The 17 Best AI and Machine Learning TED Talks for Practitioners – Solutions Review
The editors at Solutions Review curated this list of the best AI and machine learning TED talks for practitioners in the field.
TED Talks are influential videos from expert speakers in a variety of verticals. TED began in 1984 as a conference where Technology, Entertainment and Design converged, and today covers almost all topics from business to technology to global issues in more than 110 languages. TED is building a clearinghouse of free knowledge from the worlds top thinkers, and their library of videos is expansive and rapidly growing.
Solutions Review has curated this list of AI and machine learning TED talks to watch if you are a practitioner in the field. Talks were selected based on relevance, ability to add business value, and individual speaker expertise. Weve also curated TED talk lists for topics like data visualization and big data.
Erik Brynjolfsson is the director of the MIT Center for Digital Business and a research associate at the National Bureau of Economic Research. He asks how IT affects organizations, markets and the economy. His books include Wired for Innovation and Race Against the Machine. Brynjolfsson was among the first researchers to measure the productivity contributions of information and community technology (ICT) and the complementary role of organizational capital and other intangibles.
In this talk, Brynjolfsson argues that machine learning and intelligence are not the end of growth its simply the growing pains of a radically reorganized economy. A riveting case for why big innovations are ahead of us if we think of computers as our teammates. Be sure to watch the opposing viewpoint from Robert Gordon.
Jeremy Howard is the CEO ofEnlitic, an advanced machine learning company in San Francisco. Previously, he was the president and chief scientist atKaggle, a community and competition platform of over 200,000 data scientists. Howard is a faculty member atSingularity University, where he teaches data science. He is also a Young Global Leader with the World Economic Forum, and spoke at the World Economic Forum Annual Meeting 2014 on Jobs for the Machines.
Technologist Jeremy Howard shares some surprising new developments in the fast-moving field of deep learning, a technique that can give computers the ability to learn Chinese, or to recognize objects in photos, or to help think through a medical diagnosis.
Nick Bostrom is a professor at the Oxford University, where he heads theFuture of Humanity Institute, a research group of mathematicians, philosophers and scientists tasked with investigating the big picture for the human condition and its future. Bostrom was honored as one ofForeign Policys 2015Global Thinkers. His bookSuperintelligenceadvances the ominous idea that the first ultraintelligent machine is the last invention that man need ever make.
In this talk, Nick Bostrom calls machine intelligence the last invention that humanity will ever need to make. Bostrom asks us to think hard about the world were building right now, driven by thinking machines. Will our smart machines help to preserve humanity and our values or will they have values of their own?
Lis work with neural networks and computer vision (with Stanfords Vision Lab) marks a significant step forward for AI research, and could lead to applications ranging from more intuitive image searches to robots able to make autonomous decisions in unfamiliar situations. Fei-Fei was honored as one ofForeign Policys 2015Global Thinkers.
This talk digs into how computers are getting smart enough to identify simple elements. Computer vision expert Fei-Fei Li describes the state of the art including the database of 15 million photos her team built to teach a computer to understand pictures and the key insights yet to come.
Anthony Goldbloom is the co-founder and CEO ofKaggle. Kaggle hosts machine learning competitions, where data scientists download data and upload solutions to difficult problems. Kaggle has a community of over 600,000 data scientists. In 2011 and 2012,Forbesnamed Anthony one of the 30 under 30 in technology; in 2013 theMIT Tech Reviewnamed him one of top 35 innovators under the age of 35, and the University of Melbourne awarded him an Alumni of Distinction Award.
This talk by Anthony Goldbloom describes some of the current use cases for machine learning, far beyond simple tasks like assessing credit risk and sorting mail.
Tufekci is a contributing opinion writer at theNew York Times, an associate professor at the School of Information and Library Science at University of North Carolina, Chapel Hill, and a faculty associate at Harvards Berkman Klein Center for Internet and Society. Her book,Twitter and Tear Gas was published in 2017 by Yale University Press.
