Infinite Machine Learning: Artificial Intelligence | Startups | Technology

By Prateek Joshi

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Subscribers: 4
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Episodes: 142

Description

The podcast where Prateek Joshi interviews world-class AI founders, VCs, and practitioners. Each episode dives deep into a specific topic to explore how to build ML products, how to use Data to fuel those products, and how those products achieve the goal of AI. You can subscribe to Prateek's weekly newsletter that explores the intersection of AI and Startups: https://prateekjoshi.substack.com


Episode Date
Unpacking AI Startups: Metrics, Playbooks, and the Future
May 14, 2024
Automated Evaluation of LLMs
May 07, 2024
Investing In AI-first Startups
Apr 30, 2024
AI's Role In Physics, Chemistry, and Beyond
Apr 09, 2024
Generative AI for Coding
Apr 02, 2024
Building Robots That Can Cook
Mar 19, 2024
Discovering New Materials With AI
Mar 11, 2024
Designing Printed Circuit Boards With AI
Mar 04, 2024
Algorithmic Data Curation
Feb 26, 2024
Modifying Speech Accents In Real Time With AI
Feb 19, 2024
Voice AI Agents
Feb 12, 2024
MANG VC "Round Trip" Phenomenon in AI
Feb 05, 2024
AI x Future of Work
Jan 29, 2024
LLM Data Frontiers
Jan 22, 2024
AI in Defense
Jan 16, 2024
Building and Investing in Consumer AI
Jan 08, 2024
Open Source x Health AI
Dec 18, 2023
Biosimulation for Drug Development
Dec 12, 2023
Solver Agent
Dec 11, 2023
Multimodal Video Understanding
Dec 07, 2023
Underwater Robotics
Dec 04, 2023
Sam Lessin on AI investing
Nov 30, 2023
AI as an interface to the world
Nov 27, 2023
Earth Observation with AI
Nov 20, 2023
Biochemistry AI
Nov 16, 2023
Evolution of intelligence, Digital life, AGI | Flo Crivello, founder and CEO of Lindy
Nov 13, 2023
Thoughts on OpenAI DevDay announcements | Vikram Sreekanti, cofounder and CEO of RunLLM
Nov 09, 2023
Artificial Specialized Intelligence, Executive Order on AI, Open Source AI | Douwe Kiela, cofounder and CEO of Contextual AI
Nov 06, 2023
AI compute market, LLM infrastructure, Industrial AI | Ville Tuulos, cofounder and CEO of Outerbounds
Oct 30, 2023
Prateek talks about Nvidia's new AI agent that can train robots
Oct 23, 2023
Prateek talks about Generative AI in Biology
Oct 16, 2023
Prateek talks about LLMs learning to represent space and time
Oct 09, 2023
Prateek talks about the Reversal Curse of LLMs
Oct 02, 2023
Generative AI x Synthetic data | Ali Golshan, cofounder and CEO of Gretel AI
Sep 25, 2023
Programmatic AI data development, Multimodal AI, False dichotomy of fine-tuning vs RAG, Compute-optimal LLMs | Alex Ratner, CEO of Snorkel AI
Sep 18, 2023
Generative AI x Privacy | Riddhiman Das, CEO of TripleBlind
Sep 11, 2023
Prateek talks about AI infrastructure ideas and categories
Sep 07, 2023
AI coprocessor for data, Relational knowledge graphs | Molham Aref, CEO of RelationalAI
Sep 05, 2023
Prateek talks about 8 strategies to speed up ML on different hardware platforms
Aug 31, 2023
Object store for AI workloads | Anand Babu Periasamy, cofounder and CEO of MinIO
Aug 28, 2023
AI assistant for software development | Eran Yahav, cofounder and CTO of Tabnine
Aug 21, 2023
Prateek talks about Data Orchestration
Aug 17, 2023
No-Code Generative AI, Domain specific LLMs, AI experimentation | Karthik Dinakar, cofounder and CTO of Pienso
Aug 14, 2023
Prateek talks about 7 skills that ML builders should develop
Aug 10, 2023
Compute layer for data, Vector search, AI infrastructure | Venkat Venkataramani, cofounder and CEO of Rockset
Aug 07, 2023
Prateek talks about Geometric Deep Learning
Aug 03, 2023
Speeding up Generative AI models | Luis Ceze, cofounder and CEO of OctoML
Jul 31, 2023
