All Episodes
The Data Exchange with Ben Lorica — 353 episodes
The Hidden Failure Modes of AI Agents
The Data Stack Wasn't Built for AI — Here's What Comes Next
The SaaSpocalypse Is Coming — But Don't Count Out the Incumbents
AI Agents Are Implemented, Not Adopted
Why Your AI Agent Isn't Ready to Ship (And How to Know When It Is)
Why Foundation Models Haven’t Replaced Classical Machine Learning
When "Garbage In, Garbage Out" Gets It Wrong
As Code Generation Speeds Up, Who Tests the Output?
The Gap Between AI Hype and Enterprise Reality
Reading the Tea Leaves: What the World's Top AI Researchers Are Really Working On
From Web Video to Real-World Robots
Why Your AI Committee Might Be Your Biggest AI Problem
Building Mathematical Superintelligence
Your First AI Employee Is Already Clocking In
Are Multi-Agent Systems More Complex Than They Need to Be?
Coding Agents Meet Data Science
World Models Are Here—But It’s Still the GPT-2 Phase
The Hidden Challenges of Running AI at Scale in Production
What No One Tells You About Staying Employable in the AI Era
Adaptation: The Missing Layer Between Apps and Foundation Models
Securing the "YOLO" Era of AI Agents
Building the Open Source Alternative to AWS
Breaking the Memory Wall in the Age of Inference
Is Waymo Actually Profitable? The Real Cost of the Robotaxi Revolution
Beyond Vibe Coding: Building Your Entire Business with AI
The Rise of the Machine Identity: Securing the AI Workforce and AI Agents
Why Traditional Observability Falls Short for AI Agents
Teaching AI How to Forget
The Humanoid Hype Cycle: Separating “Shiny Objects” from Real Utility
The Junior Data Engineer is Now an AI Agent
The Truth About Agents in Production
The best books we read this year 📚
The Developer’s Guide to LLM Security
Is AI a Utility? Defining Usability and Public Trust
How to Build AI Copilots That Teach Rather Than Automate
The AI Revolution Finally Comes to Structured Data
Building the Knowledge Layer Your Agents Need
How Language Models Actually Think
How AI Is Reshaping Jobs, Budgets, and Data Centers
Making Data Engineering Safe for Automation and Agents
Is Your Database Ready for an Army of AI Agents?
Beyond the Dashboard: Collaborative Analytics in Slack
Stop Piloting, Start Shipping: A Playbook for Measurable AI
Databases for Machines, Not People
When AI Agents Need to Talk: Inside the A2A Protocol
The Infrastructure for Production AI
How to Make Your Data Truly AI-Ready
Beyond the Agent Hype
How to Build and Optimize AI Research Agents
Why Digital Work is the Perfect Training Ground for AI Agents
Beyond the Chatbot: What Actually Works in Enterprise AI
Why China's Engineering Culture Gives Them an AI Advantage
Predictability Beats Accuracy in Enterprise AI
2025 AI Governance Survey
The Fenic Approach to Production-Ready Data Processing
When AI Eats the Bottom Rung of the Career Ladder
From NotebookLM to Audio Companions: Why Google’s AI Team Went Startup
The AI-Native Notebook That Thinks Like a Spreadsheet
How Agentic AI is Transforming Wall Street
The Quantum Advantage Is Real—But Where's the Infrastructure?
