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Aytekin is the founder and CEO of JotForm, one of the most widely used no-code automation platforms in the world, serving more than 35 million users across education, healthcare, nonprofits, and small businesses. He’s also the author of the Wall Street Journal and Publisher’s Weekly bestselling book Automate Your Busy Work, 00:00 – IntroductionFounder mindset, automation philosophy, and the future of work 00:01 – Why Automate Your Busy Work Was Ahead of Its TimeNo-code, automation thinking before the AI boom 01:09 – Building JotForm Before the AI Hype Cycle20 years of bootstrapping, slow growth, and real product-market fit 02:29 – Forms as the Gateway to AutomationHow education, nonprofits, healthcare, and SMBs really work 03:49 – From Forms to Workflows, Approvals, PDFs, and E-SignaturesDesigning automation for people without developers 04:21 – Solo Founder Reality: Doing HR, Legal, Support, and Product AloneThe hidden cognitive cost of running everything yourself 04:51 – Competing with Google Forms as a Bootstrapped FounderWhy automation and delegation became survival tools 05:58 – Email Automation as Cognitive ReliefHow prioritization systems reduce stress and decision fatigue 07:41 – Applying Automation Internally: Teams, CI/CD, and TestingWhy automation makes teams safer, not riskier 08:10 – Designing Products Around How People Actually WorkFrom tools to systems thinking 09:17 – Writing, Teaching, and Sharing Automation PrinciplesFrom Medium and Forbes to a bestselling book 10:48 – Discovering the AI Revolution After Publishing the BookAutomation philosophy vs AI productivity tools 11:16 – “People Aren’t Overworked — They’re Over-Busy”The psychology of modern work and burnout 12:28 – Embodying Automation Principles Inside the CompanyScaling without chaos 12:48 – Email Prioritization Systems That Actually WorkHow to design inboxes for executives and founders 14:20 – Gmail Filters, Labels, and Decision AutomationSimple systems over complex tools 16:59 – Automation as Stress Reduction, Not SpeedWhy missing important work causes burnout 19:21 – Continuous Deployment and First-Day Code CommitsHow automation builds trust and confidence at scale 21:12 – Why Automation Shouldn’t Be FearedRisk reduction through systems 22:08 – Internal Automation Lessons from JotForm’s Engineering Culture 23:01 – Future of Work: Policy, Strategy, and AIWEF, global work, and structural change 24:32 – Does AI Kill Jobs or Create Better Ones?A real company case study 25:02 – Deploying AI Support Without Laying Off EmployeesHow JotForm handled AI responsibly 27:09 – Human-in-the-Loop AI SystemsWhy oversight matters more than hype 28:19 – Training AI Through Documentation and FeedbackHow resolution rates improved from 25% to 75% 31:01 – Improving AI Through Better Knowledge SystemsDocumentation as infrastructure 32:36 – New Roles Created by AI AdoptionFrom support agents to AI evaluators 33:29 – Multilingual AI Support at Global ScaleWhy AI enables inclusion, not just efficiency 35:09 – Why JotForm Didn’t Get AcquiredIndependence, focus, and long-term thinking 39:29 – Focused Work, Fewer Hours, Higher LeverageRedefining productivity at scale 41:06 – Evolution of JotForm Into a Full Automation PlatformFrom forms to AI agents and integrations 42:09 – AI Agents Demo Discussion and Key TakeawaysReal use cases, real ROI 46:18 – User Research at Massive ScaleLearning from 35 million users 48:03 – Omnichannel AI Agents: Web, Instagram, Gmail, SalesforceTraining once, deploying everywhere 49:35 – The Future of AI Agents as Digital EmployeesOne system, many touchpoints 50:14 – Advice for Young Developers and FoundersHow to compete in the AI era 50:49 – Growth Mindset Through Every Tech RevolutionFrom PCs to the internet to AI 52:10 – Why This Is the Best Time to Be YoungOpportunities created by AI and no-code tools 53:38 – Closing Reflections on Building, Learning, and PurposeA long-term view of work and life

Aleksa Gordic is an ex-software/ML engineer at Microsoft & DeepMind with a broad background across the "whole stack" - maths, electronics, software engineering, algorithms, ML & deep learning (computer vision, natural language processing (NLP), geometric DL, reinforcement learning (RL)...), web, mobile, etc. He is a Top Linkedin Voice in AI for 2023. He has The AI Epiphany YouTube channel, and occasionally shares his projects on GitHub and blogs on Medium. # Timestamps 00:00 Intro 00:45 Dropping Out, Self Learning & Chris Olah 03:20 From Android Developer to ML Engineer 06:25 LeetCode and CodeForces, Coding vs Soft Skills 17:30 Input and Output Mode of Learning 21:41 Yugoslavian Education, Cevap Cici, Hate for Schooling 25:46 Maths Teaching, Lack of Incentivizatiion and PISA Scores around the World 29:29 Inspirational Teachers 31:50 Microsoft HoloLens Summer Camp & Apple Vision 39:26 Microsoft Research, Google Ai, OpenAI & ResNet 41:50 Culture at Microsoft vs