Folgen
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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
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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.
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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 Lab
President, INFORMS Polish Section
- Co-editor, Central European Journal of Economic Modelling and Econometrics
- Editorial board member, Multiple Criteria Decision Making journal
Independent 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.
# Timestamps
00:00 Intro
01:08 Learning Programming, Communist Poland & First Computer
07:07 Polish Education System & STEM teaching
11:35 Julia’s Conceptualization & Expectations
28:05 PetaFLOP club language, Data Type-based Operations & Julia’s Performance
38:11 Project Celeste, 800M astronomical objects detection, HPC in Julia
59:50 Julia in Academia vs Industry - Speed & Ease of Learning
01:21:21 Customer-facing Apps, Streamline vs Genie
01:38:56 Julia and LLMs, Falcon 40B, Training & Inferencing in Julia
01:45:05 Relearning Julia, How to get Started
01:51:09 From in-memory to cluster processing and MIT partnership
01:59:09 Family, Productivity, Community & Work - Juggling different Balls -
Fehlende Folgen?
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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. transcript00:00 Intro02:15 Zenlytic, Dashboards and Self-serve Tools04:42 PowerBI, Tableau & Why Another Tool06:29 Semantic Layer on LLMs and Self-Serve Analytics13:00 Replacing BI Analysts, Yann Lecaun & LLM Hallucination15:19 Zoe, Zenlytic AI Assistant & Use Cases23:24 Chat-based KPI Dashboard Making26:312 Meeting at Harvard & Friendship outside Harvard30:00 Role of Ivy League Network in securing VC Funding34:50 Ingredients for landing VC Funding 37:32 Webapps vs Mobile Apps & Slack Integration43:20 Cloud vs On-Prem, Security vs Flexibility47:03 Snowflake vs Databricks51:12 Cost per Acquisition & Burn Rate for Start Ups57:01 No-code vs Code, Bubble for Web Design01:01:31 AI doomerism and Future of Work01:08:22 Grad School Project on Telescopes Monitoring Asteroid01:11:00 Horse betting and Gambling Algorithms01:19:30 AI race between US & China and its Impacts01:34:50 EU AI Act, Regulation vs Innovation, Prevention vs Experiment01:39:10 Generative AI and Societal Challenges01:45:14 Start-Up Hiring and Quality of University Grads and Education01:57:00 Future of Zenlytic & Upcoming FeaturesGuest links:Ryan Janssen: https://www.linkedin.com/in/janssenryan/Paul Blankley: https://www.linkedin.com/in/paulblank...Zenlytic: https://www.zenlytic.com/
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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/
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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.
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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:
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Google: https://bit.ly/3s5vDwc
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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This week I'll sit down with Ganes Kesari, Chief Decision Scientist at Gramener, the company behind Gramex and an innovative rising star. Ganes is a contributor in leading magazines such as Forbes, TechCrunch, Entrepreneur, and The Enterprisers Project. He won the 2020 CSuite Award for best blog by a business leader. He has taught at Princeton University and Indian Business School and has been invited to speak at TED, O'Reilly Strata, Microsoft, and Intel events.
Timestamps
00:00 intro
03:04 Gaining Business Value from AI Initiative, Establishing Baselines
08:41 Human vs AI performance baseline, Long Term Benefits of AI
10:30 Netflix’s Recommendation Engine Competition, Failed ROI and Model Accuracy
15:40 GCP losses, Data and Model Drifts, Bulls Eye in a Moving Target
19:40 Data Maturity Assessment Tool, 5 Stage Roadmap
23:20 Logging in Personal Journal, 4 years, 120,000 data points.
25:40 From Siloed Modules to End to End Flow, Gramex Unified Architecture
29:30 Gramener Game Plan, Services vs Platform
34:28 Using ModelHandler to Furnish Realtime Business Visualizations
36:51 WorldBank Data Visualisation of Technology and Entrepreneurship Report, Data Story Component
42:33 Data Journalism at Guardian, Character and Plot Visualisation of Hindu Epic Saga Mahabharata, Shakespeare’s Sonnets, Hans Rosling and GapMinder
47:18 Airtel Contract Deals
49:51 IITs, IIMs, Geeks and Humor
54:22 Education in India, SAT scores and Path Ahead
58:50 Industry-Academic Partnerships and Practical Experience
01:03:00 AI Adoption Pain Points, Cybersecurity, Regulation, Fairness and Explainability
01:07:00 CNA Financial $40M ransom payment and AI Adoption Correlation
01:13:00 Increasing Bain & Company’s Net Promote Score for a Computer Manufacturer
01:20:19 Backing in Himalayas and Monastery in Bhutan
01:25:25 AI in Biodiversity, Rhinoceros, Penguins and Whale Shark as Endangered Species
01:30:01 Google Vertex AI, Alteryx, Knime vs Gramex, Future Strategy
01:35:30 Slidesense, Business Reports and Powerpoint Integration
01:39:26 Explaining DeepLearning to your Daughter, Whitehat Jr Scam
01:45:00 How Technology is changing Social Landscape
01:47:26 Chess Champion, Garry Kasparov and DeepBlue Game
01:51:30 Chess and IQ, Narrow Intelligence and Transferability
01:53:01 Tesla Killing Jaywalker and AI’s Mindless Application
01:55:00 G7 Summit 2020 and AI war between US & China
01:58:33 Smart Twins, Enterprise Mass Production & Gramex
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Serg Masis is the author of best-selling book 'Interpretable Machine Learning with Python' and senior Data Scientist at Sygenta. He has mentored many data scientists around the world.