Prateek talks about 9 steps to do customer discovery for AI products
Jul 27, 2023
Vector databases x Vertical AI | Andre Zayarni (cofounder/CEO of Qdrant) and Karthik Dinakar (cofounder/CTO of Pienso)
Jul 24, 2023
Prateek talks about Federated Learning
Jul 20, 2023
AI x DevOps, Open source AI, Data infrastructure | Timothy Chen, General Partner at Essence VC
Jul 17, 2023
Prateek talks about 11 things to keep in mind for software engineers to get into AI
Jul 13, 2023
Generative AI stack, Android moment of AI, Data infrastructure | Jon Turow, Partner at Madrona
Jul 10, 2023
AI x Robotics | Sam Baker, investor at Scale Venture Partners
Jun 26, 2023
LLM-infused search, Why LLMs hallucinate, Grounded Generation | Amr Awadallah, cofounder and CEO of Vectara
Jun 19, 2023
Training your own LLM, Domain specific models | Naveen Rao, cofounder and CEO of MosaicML
Jun 12, 2023
Lessons from a $130M acquisition, ML model deployment for data scientists, Discovering product-market fit | Harry Glaser, cofounder and CEO of Modelbit
Jun 05, 2023
LLM Agents, Few-Shot Learning | Matt Welsh, cofounder and CEO of Fixie
May 30, 2023
AutoGPT, LLMs for developers, Context windows | Aditya Naganath, Investor at Kleiner Perkins
May 22, 2023
Elad Gil on Generative AI Opportunities, AI Agents, AI Market Structure, and LLM-infused products
May 15, 2023
Connecting LLMs to your data, In-context learning | Jerry Liu, cofounder and CEO of LlamaIndex
May 08, 2023
ChatGPT Plugins, Generative AI in the enterprise | Matt Turck, Partner at FirstMark Capital
May 01, 2023
Vector databases, Vector search | Bob van Luijt, cofounder and CEO of Weaviate
Apr 24, 2023
Iterative AI in B2B SaaS, Coaching networks, Pricing models | Jake Saper, GP at Emergence Capital
Apr 18, 2023
AI compute landscape | Jessica Leao, Maverick Ventures
Apr 10, 2023
Engineer turned VC | Leo Polovets, cofounder and GP at Susa Ventures
Apr 03, 2023
LLM tech stack, Open source startups, Building products for the government | Brian Raymond, cofounder and CEO of Unstructured
Mar 27, 2023
Synthetic data in AI, Computational irreducibility, Generative Adversarial Networks | Ofir Zuk, cofounder and CEO of Datagen
Mar 20, 2023
Decentralized AI, Blockchain, Incentivized intelligence | Ala Shaabana, cofounder of Bittensor
Mar 13, 2023
Fintech AI for 120 Million People | Vishnu Ram Venkataraman, VP Data Science and Engineering at Credit Karma
Mar 06, 2023
AI Delivery Models, Cost Structure of AI Businesses, AI-infused Applications | Jill Chase, Partner at CapitalG
Feb 27, 2023
Federated Learning, Healthcare AI | Ittai Dayan, cofounder of Rhino Health
Feb 20, 2023
Investing in open source startups | Amanda Robson, Partner at Cowboy Ventures
Feb 13, 2023
AI Market Structure | Pauline Yang, Partner at Altimeter Capital
Feb 06, 2023
State of play in AI research | Sebastian Raschka, Bestselling AI Author and Educator
Jan 30, 2023
Generative AI Index | Max Abram, Investor at Scale Venture Partners
Jan 23, 2023
ML testing landscape, Edge cases, ML testing methods, The role of synthetic data | Svet Penkov, cofounder of Efemarai
Jan 16, 2023
On-device ML, Generative AI | Sujith Ravi, founder of SliceX AI
Jan 09, 2023
Investing in Generative AI, The role of compute, The State of AI report, Biology | Nathan Benaich, founder of Air Street Capital
Dec 19, 2022
Investing in AI startups, Large Language Models, Robotics, Future of Generative AI | Rob Toews, partner at Radical VC
Dec 12, 2022
Human Centered Design In AI | Helen and Dave Edwards, cofounders of Sonder Studio
Dec 05, 2022
Prompt engineering, generative AI | Mihail Eric, founder of Confetti AI and Pametan Data Innovation
Nov 28, 2022