Machine intelligence is here, and were already using it to make subjective decisions. But the complex way AI grows and improves makes it hard to understand and even harder to control. In this cautionary talk, techno-sociologist Zeynep Tufekci explains how intelligent machines can fail in ways that dont fit human error patterns and in ways we wont expect or be prepared for.
In his bookThe Business Romantic, Tim Leberecht invites us to rediscover romance, beauty and serendipity by designing products, experiences, and organizations that make us fall back in love with our work and our life. The book inspired the creation of the Business Romantic Society, a global collective of artists, developers, designers and researchers who share the mission of bringing beauty to business.
In this talk, Tim Leberecht makes the case for a new radical humanism in a time of artificial intelligence and machine learning. For the self-described business romantic, this means designing organizations and workplaces that celebrate authenticity instead of efficiency and questions instead of answers. Leberecht proposes four principles for building beautiful organizations.
Grady Booch is Chief Scientist for Software Engineering as well as Chief Scientist for Watson/M at IBM Research, where he leads IBMs research and development for embodied cognition. Having originated the term and the practice of object-oriented design, he is best known for his work in advancing the fields of software engineering and software architecture.
Grady Booch allays our worst (sci-fi induced) fears about superintelligent computers by explaining how well teach, not program, them to share our human values. Rather than worry about an unlikely existential threat, he urges us to consider how artificial intelligence will enhance human life.
Tom Gruberis a product designer, entrepreneur, and AI thought leader who uses technology to augment human intelligence. He was co-founder, CTO, and head of design for the team that created theSiri virtual assistant. At Apple for over 8 years, Tom led the Advanced Development Group that designed and prototyped new capabilities for products that bring intelligence to the interface.
This talk introduces the idea of Humanistic AI. He shares his vision for a future where AI helps us achieve superhuman performance in perception, creativity and cognitive function from turbocharging our design skills to helping us remember everything weve ever read. The idea of an AI-powered personal memory also extends to relationships, with the machine helping us reflect on our interactions with people over time.
Stuart Russell is a professor (and formerly chair) of Electrical Engineering and Computer Sciences at University of California at Berkeley. His bookArtificial Intelligence: A Modern Approach (with Peter Norvig) is the standard text in AI; it has been translated into 13 languages and is used in more than 1,300 universities in 118 countries. He also works for the United Nations, developing a new global seismic monitoring system for the nuclear-test-ban treaty.
His talk centers around the question of whether we can harness the power of superintelligent AI while also preventing the catastrophe of robotic takeover. As we move closer toward creating all-knowing machines, AI pioneer Stuart Russell is working on something a bit different: robots with uncertainty. Hear his vision for human-compatible AI that can solve problems using common sense, altruism and other human values.
Dr. Pratik Shahs research creates novel intersections between engineering, medical imaging, machine learning, and medicine to improve health and diagnose and cure diseases. Research topics include: medical imaging technologies using unorthodox artificial intelligence for early disease diagnoses; novel ethical, secure and explainable artificial intelligence based digital medicines and treatments; and point-of-care medical technologies for real world data and evidence generation to improve public health.
TED Fellow Pratik Shah is working on a clever system to do just that. Using an unorthodox AI approach, Shah has developed a technology that requires as few as 50 images to develop a working algorithm and can even use photos taken on doctors cell phones to provide a diagnosis. Learn more about how this new way to analyze medical information could lead to earlier detection of life-threatening illnesses and bring AI-assisted diagnosis to more health care settings worldwide.
Margaret Mitchells research involves vision-language and grounded language generation, focusing on how to evolve artificial intelligence towards positive goals. Her work combines computer vision, natural language processing, social media as well as many statistical methods and insights from cognitive science. Before Google, Mitchell was a founding member of Microsoft Researchs Cognition group, focused on advancing artificial intelligence, and a researcher in Microsoft Researchs Natural Language Processing group.
Margaret Mitchell helps develop computers that can communicate about what they see and understand. She tells a cautionary tale about the gaps, blind spots and biases we subconsciously encode into AI and asks us to consider what the technology we create today will mean for tomorrow.