Google, Teams & Research Areas 50:00 Proprietary vs Open Source Models, Falcon 40B, MosaicML 01:01:02 Microsoft’s Gameplan, Profits vs User Acquisition 01:10:27 Alan Turing’s Paper, Definition of ‘Machines’ & ‘Think’ 01:14:05 Neuromoprhic Computing, Neuronal Pathways & Future of Hardware 01:16:18 LLM benchmark Saturation & Research Directions 01:20:37 Disinformation, Adobe Firefly and Social Fabric 01:23:33 Lawsuits against Stability AI & OpenAI, Transition from Non-profit to For-Profit 01:28:30 Politicization of AI, Supercomputing & Technological Real Politik 01:31:14 EU AI Regulation, European Innovation Stifling & Repurcussions 01:38:54 US restrictive Visa Regime, H1B Tech Visa problems & Tech Talent Moving out of the US 01:47:00 Life outside Work, Sports & Calisthenics

Season 2 episode 2 of The Minhaaj Podcast this week brings on the child prodigy and genius co-creator of dataframes.jl package for Julia, Dr Bogumił Kamiński. Bogumil learned C language without owning a computer from library books at the age of 16 in a small Polish town. In post-communist Poland he went on to study applied problems in management and economics and his interest lies in computational models for real-life problems.He currently serves as the full professor of economics at the Warsaw School of Economics. He also holds the following positions:- Head of Decision Analysis and Support Unit- Chairman of the Scientific Council for the Discipline of Economics and Finance- Member of the Presidium, Statistics and Econometrics Committee, Polish Academy of Sciences- Adjunct Professor, Toronto Metropolitan University- Data Science Laboratory Researcher, Fields Institute, Computational Methods in Industrial Mathematics Laboratory- Affiliated Faculty, Toronto Metropolitan University, Cybersecurity Research LabPresident, INFORMS Polish Section- Co-editor, Central European Journal of Economic Modelling and Econometrics- Editorial board member, Multiple Criteria Decision Making journalIndependent Supervisory Board Member, AutoPartner S.A.Bogumił Kamiński is an expert in the application of mathematical modeling to solve practical problems in business. In the past, he gathered experience as head of business intelligence and data analytics units in one of the largest Polish consulting and IT solution implementation companies.His field of expertise is the creation of complex decision-support models that use machine learning, optimization, and simulation methods. He is one of the world-leading experts in the Julia language and has numerous contributions to the core of the language and the package ecosystem. He created the famous dataframes.jl package for data science.He also created SilverDecisions software, which is freely available online for modeling decision trees. He has written five books one of which I have reviewed earlier, Julia for Data Science.# Timestamps00:00 Intro01:08 Learning Programming, Communist Poland & First Computer07:07 Polish Education System & STEM teaching11:35 Julia’s Conceptualization & Expectations28:05 PetaFLOP club language, Data Type-based Operations & Julia’s Performance38:11 Project Celeste, 800M astronomical objects detection, HPC in Julia59:50 Julia in Academia vs Industry - Speed & Ease of Learning01:21:21 Customer-facing Apps, Streamline vs Genie01:38:56 Julia and LLMs, Falcon 40B, Training & Inferencing in Julia01:45:05 Relearning Julia, How to get Started01:51:09 From in-memory to cluster processing and MIT partnership01:59:09 Family, Productivity, Community & Work - Juggling different Balls

Ryan is an entrepreneur, data scientist, engineer, and former VC. He is the co-founder and CEO of Zenlytic, a SaaS business that makes a next-generation AI-powered BI tool that uses LLMs and Semantic layers. He previously co-founded Ex Quanta AI Studio, a full-service data consultancy. Ryan started his career as a software developer in his native Canada, before moving to the UK. He then worked with London’s AGC Equity Partners venture capitalist and private equity investor, investing in technology businesses with check sizes of $1-$50m. He has also worked as a consultant with McKinsey & Co. and Ernst & Young. He has master's degrees from Harvard University and Oxford University and a bachelor’s degree from the University of Alberta. Paul is the Co-founder / CTO of Zenlytic, a self-serve BI tool that uses LLMs to provide a simple chat interface to complex business data. He's worked in data for 7+ years and is passionate about all things data and AI. He has a master's from Harvard in Data Science, and while there, he worked with the Minor Planet Center on algorithms to detect if previously untraceable asteroids were going to hit the Earth. Before Harvard, he worked for Roche developing algorithms that run hand-held blood glucose meters. He lives in Denver, CO, where he spends his free time snowboarding, running, and rock climbing. Zenlytic has raised seed round funding from Sequoia Capital and Bain Capital