissions
11:45 – Can DeepSeek lead to greener AI?
13:00 – Making climate models more accurate with AI
15:30 – The Global South's data gap problem
17:20 – Using transfer learning in low-data regions
18:40 – Combining AI with physics for better predictions
20:00 – The energy demands of AI explained
22:00 – Why governance matters for sustainable AI
23:30 – AI's role in shaping future climate policy
25:00 – Risks of bias in disaster AI systems
26:30 – Innovation, equity, and evolution over revolution
28:00 – Hosts’ reflections: What we learned
https://www.nature.com/articles/s41467-023-35968-5
We’re entering an era where AI systems don’t just follow prompts—they act independently. But what happens when we hand over too much control?
In this episode of Agents of Tech, our hosts Stephen Horn, Autria Godfrey and Laila Rizvi sit down with Margaret Mitchell, Chief Ethics Scientist at Hugging Face and one of the world’s leading voices on AI ethics. Together, they explore what autonomy really means in artificial intelligence—and why we can’t afford to be passive observers.
#AIEthics #ResponsibleAI #TechForGood #EthicalAI #HumanInTheLoop #AIRegulation
Topics include:
🔹 Why AI autonomy is fundamentally different from traditional automation
🔹 The real risks of removing human oversight
🔹 How trust and anthropomorphism distort our judgment
🔹 What “human in the loop” must mean going forward
This is a must-watch conversation for anyone working with AI—or impacted by it (which means all of us).
https://huggingface.co/papers/2502.02649
🎧 Listen now on your favorite podcast platform and subscribe for more deep tech insight.
0:00:00 - Intro: Are we giving AI too much control?
0:00:17 - Meet DeepSeek and Monica – the next-gen AI agents
0:00:58 - The ethics of autonomous AI
0:02:13 - Guest intro: Margaret Mitchell on AI autonomy
0:04:12 - Human control vs machine independence
0:06:25 - AI, society, and the illusion of moral reasoning
0:07:49 - Security risks from autonomous coding agents
0:11:27 - The BBC analogy & user-generated chaos
0:13:42 - Deepfakes, consent & harmful content
0:15:45 - Why AI doesn’t think like us
0:17:22 - Sensitive data, agents & social media nightmares
0:19:30 - Ease vs privacy: Why people give up control
0:21:00 - Good uses of agents: Accessibility & productivity
0:22:30 - AI and the future of creative jobs
0:24:20 - Capitalism, AGI & the wealth imbalance
0:26:10 - Margaret's message to governments
0:27:50 - Rights-based regulation vs restriction
0:29:35 - Looking 10 years ahead: Margaret’s fears & hopes
0:31:30 - Final reflections: Are we too late?
0:35:30 - Outro: Like, share & subscribe!
In this episode of Agents of Tech, hosts Autria Godfrey and Stephen Horn dive deep into one of AI’s most pressing challenges: energy consumption. With the release of DeepSeek and rising concerns over compute power and costs, the race to build efficient AI is heating up.We speak to two pioneering researchers:Dr. Shreyas Sen (Purdue University), who’s developing nervous-system-inspired chips that connect wearables with ultra-low energy use.Dr. Hongyin Luo (MIT CSAIL / BitEnergy AI), whose work on Linear-Complexity Multiplication (L-Mul) may drastically cut compute cost and energy usage.Is the future of AI massive centralized data centers — or decentralized personal clouds and localized compute? And what happens when we run out of training data?👉 Don’t forget to like, comment, and subscribe to support meaningful tech discussions!⏱️ Timestamps / Chapters:00:00 - Introduction: Welcome to Agents of Tech00:20 - Why AI energy usage is an urgent issue01:00 - DeepSeek’s $6M run and the energy debate02:00 - The promise of mixture-of-experts and energy savings02:45 - Interview intro: Dr. Hongyin Luo (BitEnergy AI)03:25 - What is L-Mul and why it matters06:00 - Floating-point vs integer math in AI08:30 - Shifting compute from datacenters to the edge10:00 - Barriers to L-Mul adoption and FPGA innovation12:00 - The case for local family clouds13:30 - Moonshot idea: Stop pretraining to save energy15:00 - Interview intro: Dr. Shreyas Sen (Purdue University)15:45 - Wearable brains and nervous-system-inspired design17:30 - Conductive human body as an AI network19:00 - Brain-to-device communication breakthroughs21:30 - Data layers: cloud, edge, and leaf devices23:00 - Real-world use and commercialization of Wi-R tech24:00 - Future implications and distributed AI potential26:00 - Panel discussion: What does efficient AI really mean?28:30 - The end of training and rise of true intelligence?30:00 - From megawatt datacenters to household AI hubs32:00 - Wrap-up and reflections33:55 - Credits and thanks#ArtificialIntelligence #AI #EnergyEfficiency #GreenAI #EdgeComputing #BrainInspiredTech #WearableTech#NeuralNetworks #BodyPoweredAI #futureofai #SustainableTech #AIChips #AIInnovation #SmartWearables
What if a virtual version of you could help cure disease?