Kriti Sharma is the Founder of AI for Good, an organization focused on building scalable technology solutions for social good. Sharma was recently named in theForbes 30 Under 30 list for advancements in AI. She was appointed a United Nations Young Leader in 2018 and is an advisor to both the United Nations Technology Innovation Labs and to the UK Governments Centre for Data Ethics and Innovation.
AI algorithms make important decisions about you all the time like how much you should pay for car insurance or whether or not you get that job interview. But what happens when these machines are built with human bias coded into their systems? Technologist Kriti Sharma explores how the lack of diversity in tech is creeping into our AI, offering three ways we can start making more ethical algorithms.
Matt Beane does field research on work involving robots to help us understand the implications of intelligent machines for the broader world of work. Beane is an Assistant Professor in the Technology Management Program at the University of California, Santa Barbara and a Research Affiliate with MITs Institute for the Digital Economy. He received his PhD from the MIT Sloan School of Management.
The path to skill around the globe has been the same for thousands of years: train under an expert and take on small, easy tasks before progressing to riskier, harder ones. But right now, were handling AI in a way that blocks that path and sacrificing learning in our quest for productivity, says organizational ethnographer Matt Beane. Beane shares a vision that flips the current story into one of distributed, machine-enhanced mentorship that takes full advantage of AIs amazing capabilities while enhancing our skills at the same time.
Leila Pirhaji is the founder ofReviveMed, an AI platform that can quickly and inexpensively characterize large numbers of metabolites from the blood, urine and tissues of patients. This allows for the detection of molecular mechanisms that lead to disease and the discovery of drugs that target these disease mechanisms.
Biotech entrepreneur and TED Fellow Leila Pirhaji shares her plan to build an AI-based network to characterize metabolite patterns, better understand how disease develops and discover more effective treatments.
Janelle Shane is the owner of AIweirdness.com. Her book, You Look Like a Thing and I Love Youuses cartoons and humorous pop-culture experiments to look inside the minds of the algorithms that run our world, making artificial intelligence and machine learning both accessible and entertaining.
The danger of artificial intelligence isnt that its going to rebel against us, but that its going to do exactly what we ask it to do, says AI researcher Janelle Shane. Sharing the weird, sometimes alarming antics of AI algorithms as they try to solve human problems like creating new ice cream flavors or recognizing cars on the road Shane shows why AI doesnt yet measure up to real brains.
Sylvain Duranton is the global leader of BCG GAMMA, a unit dedicated to applying data science and advanced analytics to business. He manages a team of more than 800 data scientists and has implemented more than 50 custom AI and analytics solutions for companies across the globe.
In this talk, business technologist Sylvain Duranton advocates for a Human plus AI approach using AI systems alongside humans, not instead of them and shares the specific formula companies can adopt to successfully employ AI while keeping humans in the loop.
For more AI and machine learning TED talks, browse TEDs complete topic collection.
Timothy is Solutions Review's Senior Editor. He is a recognized thought leader and influencer in enterprise BI and data analytics. Timothy has been named a top global business journalist by Richtopia. Scoop? First initial, last name at solutionsreview dot com.