Ventures among others for over $6M. It is revolutionizing how AI is changing the business analytics and visualization powered by plain self-serving chats with its AI assistant Zoe. transcript 00:00 Intro 02:15 Zenlytic, Dashboards and Self-serve Tools 04:42 PowerBI, Tableau & Why Another Tool 06:29 Semantic Layer on LLMs and Self-Serve Analytics 13:00 Replacing BI Analysts, Yann Lecaun & LLM Hallucination 15:19 Zoe, Zenlytic AI Assistant & Use Cases 23:24 Chat-based KPI Dashboard Making 26:312 Meeting at Harvard & Friendship outside Harvard 30:00 Role of Ivy League Network in securing VC Funding 34:50 Ingredients for landing VC Funding 37:32 Webapps vs Mobile Apps & Slack Integration 43:20 Cloud vs On-Prem, Security vs Flexibility 47:03 Snowflake vs Databricks 51:12 Cost per Acquisition & Burn Rate for Start Ups 57:01 No-code vs Code, Bubble for Web Design 01:01:31 AI doomerism and Future of Work 01:08:22 Grad School Project on Telescopes Monitoring Asteroid 01:11:00 Horse betting and Gambling Algorithms 01:19:30 AI race between US & China and its Impacts 01:34:50 EU AI Act, Regulation vs Innovation, Prevention vs Experiment 01:39:10 Generative AI and Societal Challenges 01:45:14 Start-Up Hiring and Quality of University Grads and Education 01:57:00 Future of Zenlytic & Upcoming Features Guest links: Ryan Janssen: https://www.linkedin.com/in/janssenryan/ Paul Blankley: https://www.linkedin.com/in/paulblank... Zenlytic: https://www.zenlytic.com/

Dr. Akhtar received his Ph.D. in Neuroscience and M.S. in Electrical & Computer Engineering from the University of Illinois at Urbana-Champaign in 2016. He received a B.S. in Biology in 2007 and M.S. in Computer Science in 2008 at Loyola University Chicago. His research is on motor control and sensory feedback for upper limb prostheses, and he has collaborations with the Bretl Research Group at Illinois, the Center for Bionic Medicine at the Shirley Ryan AbilityLab, the John Rogers Research Group at Northwestern University, and the Range of Motion Project in Guatemala and Ecuador. In 2021, he was named as one of MIT Technology Review’s top 35 Innovators Under 35 and America’s Top 50 Disruptors in Newsweek. 00:00 Intro 01:42 Multiarticulation of Prosthetic Hand, Finger Movements  03:10 Visiting Pakistan at 7 Years Old, Inspiration for Prosthetics 04:34 $75,000 vs $10,000 Hand, Cost Reduction & Accessibility  06:13 Sourcing Parts from China, Shenzen, Electronic Part Capital of the World  08:45 3D Printing of Hand and Distribution of locally vs imported Parts 11:00 Fixing Repair Problems for Imported Components from China, COVID 19   12:31 USB port, Bluetooth and Spiderman Web  16:56 Android/iOS App, AI&ML & Sensitivity Controller  18:50 From Research to Market, Tactile Feedback 24:15 Invasive Technology, Electrode Scarring & Partnerships 27:11 Cortical Implants & Future of BCIs for Humanity  31:39 Neuroscience Labs as Co-working Spaces 33:20 Guitar, Linkin Park & Mohawk 38:34 OpenAI and Rubic Cube vs Prosthetic Hand  49:16 Work in Ecuador & Inception of the Idea  52:39 3D Printing vs Manual Construction of Prosthetics - Robustness  01:04:31 Multimodel Neuroplasticity & Forced Interchangeability  01:10:06 Neuroscience of Parenting,  Catch 22 01:14:00 Importance of Recognition & Thanking the Crew as a Leader  01:17:00 From $200 in account to Funding round and Medicare Approving Psyonic Hand 01:20:29 Going Global and Exploring New Markets  01:23:31 Infection Mitigation Design  01:29:06 Low Cost Competitors, KalArm by Makers Hive & Game Plan  01:36:33 Shoe Dog by Phil Knight and Power of Grit 01:40:40 Impact, Legacy & Fulfillment Guest Social Media  Aadeel’s Profile: https://www.linkedin.com/in/aadeelakhtar/Perosnal Website: https://www.aadeelakhtar.com/Newsweek Coverage: https://www.newsweek.com/2021/12/24/americas-greatest-disruptors-medical-marvels-1659061.htmlMIT Innovators Coverage: https://www.technologyreview.com/innovator/aadeel-akhtar/ Follow us:  Full Episodes Playlist link: https://bit.ly/3p2oWJA Clips Playlist link: https://bit.ly/3p0Qmzs Apple Podcasts: https://apple.co/3v0YZxV Google: https://bit.ly/3s5vDwc Spotify:  https://spoti.fi/3H6jqf0 Who is Minhaaj?  Minhaaj Rehman is CEO & Chief Data Scientist of Psyda Solutions, an AI-enabled academic and industrial research agency focused on psychographic profiling and value generation through machine learning and deep learning.   CONNECT WITH Minhaaj ✩ Website - https://bit.ly/3LMvwgT ✩ Minhaaj Podcast - https://bit.ly/3H8MK4G ✩ Twitter - https://bit.ly/3v3t1RJ ✩ Facebook - https://bit.ly/3sV0XgE ✩ ResearchGate - https://bit.ly/3I6BvLu ✩ Linkedin - https://bit.ly/3v3FswQ ✩ Buy Me a Coffee (I love it!) - https://bit.ly/3JCMAnO