In this episode of Agents of Tech, hosts Autria Godfrey and Stephen Horn explore the fascinating world of digital twins—virtual replicas of real-world entities that are revolutionizing industries, especially healthcare. From their origins in NASA’s Apollo missions to accelerating clinical trials today, digital twins are changing how we predict, prevent, and personalize treatment.
Featuring Aaron Smith, founder and machine learning scientist at UnLearn, we discuss how AI-driven digital twin models are transforming clinical trials—cutting costs, speeding up timelines, and reducing the need for placebo groups.
Don’t forget to like, comment, and subscribe for more deep dives into the future of tech and science.
00:00 - Welcome to Agents of Tech
00:15 - What are Digital Twins?
01:00 - Origins in NASA and Apollo 13
01:30 - From Static to Intelligent Twins
02:30 - AI-powered evolution: Science fiction becomes science fact
03:45 - Applications in Medicine & Clinical Trials
04:30 - Guest intro: Aaron Smith from UnLearn
05:10 - How Digital Twins Accelerate Clinical Trials
07:00 - The AI models behind the magic
08:20 - Why focus on clinical trials, not patient care?
10:15 - Reducing risk and increasing trial power
12:00 - Future of Phase 3 trials
13:30 - The long-term vision for digital twins in medicine
15:00 - Placebo groups and statistical innovation
17:00 - Machine learning in rare diseases
18:20 - Regulatory frameworks: EMA & FDA alignment
21:00 - What makes a disease suitable for digital twin modeling?
22:30 - Pharma partnerships and proprietary data
24:00 - Recap: Why this tech changes everything
25:15 - Outro: Like & subscribe!
Welcome to Agents of Tech, where we explore the innovations shaping tomorrow. In this episode, we dive into how digital twins are transforming personalized medicine, featuring Terry Poon, CTO of Twin Health.
From reversing disease to real-time metabolic modeling, learn how AI, wearables and data-driven empathy are creating a new era of preventative healthcare.
🔗 Subscribe for more conversations with the visionaries behind tomorrow’s tech.
📣 Like, comment, and share to support the show!
#DigitalTwins #HealthcareAI #TwinHealth #PersonalizedMedicine #AgentsOfTech.
00:00 - Intro: What Are Digital Twins in Healthcare?
00:27 - From Sci-Fi to Reality: Digital Twins Today
01:14 - Meet Terry Poon, CTO at Twin Health
01:54 - Understanding Unique Metabolic Responses
02:31 - Why NASA’s Tech is Now Revolutionizing Medicine
03:20 - The Holistic Power of Digital Twins
04:22 - Real-World Use: Predicting Heart Attacks & Optimizing Hospitals
05:00 - Disclaimer: Medical Info vs Professional Advice
05:14 - Terry Poon on What Digital Twins Actually Do
06:36 - Reversing Disease, Not Just Managing It
07:33 - The Data That Powers Twin Health’s Success
08:55 - Tackling the Complexity of Human Metabolism
10:07 - How AI Makes Sense of 10 Billion+ Data Points
11:33 - Data Quality + Quantity = Better Outcomes
12:20 - Combining AI + Human Empathy in Care
13:33 - Could This Approach Go Beyond Metabolic Disease?
