Infinite Curiosity Pod with Prateek Joshi

Joshua Starmer is the founder and CEO of StatQuest. He makes online educational materials to teach data science, machine learning, and statistics. His YouTube channel has 775,000 subscribers. He was previously an Asst Professor at University of North Carolina, Chapel Hill. He has a PhD in biomathematics, bioinformatics, and computational biology. In this episode, we cover a range of topics including:- Teaching ML and statistics - Launching his YouTube channel - Growing his YouTube channel to 775,000 subscribers - Running growth experiments - How to create engaging content - Learning framework for ML practitioners 

Tommy Dang is the cofounder and CEO of Mage, a collaborative AI tool for product developers. They've raised a $6.3M seed round led by Gradient Ventures. Prior to this, he was a machine learning engineer at Airbnb for 5.5 years. He was previously the cofounder of OnMyBlock and has a bachelors degree from UC Berkeley. In this episode, we cover a range of topics including:- Building low-code ML tools for developers- How to incorporate AI into a product- Building machine learning models for Airbnb's Experiences vertical- His key learnings as a second time founder- What he's building at Mage- How they got their first 10 customers for Mage

Chad Sanderson is the Head of Data at Convoy. He is a scout for Sequoia Capital investing in ML and data startups. He has previously been a scout for Cowboy Ventures and Innovation Endeavors. He's been an advisor to Tola Capital and an LP to Essence Venture Capital. He is a prolific builder of products. And has built everything from feature stores, experimentation platforms, streaming platforms, data discovery systems, and workflow development platforms.In this episode, we cover a range of topics including:- Modern data stack- How he identifies great ML startups- Being a scout for Sequoia Capital- Investment themes in ML and data- Data modeling- Data collaboration tools

John Thompson is the Global Head of AI and Rapid Data Lab at CSL Behring. It's a $10B global biopharma company. Second largest of its kind in the world. It manufactures products to treat rare diseases like hemophilia. He's a best selling author of books like Data For All, Building Analytics Teams, and Analytics: How to win with intelligence. In this episode, we talk about:- AI in pharma- Building products for pharma vs bio vs healthcare- Challenges of building products for rare diseases- Plasma-derived therapeutic products- AI-powered drug discovery- State of healthcare in US

Jennifer Prendki is the founder and CEO of Alectio. They're pioneering the DataPrepOps space and building technology to help companies do Machine Learning more efficiently, in particular with less data. She's a keynote speaker and has spoken at most major conferences in the field. She has a PhD in Particle Physics and has built a phenomenal career.In this episode, we talk about:- DataPrepOps- MLOps- Data labeling- Training datasets- Carbon footprint of AI systems- Active learning- Online learning, continual learning, incremental learning

Scott Taylor runs MetaMeta Consulting and is the author of the book Telling Your Data Story. He is one of the most prolific speakers and writers on the topic of data management. He's been on DataIQ 100, Thinkers360 Top 10, and a Dataversity Top 10 Blogger. He was at Nielsen for 14 years and has a degree from UC Berkeley.In this episode, we cover a range of topics including:- Master data management- Data storytelling- Data vs analytics- How to communicate data quality issues- The journey of managing master data

Matt Harrison is a world-renowned expert on Python and Data Science. He has a CS degree from Stanford University. He is a best-selling author on Python and Data subjects. He is the author of books such as Effective Pandas, Illustrated Guide to Learning Python 3, Intermediate Python, Learning the Pandas Library, and Effective PyCharm. They've ALL been best-seller on Amazon. He is an advisor to Ponder, the Enterprise Pandas company. You can check out his online store and his course on Pandas.  In this episode, we cover a range of topics including:- Corporate training and upskilling- The process of training- Similarities and differences between the learning mechanisms for adults vs children- Framework for data practitioners to educate themselves- Biggest gap in skills today- Modes of learning- Measuring the efficiency of training products and services

Ben Taylor is the Chief AI Evangelist at DataRobot. He's a veteran thought leader on AI with over 16 years of experience. He was at Intel and Micron working on photolithography, process control, and yield prediction groups. He joined an AI hedge fund as an expert in high performance computing and AI, where he built models using a cluster of 600 GPUs. He then joined a young HR startup called HireVue, where he built out their data science group, filed 7 patents, and helped to launch their AI insights product using video/audio from candidate interviews. In 2017, Taylor co-founded Zeff.ai to pursue deep learning for image, audio, video, and text for the enterprise.In this episode, we cover a range of topics including:- Automating network design with genetic programming and deep learning- Key learnings as HireVue's first data scientist- Why he doesn't like Tensorflow- Metaheuristics- Key learnings as the cofounder of Zeff.ai- What does it take to go from 0-to-1 when building an ML product 

Srinath Sridhar is the cofounder and CEO of Regie.ai where they're building a content platform for modern revenue teams. He was one of the first 100 engineers of Facebook. He was a member of the founding team at Bloomreach where he built v1 of many of their products. He was the cofounder and CTO of Onera, which recently got acquired by Accel KKR / Toolsgroup. He's also an investor in many startups. In this episode, we cover a range of topics including:- how to build the v1 of a machine learning product- what does it take to scale a product- using generative AI in business- how to talk to customers- how to identify promising ML startups

In this episode, Prateek Joshi talks about:- Images captured by James Webb space telescope- Discovery of rare earth elements in Turkey- Meta's large language model NLLB-200 that can translate 200 languages- Minerva: Google's AI system that can solve quantitative reasoning problems- Google demonstrates quantum advantage for machine learning- MIT and Stanford researchers show how robots can handle deformable material- How GPT-3 can explain a piece of code