William H. Inmon (born 1945) is an American computer scientist, recognized by many as the father of the data warehouse. Inmon wrote the first book, held the first conference (with Arnie Barnett), wrote the first column in a magazine and was the first to offer classes in data warehousing. Inmon created the accepted definition of what a data warehouse is - a subject-oriented, nonvolatile, integrated, time-variant collection of data in support of management's decisions. Compared with the approach of the other pioneering architect of data warehousing, Ralph Kimball, Inmon's approach is often characterized as a top-down approach.    00:00 Intro  01:17 From failed Golf Career to a Computing one   03:06 Originality, Patterns & Database Design  04:37 Punch Cards, Magnetic Tapes, Fortran, Cobalt & Bits in IBM 1401s  11:16 First Book with Arnie Barnett, First Conference & Peer Pressure from Vendors   14:26 Winning over Marketing & Sales People vs IT Departments  18:15 Rise & Fall of IBM, Arrogance, Rudeness & Apathetic Company   20:04 Prism Solutions & Early Days of Data Warehousing, Dormant Data & Textual ETL  30:20 Corporate Information Factory, DataMarts & ETL  32:00 Inmon vs Kimball Approach of Data Architecture, Good, Bad & the Worse  36:15 Data Reliability with Data Marts vs Centralised Data Warehouse   39:00 Staging Area in Kimball System vs Vetting the Data    41:00 Metadata, Beethoven & Importance of Metadata,  45:00 Prolific Writing, Family of Writers & Edgar Allan Poe. Hated Writing in College  48:51 Writing Course at Stanford, Fiction & Technical Communication   51:16 Fiction Published Work & Posthumous Publishing  57:03 ELT vs ETL, Data Needs Work. Computing Power and Data Transformation  01:01:31 Big Data, Data Creation Speed & Future of Data Warehousing  01:04:06 Textual ETL, MIT Symposium & Text Data Utilisation Algorithms, Medical Research & COVID 19   01:13:45 Transformers, NLP, Graph Learning & Unfair Criticism & Animosity  01:23:56 Dotcom Bubble, Gartner’s Hype Curve, Theranos and Deception  01:29:45 Venture Capitalists are not Smart People, they are Rich People.   01:35:31 Cloud Computing vs Local DWHs  01:38:06 Databricks vs Snowflake  01:42:03 Not a Book Reader, Carving your Own Path  01:45:56 Travelling to 59 Countries, Experiencing Culture & Interesting Interactions  01:50:00 From California to Colorado, Nature in the Rockies & Life   Follow us:    Full Episodes Playlist link: https://bit.ly/3p2oWJA  Clips Playlist link: https://bit.ly/3p0Qmzs  Apple Podcasts: https://apple.co/3v0YZxV  Google: https://bit.ly/3s5vDwc  Spotify:  https://spoti.fi/3H6jqf0    Who is Minhaaj?   Minhaaj Rehman is CEO & Chief Data Scientist of Psyda Solutions, an AI-enabled academic and industrial research agency focused on psychographic profiling and value generation through machine learning and deep learning.   CONNECT WITH Minhaaj   ✩ Website - https://bit.ly/3LMvwgT  ✩ Minhaaj Podcast - https://bit.ly/3H8MK4G  ✩ Twitter - https://bit.ly/3v3t1RJ  ✩ Facebook - https://bit.ly/3sV0XgE  ✩ ResearchGate - https://bit.ly/3I6BvLu  ✩ Linkedin - https://bit.ly/3v3FswQ  ✩ Buy Me a Coffee (I love it!) - https://bit.ly/3JCMAnO

Lisa Cohen is the Director of Data Science at Twitter and Formerly at Microsoft for 20 years. He holds a bachelor and a master in Applied Mathematics from Harvard and is one of the most influential women in Data Science and AI. 00:00 Intro 02:52 Harvard, Microsoft, and Twitter. From SE to Data Science 03:40  Work Culture at Microsoft, Bigger Picture & Customer First Paradigm 16:40  Working with Bill Gates, Satya Nadella, Leadership Lessons & Marty Kagan 19:30 Zoom Meetings, Productivity & Innovation, ‘Drive’ by Daniel Pink 23:13 Working Styles, Introversion vs Extraversion,  26:43 5-day Week, Focus and Scandinavian Productivity 28:50 The Great Resignation, Data Science Jobs, Networking for People who hate Networking 34:28 Twitter vs Everything else, Metaverse, Space Tourism,  36:50 Non-computing Backgrounds & Transition into Data Science 42:35 Azure’s Race with Amazon in Cloud Computing, OpenAI & First Mover Advantage 46:50 Softball & leadership, Azure Sharks & ‘Hit Refresh’ by Satya Nadella 51:16 Reid Hoffman, Naval Ravikanth & Inspirational Leaders  55:00 Roadblocks in Optimising Data Utilization for Creating Business Value 01:01:00 Data-Centric Models vs ML-Centric Models, Data Augmentation & Use Cases at Microsoft  01:04:04 NVIDIA GTC, Apple M!, Chip Shortage and repercussions for AI 01:08:49 Women in STEM, Mom Support Group & Women leaving STEM faster 01:17:06 Lessons for Leadership being a Parent. 01:20:25 Managing things as a Parent, Work Cycles & Productivity Marathon 01:21:00 Valedictorian Child, Being Elder Sibling, Work Ethics and Parents  01:25:30 Performance Expectation, Sibling Rivalry, Being a Role Model   01:27:19 Mentors and Best Advice  01:30:05 Jack Dorsey, Life, Legacy & Impact on Others  yse083q3AKJv8eUnKDPK