14:25 - Can AI Discover What Humans Can’t See?
15:57 - Surprising Patterns: Morning vs Afternoon Exercise
16:33 - What True Personalization Takes to Work
17:32 - The Tight Feedback Loop That Fuels Change
18:33 - Advice for AI Innovators in Healthcare
19:39 - A Future Without One-Size-Fits-All Medicine
20:41 - Empathy: The Underrated Key to Patient Adherence
21:17 - Final Thoughts & Takeaways
Welcome to Agents of Tech! In this episode, we dive into the future of data storage with the visionary Dr. Stuart Parkin. A pioneer in spintronics and the inventor of racetrack memory, Dr. Parkin’s groundbreaking work has shaped the way we store and process data in the digital age. With AI’s insatiable demand for data, how do we keep up? Dr. Parkin shares insights into the challenges of traditional storage, the revolutionary potential of spintronics, and how racetrack memory could transform AI and computing as we know it.
🔹 How does AI’s growing demand impact data storage?
🔹 What is spintronics, and how does it work?
🔹 Can racetrack memory revolutionize computing?
🔹 How close are we to commercializing this next-gen storage technology?
Tune in to find out! If you enjoy the conversation, don’t forget to like, subscribe, and share to help us bring more groundbreaking discussions to you.
00:00 - Introduction to Agents of Tech & AI’s Data Challenge
00:06 - Meet Dr. Stuart Parkin & His Impact on Data Storage
00:28 - How the Spin Valve Revolutionized Storage Technology
01:26 - The Growing Bottleneck: AI’s Increasing Data Needs
03:00 - Spintronics & The Promise of Racetrack Memory
05:29 - Dr. Stuart Parkin’s Journey & Groundbreaking Innovations
07:32 - Overcoming Storage Barriers & The Future of Spintronics
10:06 - The Push for Energy-Efficient Computing & AI
13:31 - Why Racetrack Memory is Critical for AI & Big Data
16:56 - The Investment Needed to Make Racetrack Memory Mainstream
18:56 - Neuromorphic Computing & The Future of AI Hardware
23:39 - Final Thoughts & Closing Remarks
AI is advancing at a breakneck pace, but how will we store the massive amounts of data it requires? In this episode of Agents of Tech, hosts Autria Godfrey, Stephen Horn, and Laila Rizvi explore the growing demand for AI data storage and the innovations shaping the future.
💡 We break down:
- The Stargate Project, a $500 billion AI infrastructure investment
- DeepSeek AI, a cost-efficient rival to ChatGPT?
- The next frontier of data storage – synthetic DNA
- How biology meets computing to create a more sustainable tech future
We’re joined by Dr. Jeff Nivala, Co-Director of the Molecular Information Systems Lab (University of Washington & Microsoft), to discuss the groundbreaking potential of DNA-based storage and its role in the future of AI.
🚀 If you enjoy the episode, don’t forget to like, subscribe, and share to stay up to date with cutting-edge tech discussions!
📌 Follow us for more:
Bluesky: @agentsoftech.bsky.social
TikTok: @Agents_of_Tech
Instagram: @agents_of_tech_
X/Twitter: @Agents_of_Tech
#AI #DataStorage #DeepSeek #DNAStorage #techpodcast
Chapters:
00:00 - Welcome to Agents of Tech
00:11 - The AI data storage crisis
00:42 - The $500B Stargate Project – The U.S. bets big on AI
01:22 - The rise of DeepSeek AI – Can it rival ChatGPT?
02:44 - Mark Zuckerberg’s AI ‘war room’
03:37 - Meet our guest: Laila from WebsEdge
04:52 - The storage bottleneck – why AI outpaces traditional infrastructure
06:47 - The innovation lag: Can engineers solve AI’s storage problem?
08:33 - Dr. Jeff Nivala joins the discussion
09:46 - How synthetic DNA can store digital data
12:00 - Can DNA replace traditional data centers?
14:33 - The intersection of biology and computing
16:21 - DNA vs. traditional computing: A paradigm shift
18:45 - Scaling DNA-based storage – When will it be practical?