Search engines, the role of ML in enterprise search, 0-1 phase of building products | Debarghya Das, Founding engineer at Glean
Nov 21, 2022
Data observability, creating open source software, being a founder, being an author | Andy Petrella, cofounder of Kensu
Nov 14, 2022
Explainable AI, model monitoring, observability | Krishna Gade, CEO of Fiddler AI
Nov 07, 2022
Conversation intelligence | Greg Tapper, CEO of PatternAI
Oct 31, 2022
AI on the blockchain, decentralized AI research, incentivized computer networks | Ala Shaabana, cofounder of Bittensor
Oct 24, 2022
AI observability, being a founder, measuring the ROI of a product | Alessya Visnjic, CEO of WhyLabs
Oct 20, 2022
Getting into VC, ML infrastructure trends, generative AI on content platforms, product management at startups | Rak Garg
Oct 17, 2022
ML in cybersecurity, founding a startup, 0-1 phase of building ML products | Howie Xu, VP of AI/ML at Zscaler
Oct 13, 2022
Data governance | Peggy Tsai, Chief Data Officer at BigID
Oct 10, 2022
Being the first engineer at a unicorn, founding an AI startup, being a VC | Jay Madheswaran
Oct 06, 2022
AI alignment, Superintelligence, AI safety | Jeremie Harris
Oct 03, 2022
Data product pyramid, data product marketplace, data mesh | Jon Cooke
Sep 29, 2022
Building a collaborative data platform, founding a startup, product design, engaging users, how will data roles evolve in the future | Oliver Hughes
Sep 26, 2022
Data observability, building a data startup, how to do customer discovery | Egor Gryaznov
Sep 22, 2022
Synthetic data, quality profiling, building a data startup | Fabiana Clemente
Sep 19, 2022
Building an open source startup, programming hygiene for ML practitioners, product discipline | Ketan Umare
Sep 15, 2022
Investing in ML startups, building ML products, startup opportunities in ML | Leigh Marie Braswell
Sep 12, 2022
How to build an ML startup from scratch, product design, open source strategy, pricing mechanics | Phil Howes
Sep 08, 2022
Building a global community for women in AI and tech | Sadie St. Lawrence
Sep 01, 2022
Growing from 0 to 775,000 YouTube subscribers by teaching ML and statistics | Joshua Starmer
Aug 29, 2022
Building low-code ML tools, being a second-time founder | Tommy Dang
Aug 22, 2022
Investing in ML and Data startups, Understanding the modern data stack | Chad Sanderson
Aug 15, 2022
AI in pharma, Building products for pharma vs bio vs healthcare | John Thompson
Aug 08, 2022
Active Learning in ML, DataPrepOps, Carbon footprint of AI systems | Jennifer Prendki
Aug 01, 2022
Telling stories WITH data vs ABOUT data | Scott Taylor
Jul 28, 2022
Upskilling, learning, and keeping yourself relevant as a data practitioner | Matt Harrison
Jul 25, 2022
Ben Taylor on metaheuristics, AI teaching AI, genetic programming, impact of generative AI on art, building startups, and what it means to be the first data scientist at a company
Jul 21, 2022
Srinath Sridhar on the 0-to-1 journey of building ML products
Jul 18, 2022
What's new in ML: Space telescope, rare earth elements, universal speech translator, quantitative reasoning, quantum computing, robots handling deformable material, and how AI systems can explain a piece of code.
Jul 14, 2022
Adam Sroka on how energy markets work, where renewable energy fits in, software engineering, data scientists, and using machine learning for climate problems
Jul 11, 2022
Doug Laney on infonomics, data monetization patterns, quantifying data's economic value, collateralizing data, and insuring data.
Jul 06, 2022
What's new in ML: The question of whether AI is sentient, NASA's helicopter on Mars, Yann LeCun's recent proposal on Autonomous Machine Intelligence, Amazon's AI-powered coding assistant, and a reconfigurable AI chip built by MIT engineers.