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The 17 Best AI and Machine Learning TED Talks for Practitioners - Solutions Review
- Using machine learning to see how living brains learn - The University of Utah - September 8th, 2026 [September 8th, 2026]
- Applying causal machine learning to assess and improve cleantech policy design - Nature - September 8th, 2026 [September 8th, 2026]
- Frontier Tech Leaders Programme Celebrates First Machine Learning Bootcamp Graduation and AI for Sustainable Tourism Hackathon in Angola - United... - September 8th, 2026 [September 8th, 2026]
- From the Knowledge to machine learning: Wayve takes AI driving to London - IOT Insider - September 8th, 2026 [September 8th, 2026]
- Algorithm optimizes machine learning techniques that use linear, tunable resistor networks - AIP.ORG - September 2nd, 2026 [September 2nd, 2026]
- Math Modeling Seminar: Applications of Topological Data Analysis and Machine Learning Models in Predictive Biology and Drug Discovery | Events | RIT -... - September 2nd, 2026 [September 2nd, 2026]
- UC Berkeley Announces New Professional Graduate Degree in AI and Machine Learning - University of California, Berkeley - August 25th, 2026 [August 25th, 2026]
- DedeepyaYarraand the rise of Trustworthy AI: Where Machine Learning meets cybersecurity - India.com - August 25th, 2026 [August 25th, 2026]
- Machine learning smooths the road from idea to real-world climate impact - EurekAlert! - August 18th, 2026 [August 18th, 2026]
- Chris Latham Interviews Henry Zelikovsky, Founder & CEO of Softlab360: Successful Applications of AI/Machine Learning in Wealth Management -... - August 18th, 2026 [August 18th, 2026]
- Integrated data and machine learning transform lung cancer diagnosis and treatment - Bioengineer.org - August 18th, 2026 [August 18th, 2026]
- Machine learning accelerates climate solutions from ideas to real-world impact - Bioengineer.org - August 18th, 2026 [August 18th, 2026]
- Identification of weight loss predictors using machine learning approaches in adolescents with obesity - Nature - August 16th, 2026 [August 16th, 2026]
- Quantitative Hedge Fund Strategies: The Machine Learning Revolution of 2026 - rebellionresearch.com - August 16th, 2026 [August 16th, 2026]
- Healthcare Machine Learning Hits Production Scale as Governance Falls Behind, Black Book's Fourth Annual Report Finds - bhpioneer.com - August 16th, 2026 [August 16th, 2026]
- Machine Learning Identifies Predictors of Weight Loss in Adolescents With Obesity - Bioengineer.org - August 16th, 2026 [August 16th, 2026]
- How AI is changing hurricane forecasting as scientists track storms with machine learning - Gulf Coast News and Weather - August 12th, 2026 [August 12th, 2026]
- Scalable prediction of suicidal risk in university students: a three steps machine learning approach in university settings - Nature - August 12th, 2026 [August 12th, 2026]
- Identification of critical brain regions for young adults with obesity and their relationships with impulsivity using machine learning based on... - August 12th, 2026 [August 12th, 2026]
- UNIVERSITY OF ALBERTA Drones and machine learning team up to map forest soil health - Education News Canada - August 12th, 2026 [August 12th, 2026]
- Meet Millie Pradawong, the 14-year-old Virginia student using machine learning and CRISPR to make microal - The Times of India - August 7th, 2026 [August 7th, 2026]
- UWs Machine Learning for High School Teachers Workshop Enriches Classrooms - University of Wyoming - August 7th, 2026 [August 7th, 2026]
- Assessment and pathways of the energy production revolution in the Yellow River Basin, China towards carbon peaking: a machine learning approach -... - August 7th, 2026 [August 7th, 2026]
- TN Agri Budget: Govt bets on AI, Machine Learning to deliver real-time assistance to farmers - ThePrint - August 7th, 2026 [August 7th, 2026]
- Machine Learning Identifies Cognitive Impairment From Patient Speech - Psychiatry Advisor - August 5th, 2026 [August 5th, 2026]