21:00 - The future of AI storage: Data forests instead of data centers?
23:00 - Final thoughts & wrap-up
Program Notes:
https://openai.com/index/announcing-the-stargate-project/
https://fortune.com/2025/01/27/mark-zuckerberg-meta-llama-assembling-war-rooms-engineers-deepseek-ai-china/
In this episode of Agents of Tech, we explore the rapidly evolving landscape of artificial intelligence and its intersection with cybersecurity. Our host, Autria Godfrey, is joined by Dr. Siwei Lyu, Director of the University at Buffalo Media Forensics Lab, and Dr. Damon McCoy, Co-Director of the NYU Center for Cybersecurity, to discuss the challenges and opportunities presented by AI.
From the dangers of deepfakes and their role in misinformation to the vulnerabilities of critical infrastructures, our guests weigh in on the pressing need for innovative detection tools, ethical AI development, and global cybersecurity collaboration. Dr. Lyu introduces his groundbreaking DeepFake-o-Meter, while Dr. McCoy highlights real-world examples of AI-enhanced cyberattacks and shares insights on safeguarding data in an era of decentralization.
If you’re interested in the cutting-edge applications of AI in cybersecurity and the measures being taken to protect against its misuse, this episode is a must-watch.
Don’t forget to like, subscribe, and share to stay updated on the latest in AI innovation.
🔗 https://www2.deloitte.com/us/en/insights/industry/financial-services/financial-services-industry-predictions/2024/deepfake-banking-fraud-risk-on-the-rise.html
🔗 https://sensity.ai/reports/
#AI #Cybersecurity #Deepfakes #ArtificialIntelligence #Technology #AIForGood #CyberThreats #DataSecurity #AIResearch #TechInnovation #Misinformation #DigitalSafety #AIandEthics #FutureOfAI #DeepfakeDetection #CyberAwareness #TechPodcast #AgentsOfTech #AIInnovation #AIinCybersecurity #MediaForensics #AIForSecurity
Chapters:
00:00 - Welcome to Agents of Tech
00:08 - Introduction to AI and Cybersecurity
00:44 - Exploring Deepfakes: A Modern Challenge
01:50 - Guest Introduction: Dr. Siwei Lyu
03:30 - How the DeepFake-o-Meter Detects Manipulated Media
07:00 - Challenges in Deepfake Detection and Bias in AI Models
12:40 - The Growing Threat of AI-Driven Fraud
14:00 - Public Awareness and Education on Deepfakes
16:50 - Ethical Use of AI: Benefits and Risks
19:00 - Guest Introduction: Dr. Damon McCoy
20:40 - AI in Cybersecurity: Vulnerabilities in Critical Infrastructure
23:00 - The Threat of Data Poisoning in AI Systems
27:10 - Real-World Examples of AI-Driven Cyber Attacks
30:00 - Insider Threats and Protecting Sensitive Data
34:10 - Addressing Global Cybersecurity Norms and Collaboration
38:00 - Building a Culture of Cybersecurity Awareness
42:00 - Final Thoughts: Aligning Incentives in Cybersecurity
45:00 - Closing Remarks and Acknowledgments
Join us on this episode of Agents of Tech as we explore the transformative potential of quantum science with the brilliant Professor Erica Carlson from Purdue University. 🎙️ Discover how quantum mechanics is shaping the future of technology, tackling global challenges like climate change, energy efficiency, and more. With engaging insights into superconductors, quantum materials, and neuromorphic computing, this conversation will leave you in awe of the possibilities the Quantum Age holds.
✨ Don’t miss her inspiring journey, educational initiatives, and her unique approach to making complex quantum concepts accessible to everyone.
🗓️ Special focus on the upcoming United Nations International Year of Quantum Science and Technology 2025, celebrating 100 years of quantum mechanics.
🎧 Subscribe for more insights into the cutting-edge innovations shaping our future!
Dr Erica Carlson's YouTube Channel: https://www.youtube.com/channel/UCN6ygeEojVhJqocfAxP2wqw.
Richard Feynman Lectures: https://www.feynmanlectures.caltech.edu/.