Dhaval Patel is a software & data engineer with more than 17 years of experience. He has been working as a data engineer for a Fintech giant Bloomberg LP (New York) as well as NVidia in the past. He teaches programming, machine learning, data science through YouTube channel CodeBasics which has 428K subscribers worldwide.  00:00 Intro 01:34 Autoimmune disease ‘Ulcerative colitis’, Life & Death Struggle, Back to Life 03:40 Mental Health, Steroids & Immune System  11:00 Planning Videos, Pedagogy & Smart People Problem 17:15 Working at Bloomberg, Bloomberg Trading Terminal & Exceptional Talent in Bloomberg 21:13  Career Tracks on Data Related Spectrum, Pathways for different Careers 25:16  Data Structure and Algorithms, Politics vs Equations, Eternity  28:20  ML vs Deterministic Programming, Time & Space complexity of the ML Models 30:37 Kaggle vs Real Life, Soft Skills for Engineers, Transition from Competitions to Industrial Use-cases  30:02 Litmus Test for Hiring Data Scientists, Continuous Engagement & Adaptability 42:35 Loss of Productivity by Lack of Communication Skills, Education System Deficiencies, How to Win Friends by Dale Carnegie  46:50 Death by PowerPoint, Simplicity & Walk vs Talk 49:51 Negotiating Salary,  Action vs Motivation, Cellphone is a Distraction  57:35 Growing Vegetables, Joy of Gardening, Rural Childhood & GMO Food   01:01:40 Dhando Investor, Motel Business Monopoly by Patels, Software Engineering 01:04:04 Deep learning, C++ Back-propagation Algorithms,  Nvidia Titan RTX GPUs, Amazon Stores Experience 01:08:49 Nvidia Broadcast Noise Cancellation Demonstration, Nvidia Card Filtering, CNNs and Edge Detection  01:16:06 BlackBox Models, ML-centric vs Data-Centric Models,   01:19:25 Natural Language Understanding, Yann Lecaun, Low Accuracy is NLP Models 01:21:18 Github AI Pairing, Data Structures & Future of Programming Languages 01:27:01 ETL pipelines & Distributed Computing Structures  01:30:00 FAST API, Beginner’s Tools, Pytorch vs TensorFlow, Improvements in Tensorflow 2.0 01:35:05 Programmers vs Normal People, Semantics of English vs Programming Languages, pd.read_csv  01:38:03 Nvidia GPU vs Apple M1 GPU, Hope for non-Nvidia Deep-learning, Google Colab 01:41:30 Google Pixel,  Google Tensor Chips & Chip Shortages 01:44:00 Discord Community for Data Science, Mentorship & Abundance Mindset 01:49:00 Struggles, Battles, Hopelessness & Dysphonia

Harrison Canning is a student at the Rochester Institute of Technology in the School of Individualized Studies, Founder of The BCI Guys & Neurotechnology Exploration Team. He makes videos on his Youtube channel The BCI Guys and has designed his own degree centered around brain-computer interface technology (BA in Neurotechnology). The BCI Guys is a media company dedicated to removing the barrier to entry and increasing interest in the field of neurotechnology. It produces engaging, sensational, digestible, and informative content via YouTube, podcasts, and blog posts. Its aim is to lead the conversation around neurotechnology through a science-based approach and conveying what is possible, while also conveying the tremendous potential of brain-computer interface and neuromodulation technologies. 00:00 Intro 01:34 Assault, Concussion and Neurotech 06:01 Coping with Memory Loss, Mathematical Ability & Courage  12:50  Moral Support, SuperMoms & Hope 08:15  Bodysuits, Neuro diseases, Robotics & Boston Dynamics 10:48  Pros and Cons of invasive vs non-invasive Solutions, 1000 Brains Theory, Signal Amplification Issues 13:40  Lucid Dreams, Brain Wave Differences in Human Subjects, RIT Neurotech Research Lab 28:16 Accuracy for Apple Watches & Wearables and Size to Measurement Precision Ration   30:39  SpO2 Levels, Sleep and Stress levels, False Positives 33:32  Delta Waves, Meditation and Focus Research 37:30  Post-trauma Brain Rewiring, Man with Half a Brain, Machine Learning & Intent Prediction through Connectomes  43:10  NeoCortex in Humans vs Other Animal Species, Cons of Late Maturation of Cortex, Human Behavioral Biology 47:00 NeuroPharmacology vs NeuroModulation, Addiction & Jordan Peterson 50:00 Deep Brain Stimulation, Jaak Panksepp, Clinical trials on 2000 People, Controllable Neuro Modulation to Alleviate Pain 53:30  Number of Electrodes, Depression & Anxiety, Neuropathic Pain  56:10 Seizure Detection through AI, Brain Wave Patterns for Seizures, Chip Implants for Preventing them 58:30  Inspiring Mentor & Role Model  01:02:40 Neuroscience Starter Kit, Cost of  Hypondyne Z vs OpenBCI , $499 EEG Cap 01:06:04 Neurotech Education Around the World. Neurotechx Latam, Nigerian Schools  01:10:02 Distributed Neurotech, Remote Patient Monitoring, Technology Exchange  01:14:50 Wernicke & Broca’s Area, Speech Restoration through ML & BrainGate 01:21:25 Motor vs Sensory Homunculus, Sense Substitution & Neuroplasticity  01:26:18 Predicting Human Activity based on Brain Waves, Jennifer Anniston Neuron & Dedicated Neurons  01:30:30 AGI, Recreation of Artificial Brain & Limbic System 01:36:00 Stereotypes as Dropout Regularisation, Racism, Xenophobia, Polarity 01:39:20  Icecream, Greasy Food, Music, Happiness, Sex & Rationality 01:42:00 Future of BCI Guys   01:27:30  Neuroethics, Facebook Whistleblower, Body Image, Culture, Society & Cognitive Enhancements