From Human-Readable to Machine-Usable: The New API Stack
Why Voice Security Is Your Next Big Problem
Unlocking Unstructured Data with LLMs
Building Production-Grade RAG at Scale
Unlocking AI Superpowers in Your Terminal
From Vibe Coding to Autonomous Agents
How a Public-Benefit Startup Plans to Make Open Source the Default for Serious AI
The Highly Uncertain Future of OpenAI’s Dominance
Beyond Guardrails: Defending LLMs Against Sophisticated Attacks
Navigating the Generative AI Maze in Business
The Practical Realities of AI Development
Beyond the Demo: Building AI Systems That Actually Work
Vibe Coding and the Rise of AI Agents: The Future of Software Development is Here
2025 Artificial Intelligence Index
How AI is Transforming Talent Development
Prompts as Functions: The BAML Revolution in AI Engineering
Building the Operating System for AI Agents
Bridging the AI Agent Prototype-to-Production Chasm
The Evolution of Reinforcement Fine-Tuning in AI
Beyond GPUs: Cerebras’ Wafer-Scale Engine for Lightning-Fast AI Inference
The Future of AI: Regulation, Foundation Models & User Experience
The AI Agent Rundown: 10 Things to Know Now
Why ‘Structure’ Is All You Need: A Deep Dive into Next-Gen AI Retrieval
Why Legal Hurdles Are the Biggest Barrier to AI Adoption
Unlocking Spreadsheet Intelligence with AI
Monthly Roundup: Deregulation, Hardware, and Inference Scaling
What AI Teams Need to Know for 2025
AI Unlocked: The Data Bottleneck
The Data-Centric Shift in AI: Challenges, Opportunities, and Tools
Monthly Roundup: Semiconductors, Frontier Models, and Practical Innovations
Breaking the Cloud Barrier: How DBOS Transforms Application Development
The Essential Guide to AI Guardrails
Beyond ETL: How Snow Leopard Connects AI, Agents, and Live Data
2024 Generative AI in Healthcare Survey Results
Monthly Roundup: BAML, Tencent’s Hunyuan Model, AI & Kubernetes, and the Future of Voice AI
Building the Future of Finance: Inside AI Valuation Bots
Unleashing the Power of BAML in LLM Applications
Cracking the Code: How Enterprises Are Adopting Generative AI
Monthly Roundup: Ray Compiled Graphs, Llama 3.2 and Multimodal AI, and Structured Data for RAG
Reimagining Code: The AI-Driven Transformation of Programming and Data Analytics
The Security Debate: How Safe is Open-Source Software?
Generative AI in Voice Technology
Building An Experiment Tracker for Foundation Model Training
Monthly Roundup: AI Regulations, GenAI for Analysts, Inference Services, and Military Applications
Unlocking the Power of LLMs with Data Prep Kit
Advancing AI: Scaling, Data, Agents, Testing, and Ethical Considerations
Bridging the Hardware-Software Divide in AI
Monthly Roundup: The Economic Realities of Large Language Models
From Hype to Reality: The Current State of Enterprise Generative AI Adoption
Automating Unstructured Data Extraction with LLMs
Generative AI in Context: Hybrid Intelligence and Responsible Development
Monthly Roundup: Navigating the Peaks and Valleys of Generative AI Technology
From Preparation to Recovery: Mastering AI Incident Response
Unlocking the Power of Unstructured Data
Postgres: The Swiss Army Knife of Databases
Supercharging AI with Graphs
Monthly Roundup: SB 1047, GraphRAG, and AI Avatars in the Workplace
Fine-tuning and Preference Alignment in a Single Streamlined Process
TinyML, Sensor-Driven AI, and Advances in Large Language Models
Machine Unlearning: Techniques, Challenges, and Future Directions
Unleashing the Power of AI Agents
Monthly Roundup: Llama 3, Agents, Evaluation Metrics, Cyc, TikTok, and more
LLMs for Data Access: Unlocking Insights with Text-to-SQL
2024 Artificial Intelligence Index
DBRX and the Future of Open LLMs
Monthly Roundup: New LLMs, GTC 2024, Constraint-Driven Innovation, Model Safety, and GraphRAG
Automating Software Upgrades: How to Combine AI and Expert Developers
Generative AI in the Industrial Sphere
The Intersection of LLMs, Knowledge Graphs, and Query Generation
Unlocking the Potential of Private Data Collaboration
Frontiers of AI: From Text-to-Video Models to Knowledge Graphs
Adaptive, Specialized, and Accessible: Where AI Systems Are Heading Next
2024 Themes and Trends in AI
The AI Infrastructure Revolution: From Cloud Computing to Data Center Design
AI in Depth: Transforming Transportation, Enterprise, and Policy