#QuantumScience #QuantumMechanics #Technology #Innovation #FutureTech #Superconductors #QuantumMaterials #NeuromorphicComputing #UN2025 #SciencePodcast #AgentsOfTech
Chapters:
00:00 - Welcome to Agents of Tech
00:14 - Exploring the Quantum Age with Professor Erica Carlson
00:45 - UN's International Year of Quantum Science 2025
02:20 - What is Quantum Mechanics?
04:00 - Professor Carlson’s Journey into Quantum Physics
06:50 - Superconductors and Their Quantum Effects
09:30 - The Fascinating World of Liquid Crystals
11:40 - Making Quantum Science Accessible: Podcasts, YouTube, and More
14:05 - Particle-Wave Duality: The Beauty of Quantum Physics
16:30 - Advances in Quantum Materials
18:45 - The Role of Quantum Science in Solving Global Challenges
21:30 - Neuromorphic Computing and the AI Revolution
24:15 - How Quantum Discoveries Shape the Future
27:00 - Why Quantum Technology Matters to Everyone
28:45 - Closing Thoughts: Celebrating the Quantum Age
In this episode of Agents of Tech, Stephen Horn and Autria Godfrey explore the rapidly evolving world of Artificial Intelligence and ask the pressing questions: Can we trust AI? Is it safe? AI is becoming deeply embedded in every aspect of our lives, from healthcare to transportation, but how do we ensure it aligns with ethical principles and remains trustworthy?
Featuring insights from:
Dr. Shyam Sundar, Director of the Center for Socially Responsible AI at Penn State, who discusses the role of ethics and trust in AI systems.
Dr. Duncan Eddy, Executive Director of the Stanford Center for AI Safety, who shares lessons from aerospace safety and how they apply to AI.
Join us as we examine the balance between technological advancement and safety, explore the role of regulation, and dive into the psychology of trust in AI. With perspectives on global AI trends, cultural differences in trust, and what the future holds, this is a must-watch for anyone curious about AI's impact on our society.
#ArtificialIntelligence #AISafety #AITrust #EthicalAI #FutureOfAI #MachineLearning #AIFuture #AIInnovation #TechEthics #AgentsOfTech
00:00 - Welcome to Agents of Tech
Stephen Horn and Autria Godfrey introduce the episode, broadcasting from London and Washington, D.C., and pose today’s critical question: Can we trust AI?
02:15 - AI in Our Lives: Benefits and Risks
A discussion on how AI is rapidly transforming industries like healthcare, finance, education, and transportation. But with this integration come concerns about ethics, bias, and safety.
05:30 - Ethical Implications of AI
Exploring the challenges of making AI systems socially accountable and the ethical dilemmas arising from unchecked AI development.
10:00 - Conversation with Dr. Shyam Sundar
Dr. Sundar, Director of the Center for Socially Responsible AI at Penn State, explains how AI’s conversational nature impacts trust and how personalization can lead to both engagement and misplaced trust.
15:45 - Cultural Differences in AI Trust
A fascinating look at how different cultures approach and trust AI systems, highlighting the global nature of AI challenges.
20:00 - Dr. Duncan Eddy on AI Safety Frameworks
Dr. Eddy, Executive Director of the Stanford Center for AI Safety, draws parallels between aerospace safety systems and AI, offering insights into incremental safety improvements and regulation.
25:30 - Can Regulation Keep Up with AI?
A discussion on global efforts like the EU AI Safety Act and challenges in regulating both AI development and deployment, especially in high-risk applications.
30:15 - How to Verify AI Outputs
Examining methods like adaptive stress testing and formal verification to improve AI reliability and avoid catastrophic errors in fields such as medicine and finance.
35:00 - The Future of AI Safety and Trust
Closing thoughts on how AI safety research is racing to keep up with innovation, the importance of fostering a culture of safety, and ensuring trustworthiness as AI becomes ubiquitous.
38:00 - What’s Next on Agents of Tech?
A sneak peek at the next episode, where the focus will shift to deepfakes and cybersecurity with experts from NYU and the University of Buffalo. Trust in Artificial Intelligence