Matthias Fey is the creator of the Pytorch Geometric library and a postdoctoral researcher in deep learning at TU Dortmund Germany. He is a core contributor to the Open Graph Benchmark dataset initiative in collaboration with Stanford University Professor Jure Leskovec. 00:00 Intro 00:50 Pytorch Geometric Inception   02:57  Graph NNs vs CNNs, Transformers, RNNs 05:00  Implementation of GNNs as an extension of other ANNs  08:15  Image Synthesis from Textual Inputs as GNNs  10:48  Image classification Implementations on augmented Data in GNNs  13:40  Multimodal Data implementation in GNNs  16:25  Computational complexity of GNN Models 18:55  GNNAuto Scale Paper, Big Data Scalability 24:39  Open Graph Benchmark Dataset Initiative with Stanford, Jure Leskovec and Large Networks 30:14 PyG in production, Biology, Chemistry and Fraud Detection  33:10 Solving Cold Start Problem in Recommender Systems using GNNs 38:21 German Football League, Bundesliga & Playing in Best team of Worst League  41:54  Pytorch Geometric in ICLR and NeurIPS and rise in GNN-based papers  43:27 Intrusion Detection, Anomaly Detection, and Social Network Monitoring as GNN implementation  46:10  Raw data conversion to Graph format as Input in PyG 50:00 Boilerplate templates for PyG for Citizen Data Scientists  53:37 GUI for beginners and Get Started Wizards   56:43  AutoML for PyG and timeline for Tensorflow Version   01:02:40 Explainability concerns in PyG and GNNs in general 01:04:40 CSV files in PyG and Structured Data Explainability 01:06:32 Playing Bass, Octoberfest & 99 Red Balloons  01:09:50 Collaboration with Stanford, OGB & Core Team 01:15:25 Leaderboards on Benchmark Datasets at OGB Website, Arvix Dataset  01:17:11 Datasets from outside Stanford, Harvard, Facebook etc   01:19:00  Kaggle vs Self-owned Competition Platform  01:20:00 Deploying Arvix Model for Recommendation of Papers 01:22:40 Future Directions of Research  01:26:00 Collaborations, Jurgen Schmidthuber & Combined Research  01:27:30 Sharing Office with a Dog, 2 Rabbits and How to train Cats

Ankit is an experienced AI Researcher/Machine Learning Engineer who is passionate about using AI to build scalable machine learning products. In his 10 years of AI career, he has researched and deployed several state-of-the-art machine learning models which have impacted 100s of millions of users.    Currently, He works as a senior research scientist at Facebook where he works on a variety of machine learning problems across different verticals. Previously, he was a  researcher at Uber AI  where he worked on application of deep learning methods to different problems ranging from food delivery, fraud detection to self-driving cars.   He has been a featured speaker in many of the top AI conferences and universities like UC Berkeley, IIT Bombay and has published papers in several top conferences like Neurips, ICLR. Additionally, he has co-authored a book on machine learning titled TensorFlow Machine Learning Projects.  He has undergraduate and graduate degrees from IIT Bombay (India) and UC Berkeley respectively. Outside of work, he enjoys running and has run several marathons. 00:00 Intro 00:17  IIT vs FAANG companies, Competition Anxiety 05:40  Work Load between India and US, Educational Culture   07:50. Uber Eats, Food Recommendation Systems and Graph Networks  11:00 Accuracy Matrices for Recommendation Systems   12:42 Weather as a predictor of Food Orders and Pizza Fad 15:48 Raquel Urtusun and Zoubin Gharamani, Autonomous Driving and Google Brain 17:30 Graph Learning in Computer Vision & Beating the Benchmarks 19:15 Latent Space Representations and Fraud Detection 21:30 Multimodal Data & Prediction Accuracy  23:20 Multimodal Graph Recommendation at Uber Eats 23:50 Post-Order Data Analysis for Uber Eats 27:30  Plugging out of Matrix and Marathon Running 31:44  Finding Collusion between Riders and Drivers with Graph Learning  35:40  Reward Sensitivity Analysis for Drivers in Uber through LSTM Networks  42:00 PyG 2.0, Jure Leskovec, and DeepGraph, Tensorflow Support   46:46 Pytorch vs Tensorflow, Scalability and ease of use. 52:10 Work at Facebook, End to End Experiments 55:19 Optimisation of Cross-functional Solutions for Multiple Teams   57:30  Content Understanding teams and Behaviour Prediction 59:50 Cold Start Problem and Representation Mapping  01:03:30 NeurIPS paper on Meta-Learning and Global Few-Shot Model 01:07:00 Experimentation Ambience at Facebook, Privacy and Data Mine  01:09:03 Cons of working at FAANG  01:10:20 High School Math Teacher as Inspiration and Mentoring Others  01:18:25 TensorFlow Book and Upcoming Blog 01:16:40 Working at Oil Rig in the Ocean Straight Out of College  01:20:08 Promises of AI and Benefits to Society at Large 01:25:50 Facebook accused of Polarisation, Manipulation and Racism  01:28:10 Revenue Models - Product vs Advertising 01:31:15 Metaverse and Long-term Goals  01:33:10 Facebook Ray-Ban Stories and Market for Smart Glasses 01:36:40 Possibility of Facebook OS for Facebook Hardware 01:38:00 LibraCoin & Moving Fast - Breaking Things at Facebook  01:39:09 Orkut vs Facebook - A case study on Superior Tech Stack 01:42:00 Careers in Data Science & How to Get into It 01:45:00 Irrelevance of College Degrees and Prestigious Universities as Pre-requisites 01:49:50 Decreasing Attention Span & Lack of Curiosity  01:54:40 Arranged Marriages & Shifting Relationship Trends