- The Evolution of AI and Machine Learning: Powering the Future of Energy - JPT Homepage - August 5th, 2026 [August 5th, 2026]
- How Machine Learning Is Reshaping Extended Detection and Response - Technology Org - August 5th, 2026 [August 5th, 2026]
- AI and machine learning roles boost Indias white-collar recruitment - Staffing Industry Analysts - August 5th, 2026 [August 5th, 2026]
- Machine learning narrows search for additional particles in the Higgs boson family - Phys.org - July 24th, 2026 [July 24th, 2026]
- F1 in Belgium: Machine learning algorithms are ruining the sport - Ars Technica - July 24th, 2026 [July 24th, 2026]
- Researchers use AI and machine learning to design two new promising blue TADF OLED emitters - OLED-Info - July 24th, 2026 [July 24th, 2026]
- Machine learning professor breaks down OpenAI model's hack of another AI company - CBS News - July 24th, 2026 [July 24th, 2026]
- Barlast Tests Folk Tradition and Machine Learning On Imitation Game - World Music Central - July 24th, 2026 [July 24th, 2026]
- Predicting Outcomes with Machine Learning | Mathematical Sciences | College of Arts & Sciences - University of Delaware - July 6th, 2026 [July 6th, 2026]
- Machine Learning in Public Health: A 3-day Intensive Workshop - American Public Health Association - July 6th, 2026 [July 6th, 2026]
- Tunable band-stop photodetection with machine learning-enabled broadband spectral adaptation - Nature - July 3rd, 2026 [July 3rd, 2026]
- Basic machine learning with lessR : Easy, simple, and free - Open Access Government - July 3rd, 2026 [July 3rd, 2026]
- QuadSci Named Machine Learning Company of the Year - MarTech Cube - July 3rd, 2026 [July 3rd, 2026]
- From Conventional to Intelligent Triage: A Systematic Review of Artificial Intelligence and Machine Learning Applications in Emergency Departments -... - July 3rd, 2026 [July 3rd, 2026]
- On Robustness and Chain-of-Thought Consistency of RL-Finetuned VLMs - Apple Machine Learning Research - July 3rd, 2026 [July 3rd, 2026]
- Improving Wildfire Prediction with Machine Learning and Firebreaks - University of Reading - July 3rd, 2026 [July 3rd, 2026]
- A 3X Leader for the Agentic Era: DataRobot Named a Leader Again in the Gartner Magic Quadrant for Data Science and Machine Learning Platforms -... - June 24th, 2026 [June 24th, 2026]
- A 3X Leader for the Agentic Era: DataRobot Named a Leader Again in the Gartner Magic Quadrant for Data Science and Machine Learning Platforms - Yahoo... - June 24th, 2026 [June 24th, 2026]
- Undergrads gain hands-on machine learning experience in summer program - The Pennsylvania State University - June 24th, 2026 [June 24th, 2026]
- Python and Machine Learning: Why the Two Skills Are Increasingly Inseparable - BNO News - June 24th, 2026 [June 24th, 2026]
- Domino Data Lab Named a Visionary for the Third Consecutive Year in the 2026 Gartner Magic Quadrant for AI Platforms for Data Science and Machine... - June 24th, 2026 [June 24th, 2026]
- Machine Learning Boosts Smart Thermochromic Window Efficiency - Bioengineer.org - June 24th, 2026 [June 24th, 2026]
- A.I. VS HUMAN ROAST BATTLE to Pit Machine Learning Against Live Rapper in SF - BroadwayWorld - June 16th, 2026 [June 16th, 2026]
- Machine learning gives the U.S. a 1% chance of winning the World Cup final in its own backyard - Fortune - June 16th, 2026 [June 16th, 2026]
- Machine Learning Reveals Genes That Help Yeasts Resist Stress - Department of Energy (.gov) - June 16th, 2026 [June 16th, 2026]
- Machine Learning Reveals AED Impact on LGG Prognosis - Bioengineer.org - June 16th, 2026 [June 16th, 2026]
- Introducing the Third Generation of Apples Foundation Models - Apple Machine Learning Research - June 12th, 2026 [June 12th, 2026]
- Machine learning model predicts T2D risk up to 10 years before onset - Managed Healthcare Executive - June 12th, 2026 [June 12th, 2026]