Timestamps:
00:00 intro
08:30 Old 4.77 MH z Computer, Late 80s and Programming
11:51 Fairness, Accountability and Transparency in Machine Learning, Startup and Harvard
16:33 Fairness vs Preciseness, Bias and Variance Tradeoff, Are Engineers to blame?
21:43 Mask-Detection Problem in Coded-Bias, Biased Samples, Surveillance using CV
32:38 Fixing Biased Datasets, Augmenting Data and Limitations
37:39 Algorithmic Optimisation and Explainability
40:51 Eric Schmidt on Behavioral Prediction, SHAP values, Tree and DeepExplainers
44:50 Challenges of using SHAP and LIME & Big Data
49:37 GPT3, Large Models and ROI on Explainability
01:00:00 TCAS, Collision Risks and Interpretability, Ransom Attacks
01:08:09 Guitar, Bass, and Led Zepplin
01:09:31 Birth Order and IQ, Science vs Folk Wisdom
01:13:30 Reverse Discrimination & Men, Bias in Child Custody, Prison Sentences, and Incarceration
01:23:11 Receidivism to Criminal Behaviour, Ethnic over-representation & Systematic Racism
01:24:44 Human Judges vs AI, Absolute Fairness, Food and Parole
01:30:20 Face Detection in China, Privacy vs Convenience, Feature Engineering and Model Parsimony
01:35:51 Sparsity, Interaction Effects, and Multicollinearity
01:38:23 Four levels of Global and Local Predictive Explainability
01:43:17 Recursive and Sequential Feature Selection
01:47:42 Ensemble, Blended and Stacked Models and Interpretability
01:53:45 In-Processing and Post-Processing Bias Mitigation
01:57:00 Future of Interpretable AI
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Ryne Sherman is Chief Science Officer of Hogans Assessments and Podcast Host of Hogan's Podcast. He was a Professor of Psychological Sciences at Florida Atlantic University before that.
TimeStamps:
00:00 intro
01:42 Personality Portraits, Big Five, Self vs Other Reports
03:53 Trait Identification, Talent Hunting and Reputation-based Prediction
06:07 Adult Variations in Personality, High School Screening and Stability of Profile
08:03 Personality Profile of Trump Supporters and Shard Psychographics
11:40 Core Beliefs and Values as Predictors, Politics and Economic Stimulus
16:01 Psychometric Theory vs Pop Psychology, Response Patterns and Behavioral Predictions
19:11 From Archetypes to Oedipus complex, Reliability and Validity of Hogan Assessments
22:37 Machine Learning, AI and Personality Predictions, Ensemble Models
26:11 Algorithmic Explainability in Assessment Data, Avoiding Blackbox NNs
29:02 Career Development, Executive Recruiting and Personality Plasticity
32:00 Department transfers, Perceived Image and Reputation Awareness
33:51 Childhood, Boy Scout and High School
35:24 Birth Order and Research on Effects on Personality
37:00 Dark Side of Personality, Attention Craving and Workplace Problems
39:52 Explaining Personality Reports and Failed Predictions
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Greg Gage is the co-founder and CEO of Backyard Brains, an organization that develops open-source tools that allow amateurs and students to participate in neural discovery. Greg is an NIH-award-winning neuroscientist with 9 popular TED Talks and dozens of peer-reviewed publications. Greg is a Senior Fellow at TED and the recipient of the White House Champion of Change from Barack Obama award for his commitment to citizen science.
Greg Gage
00:00 intro
02:28 Graduate Work to Brain Interface Company 20:40 Neuralink, EMG and Cyborgs
28:57 Electrode Scarring, Heart Stunts and Neural Engineering
09:40 Neuronal Activation for Behavioral Activations in Monkeys
38:39 Behaviorism, Experimental Psychology and Implications
40:41 Recreation of Memories through Artificial Hippocampus
41:40 Neural Network-based Prosthetics for Limb Amputees
46:50 AI bot Sofia, Facial Nerves in Robots for Emotive Abilities
51:44 Big Five, Personality Traits, Neurophysiology & Predicting Divorce
57:41 Mental Disorders and Wearable Tech
01:01:04 Surveys, Behavioral Data and Neuroscience
01:04:00 Neuroscience in Schools and Expansion to Developing World
01:16:00 Work with LEXUS designing Autonomous Car Experience, Children and Science
01:12:30 Community Work, Silicon Valley and Work Culture 01:20:00 RoboRoach, Flint Michigan and Joy of Learning
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Fabio Pereira is leading the Open Innovation Labs initiative in Latin America at Red Hat. Open Innovation Labs is an intensive, highly focused residency in an environment designed to experiment, immerse and catalyze innovation. He is the author of the book "Digital Nudge: The hidden forces behind the 35,000 decisions we make every day". He had been a Principal Consultant, a Digital Transformation Advisor at ThoughtWorks, a large software consultancy firm for over 10 years.