Francis Corrigan is Director of Decision Intelligence at Target Corporation. Embedded within the Global Supply Chain, Decision Intelligence combines data science with model thinking to help decision-makers solve problems. 00:00 Intro  01:21  Data Science applications in Logistics and Supply Chain, Cost and Performance trade-off  03:21  Amazon vs Target fulfillment Model, Owning vs Coordinating with Last Mile companies e.g. FedEx  08:36 Suez Canal Container Blockage, Fallback plan at Target  10:37 Predicting products to Stock in Bottle Neck Scenarios  12:42  Air Freight vs Sea Shipments Costs, Ideal vs Real World Deliveries  15:48  Lack of Good Data and Prediction Challenges  18:00  Managing Expectations as Head of Analytics, Importance of Communicating  20:11 Stakeholder Management & Data Science  Newsletter  23:39  Technical and Non-technical Teams Coordination, Speed Reading  26:36  Data Stories and Visualizations  29:47 Reporting Pipelines vs Story Narration  31:37 Times Series, Prophet, Flourish and Hans Rosling  35:28  Economist turned Data Scientist,  Embarrassment as Motivation  38:20  Lack of Practical Skills of Data Science at University  41:18  Employer’s Perspectives on Data Science Talent   45:24  What Causes Data Teams Failure  48:40  COVID 19 and Times Series Corruption,  Anomaly Detection  56:15  Toilet Paper Demand Scenario, Commodity Pricing Alerts  59:50  Automating Alerts for Panic Situation  01:02:10  Pandemic as a Blessing for Digital Business, Exponential Growth Rates and Tuition Fee Reimbursement for Employees  01:06:06 Data as Decision Support System, Strategic Decision Indicators   01:08:08 Capital in 21st Century, Thomas Piketty and Free Markets   01:11:31 Failures of Capitalist Societies on Individual Front and Socialist Aversion of Wealth Generation   01:15:15 UBI, Interventions, and CEO to Lowest Paid Worker Ratio   01:18:25 Career Blunders and Regrets   01:22:12 Psychometric Tests for Intellect Filtering, Behavioral Stability and Creativity Trade-off   01:24:08 Target’s Epic Failure in Canada, What Data Science could have Prevented   01:25:08 Gameplan to Compete with Walmart and Amazon    01:28:00 Sarimax, Armiax and Volatility Management, Planning vs Forecasting  01:31:33 Deep NNs or Lack thereof, Explainability and Monte Carlo as Alternative  01:34:00 Model Parsimony in Times Series, Baseline Models in Excel   01:37:50 R vs Python, Specific Use Cases   01:40:25 Delegating and Element of Trust   01:43:20 Time and Space Complexity of Models, Netflix and Deployments at Target   01:46:00 Political Impacts on Shipments, Narratives and Hypothesis Testing  01:48:00 Nate Silver, Nassem Talib, and Early Inspirations  01:52:05 Work-life Balance

Walid S. Saba is the Founder and Principal AI Scientist at ONTOLOGIK.AI where he works on the development of Conversational AI. Prior to this, he was a PrincipalAI Scientist at Astound.ai and Co-Founder and the CTO of Klangoo. He also held various positions at such places as the American Institutes for Research, AT&TBell Labs, Metlife, IBM and Cognos, and has spent 7 years in academia where he taught computer science at the New Jersey Institute of Technology, theUniversity of Windsor, and the American University of Beirut (AUB). Dr. Saba is frequently an invited speaker at various organizations and is also frequently invited to various panels and podcasts that discuss issues related to AI and Natural Language Processing. He has published over 40 technical articles, including an award-winning paper that was presented at theGerman Artificial Intelligence Conference in 2008. Walid holds a BSc and an MSc in Computer Science as well as a Ph.D. in Computer Science (AI/NLP) which he obtained from Carleton University in 1999. 00:00 intro 01:00 Language as a mental construct, PAC,  Subtext in Sentences 06:28 OpenAI’s Codex Platform, Below Human Baseline Performance of NLP 18:00 Comprehension vs Generation,  Search vs Context 19:20 Sophia the Robot, Shallow ethics in AI and Commercialisation of Academia 27:40 Bad Research Papers, Facebook runaway train & AI Godfathers Cult. 32:30 AI leaders and Profiteering, Unethical Behaviour of Influencers. 