- GPU as a Service Market to Reach USD 14.4 Billion by 2033 at 16.0% CAGR, Fueled by Generative AI, Machine Learning, and Cloud Infrastructure Expansion... - June 12th, 2026 [June 12th, 2026]
- Machine learning-guided design of mechanoadaptive bioglues for multitissue trauma and first-aid applications - Nature - June 12th, 2026 [June 12th, 2026]
- OUCRU scientists are using machine learning to forecast the next dengue outbreak - tropicalmedicine.ox.ac.uk - June 12th, 2026 [June 12th, 2026]
- IIT Roorkee invites applications for 11th Batch of Data Science, Machine Learning & Generative AI Programme - Elets Technomedia - June 12th, 2026 [June 12th, 2026]
- RAG Is Not Machine Learning, and the ML Toolkit Solves the Wrong Problem - Towards Data Science - June 3rd, 2026 [June 3rd, 2026]
- A reality check on the AI jobs hysteria - Machine Learning Week US - June 3rd, 2026 [June 3rd, 2026]
- STMicroelectronics Releases Vibration Sensor With Integrated Machine Learning for Industrial Monitoring - geneonline.com - June 3rd, 2026 [June 3rd, 2026]
- NAVER LABS Europe is offering a 2026 Research Internship in Large Language Models, focusing on AI Alignment, Controlled Generation, and Machine... - May 29th, 2026 [May 29th, 2026]
- Q&A: A Machine-Learning-Based Tool to Enhance Clinical Care of Patients With Multiple Sclerosis - Physician's Weekly - May 29th, 2026 [May 29th, 2026]
- Evaluating the Diagnostic Performance of AI and Machine Learning in Sickle Cell Disease Detection: A Systematic Review - Cureus - May 29th, 2026 [May 29th, 2026]
- HTC-19 Update: Artificial Intelligence and Machine Learning - Chromatography Online - May 29th, 2026 [May 29th, 2026]
- Multimodal phenotypic classification of generalized anxiety and panic using structural MRI data and psychosocial factors: machine learning results... - May 29th, 2026 [May 29th, 2026]
- Machine Learning Personalizes Depression Treatment with the Help of Wearable Technology - UC San Diego Today - May 27th, 2026 [May 27th, 2026]
- How Machine Learning Makes Complex Knowledge Useable in Real-World Conditions - Supply & Demand Chain Executive - May 25th, 2026 [May 25th, 2026]
- How Airbnbs machine-learning tools aim to prevent Memorial Day weekend parties in Las Vegas - FOX5 Vegas - May 25th, 2026 [May 25th, 2026]
- Artificial Intelligence and Machine Learning in Hospital Quality Management, Patient Safety, and Accreditation Readiness: A Systematic Review and... - May 25th, 2026 [May 25th, 2026]
- Machine learning accelerates analysis of fusion materials - Technology Org - May 25th, 2026 [May 25th, 2026]
- Dr. Kaveh Heidary Presents Innovations in AI, Machine Learning and Multispectral Imaging - aamu.edu - May 25th, 2026 [May 25th, 2026]
- Comparison of Prognostic Performance Between a Machine Learning Model and Manually Measured Grey-White-Matter Ratio on Early Brain Computed Tomography... - May 25th, 2026 [May 25th, 2026]
- Machine learning proves that graphene is hydrophobic - Phys.org - May 13th, 2026 [May 13th, 2026]
- Machine learning algorithm predicts AMD stock price on May 31, 2026 - Finbold - May 13th, 2026 [May 13th, 2026]
- Genetic association and machine learning improve the prediction of type 1 diabetes risk - Nature - May 1st, 2026 [May 1st, 2026]
- What Can We Expect From Machine Learning Predictions in Daily Clinical Neurology? - Neurology Live - May 1st, 2026 [May 1st, 2026]
- How Spam Filters Paved the Way for Adversarial Machine Learning - 150sec - May 1st, 2026 [May 1st, 2026]
- Real-Time Estimation of Numerical Rating Scale (NRS) Scores Using Machine Learning-Based Facial Expression Analysis: A Proof-of-Concept Study - Cureus - May 1st, 2026 [May 1st, 2026]
- Heriot-Watt researcher warns gen AI in machine learning carries serious and underestimated risks - EdTech Innovation Hub - May 1st, 2026 [May 1st, 2026]
- HS-SPME/GCMS and Machine Learning Enable Volatile Fingerprinting and Classification of Commercial Vinegars - Chromatography Online - April 12th, 2026 [April 12th, 2026]