Fabio Pereira
00:00 intro
00:30 35,000 Decisions , Cognitive Overload and Delegation to Technology
02:30 Pre-Modern Man’s Cognitive Load and Number of Choices
13:52 Antidote to Decision Fatigue, Pomodoro Technique and CrossFit
09:40 Digital Quotient (DQ), Emotional Quotient (EQ) and IQ
14:10 Digital Nudge, Behavioral Sciences and Netflix
20:41 ThoughtWorks, Business Process and Insurance Company Use Case
26:20 UX and RX in Book Writing, Summarization and Legibility
30:20 Nir Eyal, Indestructible and Divided Attention
31:28 Growing up in Brazil, Movies with Subtitles and Hobbies
35:45 IRC, Global Citizenship, Pharmacy and World Travel
44:53 Snapstreak, YouTube Videos, Notifications, Dopamine and Loss Aversion
48:26 John Suler’s 6 Factors of Inhibition, Dual Identity and Twitter vs Linkedin
55:00 Clubhouse, Leaked Recordings and Real Self
56:00 Big Brother Brazil, Reality Shows and Evocation of Real Emotions
57:55 Cyborgs, Biohacking, Neuralink teaches Monkey’s to Play Games and Earthquake in Chile
01:01:00 Induced Emotions through Neurotransmitters and Hunger Aggression
01:05:00 Human Behaviour Biology, Robert Sapolsky and Diet/Memory Relationship
01:07:00 Thinking Fast and Slow and Ivy League baffling Bat and Ball Riddle
01:12:30 Intuition, ESP, Meditation and Eckhardt Tolle
01:18:12 Playing Prank on TEDx Audience, GDPR cookies and Privacy Policy Agreement
01:22:00 Default Biases for Visitors, Checkboxes, Radioboxes and Automatic Suggestions
01:29:52 Algorithmic Bias, Newzealand’s AI-based Passport issuance and Movie Coded-Bias
01:38:15 Intentional Bias, Diversified Training Set and Double-Edged Sword
01:41:40 Moral Decisions for Self-Driving Car, MIT Review article on flawed IMAGENET data
01:49:25 Time Well Spent movement , AR/VR tools for patients in Hospitals and Digital Nudging Tools
01:56:20 From CBT to Self-Assessing Behavioral Patterns
01:57:30 Innovation and Work at RedHat and Infobizity
02:01:00 Steve Wozniak, CS101 and Goals for ‘Digital Nudge’
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Vivek Viswanathan, is Global Head of Research at Rayliant Global Advisors founded by the brilliant, Jason Hsu (managed $145 Billion). Rayliant Quantamental China Equity ETF is a $22 Billion active portfolio employing a systematic approach to harvesting behavioral alpha by exploiting mispricings among Chinese stocks traded in markets around the world. We will be talking about Archegos, GameStop, Chinese Market and Algorithmic Trade, and much more. Don't miss this one!
# Vivek
00:00 intro
00:47 Fundamentals of Stock Investment
05:16 Blind Optimism, FOMO and Psychology of Investment
09:30 Quant Investing, Fundamental and Technical Analysis and Returns
15:40 Sentiment Analysis, Seasonality, Mean Reversal and Trend Signals
20:21 Survivorship Bias, Different Types and Remedy
24:07 Python, Automation, Risk and Retail Investors
31:27 Tech Stocks, Stability and Long-term Returns
34:08 Daniel Kahneman, Psychological Biases and Behavioral Economics
35:22 Tech Fatigue, Eye Strain and Productivity
40:13 Work from Home, Corporate Taxes and Universal Basic Income
45:38 McCarthyism, Socialism and Communism
49:30 Ernest Chang, PhD in Finance to become Quant Investor
52:22 Necessity of a Ph.D, Social Credentialing, Education System and Misplaced Rewards
01:02:40 Coursera IPO, Self-Learning and On-Job Training
01:05:16 Chinese Stock Markets, 2015 Crash, Regulation and Corruption
01:16:57 Why invest in Chinese ETFs, Inefficient Markets and Diversification
01:24:06 Trade Wars between US and China, Alaska Summit, Semiconductor Shortage
01:28:20 Archegos, Theranos, Wirecard, Enron and Stock Market Scams
01:33:20 Nissan Scandal, Arthur Anderson, Big Four and Abetting the Scammers
01:38:30 Rayliant Global Advisors, Jason Hsu and Learning the Trade
01:41:10 Blackbox of Neural Networks, Expected Returns Signals and Explainability
01:44:45 Linear and Non-linear Patterns, Weighted Averages and Decomposition of Reasons
01:47:28 Books, Dhando Investor, Intelligent Investor and Medallion Fund
01:53:18 Work Related Stress, 100 hour week at JP Morgan, Gym and Diet
01:57:10 Protein Intake, Keto and Vegetarianism
02:02:02 Cardio, Glycogen and Oxygen Levels in Blood
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