37:50 Non-Verbal Component of Natural Language Understanding, Prosody and Accuracy Boost 41:33 Ontologik’s NLU Engine, Adjective Ordering Restriction Mystery  43:58 Ontological Structure and Chomsky’s Universal Grammar, Discovery vs Creation 45:31 Entity Extraction and How Ontologik’s Engine tackles this Problem 47:50 Language Agnostic Learning, Foreign Language Learning, and Pedagogy of Linguistics 54:00 First Language, Blank State and Missing Sounds in Some Languages 55:20 Real-time Language Translation Engines, AR/VR Aids and Commercial Utility 01:01:00 Sentiment Analysis, Language Policing & Censorship  01:04:00 Ontological Structures, Gender Bias and Situational Paradox 01:09:00 3 Foods for Rest of the Life & Fad Food Indulgence 01:11:00 Inspiration for Getting into the Field, Career Ideals & Cultural Influence 01:15:30 Epistemology, IQ and The Bell Curve  01:17:00 Einstein’s IQ, Haircut, Social Skills, and Success Rubric 01:22:00 Attracting Brilliant Talent Around the World, Ivy League PhDs & Standardised Testing 01:28:40 Unsupervised Learning, Accuracy & Comprehensibility in NLU 01:30:20 BF Skinner, Pavlovian Dogs, Skinner has been Skinned. 01:37:50 Human Behavioral Biology, Endocrinal System similarities with Humans yet they don’t learn Languages. 01:45:30 Language as an expression of Genetic differences, Big Five & Phenotype. 01:49:40 IBM Watson Personality Insights, Text-based personality Inferences. 01:55:30 Long Short Term Memory Issue in Ontologik’s Engine, Computational Complexity, Timeline for Release

Richard Turrin is an award-winning, dynamic Fintech expert with over 20 years of experience in leveraging new technology to drive revenue growth for market-leading companies. He writes, speaks, and consults on innovation and China because he learned about both the hard way. He headed four labs in banks responsible for financial product innovation and headed fintech operations in China. His best-selling books 'Cashless' and 'Innovation Excellence Lab' are some of the most recommended books on the topic. He has worked for IBM in senior roles and has been a professor at Hult International Business School.  00:00 intro 00:38 Financial Crisis of 90s and Arrival in Shangai 03:32 China, From Copycat to Innovator, WeChat and Mark Zuckerberg 08:42 Twelfth Five-Year Plan, Regulation of IT and China’s Gorbachev of Fintech 15:09 Crocodile in the Yangtze, Chinese’s Public-Private Partnership and Liberalisation 24:19 China’s Great Firewall, Invasion of Privacy and Uhygar Plight, Freedom as an Average Consumer 32:24 Central Bank Digital Currency, Blockchain and Version 2.0 42:00  Architecture of CDBC. Centralised, Decentralised or Distributed. Public or Private BlockChain 54:00  Challenges of International Adoption of China’s CDBC , US’s Exclusionary Policy and China’s Partnerships in Africa and Middle East  01:11:50 Losers in Chinese CDBC War, US and Allies, PayPal, Square, Stripe and Alipay 01:29:30 US Foreign Policy, Walk of Shame out of Afghanistan, Fiascos in Iraq and Vietnam and Lost Respect in International Community 01:39:50 China’s Innovation beats US by at least 5 Years, Repercussions of CDBC, Smart Contracts and Private Sector Trade 01:12:21 Inspiration in Life, Love of Books and Loss of Mother

James Gaskin is a professor of Information Systems Management at Brigham Young University. 00:00 intro 07:00 Mismatch between Pedagogical Style and Student Needs  12:11 Behavioral Science and Structural Equation Modelling. 16:40  Cut-off scores in Model Acceptance in SEM 17:30  SEM on Big Data and Computational Intensity 20:14  Model Explanation in Academics vs Industry 21:16  Academic Trash Research Papers getting Published 23:35  Gerry-mandering of Data and Publishing Mafia 26:20  HTMT as Discriminant Validity Criteria and other Accuracy Metrics 28:20  Empirical vs Mathematical Convergence of Models and Compromise 29:51 Life as Gymnast and 31 Moves in Life, Japan, California and Malaysia 35:00 Failing High School and Relationship Stability  37:19 Data Scientist vs Academic Learning - Siloed Knowledge 49:39 Book ‘How to lie with Statistics’, John Perkins, Joseph Stiglitz and Political Manipulation of Data  44:22 Enron, Big Four and Cooking Books  47:26 Hedonist Motivation System, Pavlov’s Reinforcement and SEM 53:40 Futility of Research in Social Sciences and Remedy 55:40  Utrect University Abandons Citations for Hiring and Promotion of Faculty for Open Science 59:40 Work Path towards Ph.D in Australia. Practice vs Theory 01:03:00 Fixing the Academia and Failure. Video Journals for Research 01:07:49 Ratemyprofessor Score and Wrong Incentives for Teacher Rating 01:10:00 University Campus as Political Battlefields, Psychology and Conservatism 01:12:21 Dilemma of Academia vs Industry in Future 01:31:51 Favourite SEM software 01:17:40 Shortcomings of AMOS by IBM  01:19:36 Mediation and Moderation in Structural Models and Explainability 01:23:20 Dropout Regularisation, Second Generation Statistical Tools & Explainability 01:26:00 HC Moneyball and SEM for Understanding Dynamics 01:31:00  Path Analysis and Sales Data Modelling 01:532:41 Mediation and Moderation analysis and Prediction  01:37:40 The Invention Book and Mechanical Engineer 01:40:15  Daughters, Invention Book and Different temperaments 01:53:41 Mediation and Moderation analysis and Prediction