Jun 30, 2022
Jason Krantz on talent trends in the AI sector, hyperlocal job markets in US, flow of talent across sectors, and the craft of employee retention
Jun 27, 2022
Harpreet Sahota on community building, bottom-up adoption, and developer relations for machine learning products
Jun 20, 2022
Jordan Morrow on the next unlock for the education market, data literacy, and upskilling in machine learning
Jun 20, 2022
Brent Dykes on data storytelling
Jun 16, 2022
Joe Reis on data engineering and architecture
Jun 13, 2022
What's new in ML: Prateek Joshi talks about nuclear fusion, photonic chips, electronic skin, and analyzing satellite imagery with machine learning.
Jun 09, 2022
Vin Vashishta on injecting reality into machine learning products and creating business value with data science
Jun 06, 2022
AMA with Prateek Joshi: Space industry, synthetic data in machine learning, foundation models, AI-infused coding tools
Jun 02, 2022
Serg Masis on interpretable machine learning, process fairness vs statistical fairness, how to measure interpretability, how to interpret neural networks, how to increase the interpretability of a model
May 30, 2022
AMA with Prateek Joshi: Python vs Matlab for machine learning, switching careers to ML, building startups, career paths
May 26, 2022
Zach Keller on recommerce, circular shopping, carbon footprint, economics, how do incentives work in marketplaces, push bucket vs pull bucket, machine learning tools, building data science culture
May 23, 2022
What's new in ML: Prateek Joshi talks about predicting battery lifetimes, fighting wildfires with machine learning, rainfall mapping, avoiding idling at traffic lights, world's largest publicly available machine learning hub, a plant nutrient detected by
May 19, 2022
Demetrios Brinkmann and Vishnu Rachakonda on how they built the world's largest online hub for production Machine Learning practitioners
May 16, 2022
What's new in ML: Prateek Joshi talks about brain computer interface, nanomagnetic computing, counting microplastics using Machine Learning, quantum tunneling memory, wine reviews written by AI, spotting cavity, cancer research
May 12, 2022
Thom Ives on his AI journey, creating educational content, establishing online presence, building a portfolio of machine learning projects, preventing burnout, how growth happens through cycles, storytelling for data scientists.
May 09, 2022
What's new in ML: Prateek Joshi talks about generative AI, enzyme that can break down plastic quickly, nuclear fusion, low-carbon concrete, synthesizing molecules, object detection, few-shot learning.
May 05, 2022
Tushar Gupta on the step-by-step process of getting a tech book published, identifying topics for books, the process of writing, and trends in machine learning books.
May 02, 2022
Richad Nieves-Becker on doing academic vs business work in data science, why sales skills are important for data scientists, how to define tractable problems, the advantage of modular products, rise of MLOps, data versioning, and monetization of machine l
Apr 28, 2022
Matt Kirk on quantitative economics, data science, writing books, being a zen student, surviving cancer, and using the pomodoro technique.
Apr 25, 2022
Che Sharma on experimentation, storytelling, reusable components, creating customer empathy, and data communities.
Apr 21, 2022
Pedram Navid on data activation, how data can get political, reverse ETL, and how data practitioners should forge alliances.
Apr 18, 2022
Amir Feizpour on building online communities, knowledge discovery, doing research, data science culture, and coaching.
Apr 14, 2022
Margaretta Colangelo on how she entered the world of AI, using AI in healthcare, 2021 milestones, cancer research, AI-power drug discovery, the process of writing, and building a career.
Apr 11, 2022
Denis Rothman on how he entered the world of AI, what is metahuman AI, the importance of practice in machine learning, why use transformers, working with customers, interviewing people, and thriving at work.
Apr 07, 2022
Andrew Berry on teaching data science, designing courses, preparing data scientists for jobs, and building a career.
Apr 04, 2022
Emilie Schario on entering the world of data science, looking for jobs, working with customers, managing teams, interviewing people, and building a career.
Mar 31, 2022
Mihail Eric on how he entered the world of machine learning, the role of educational platforms in ML, working with customers, managing teams, interviewing people, and thriving at work.
Mar 24, 2022
Alexey Grigorev on how to enter the world of machine learning, learning data science, running a data community, writing books, doing projects, interviewing people, and how to be a successful professional.
Mar 16, 2022