Software Meets Hardware: Enabling AMD for Large Language Models
Incentives are Superpowers: Mastering Motivation in the AI Era
Synthetic Futures: The Convergence of Biology and AI
AI Co-Pilots in Action: Transforming Function Calling in Cybersecurity
Leveling Up: Tools and Techniques to Make AI Development More Accessible
LLMs on CPUs, Period
Democratizing Wealth Management With AI
Knowledge Graphs: Contextualizing Enterprise Data for More Accurate LLMs
TimeGPT: Machine Learning for Time Series, Made Accessible
Best Practices for Building LLM-Backed Applications
The Evolution of Crypto, Blockchain, and Web3
Open Source Data and AI: Past, Present, Future
Orchestration for LLM and RAG applications
Reflections from the First AI Conference in San Francisco
Kùzu: A simple, extremely fast, and embeddable graph database
Navigating the Nuances of Retrieval Augmented Generation
The Rise of Generative AI-Powered Social Media Manipulation
Versioning and MLOps for Generative AI
Navigating the Generative AI Landscape
Trends in Data Management: From Source to BI and Generative AI
AI and the Future of Speech Technologies
The Future of Cybersecurity: Generative AI and its Implications
Ivy: The One-Stop Interface for AI Model Deployment and Development
Navigating the Risk Landscape: A Deep Dive into Generative AI
Software Development with AI and LLMs
A Lightweight SDK for Integrating AI Models and Plugins
Using LLMs to Build AI Co-pilots for Knowledge Workers
ETL for LLMs
The Future of Graph Databases
Delivering Safe and Effective LLM and NLP Applications
Using Data and AI to Democratize Entity Resolution and Master Data Management
An Open Source Data Framework for LLMs
Redefining AI Infrastructure: Deploying and Developing with a Next-Generation Developer Platform
The Rise of Custom Foundation Models
The Future of Vector Databases and the Rise of Instant Updates
LLMs Are the Key to Unlocking the Next Generation of Search
Building and Deploying Foundation Models for Enterprises
Building Robust AI Infrastructure for Critical Solutions
Machine Learning for High-Risk Applications
Boosting Perception With Synthetic Data
Revolutionizing B2B: Unleashing the Power of AI and Data
AI Metadata
The 2023 AI Index
Custom Foundation Models
Uncovering and Highlighting AI Trends
How Data and AI Happened
Blazing fast bulk data transfers between any cloud
Exhaustion of High-Quality Data Could Slow Down AI Progress in Coming Decades
Generating high-fidelity and privacy-preserving synthetic data
How technology is disrupting the venture capital industry
Running Machine Learning Workloads On Any Cloud
2023 Trends in Data Engineering and Infrastructure
Preparing for the Implementation of the EU AI Act and Other AI Regulations
The Open Source Stack Unleashing a Game-Changing AI Hardware Shift
Data Science and AI in Context
Evaluating Language Models
2023 Opportunities and Trends: Data, Machine Learning, and AI
Exploring DALL·E 2
Data Science at Shopify and Stitch Fix
Building a data management system for unstructured data
A Cloud Native Vector Database Management System
What’s Next for Machine Learning in Time Series
Efficient Methods for Natural Language Processing
Responsible and Trustworthy AI
Building a premier industrial AI research and product group
An open source, production grade vector search engine
A comprehensive suite of open source tools for time series modeling
Building Safe and Reliable AI applications
A new storage engine for vectors
Project Lightspeed: Next-generation Spark Streaming
The Unreasonable Effectiveness of Speech Data
Machine Learning Integrity
Synthetic data technologies can enable more capable and ethical AI
Confidential Computing for Machine Learning
Applied NLP Research at Primer
Using SQL to Retrieve Data from APIs and Web Services
Machine Learning for Time Series Intelligence
Unleashing the power of large language models
Building production-ready machine learning pipelines
Machine Learning at Gong
Data Infrastructure for Computer Vision
How DALL·E works
Scalable, end-to-end machine learning, for everyone
Orchestration and Pipelines for Data Scientists
Dataframes at scale
Software-Defined Assets
Adversarial Machine Learning
Orchestrating Machine Learning Applications
Narrative AI
Machine Learning Model Observability
Dataflow Automation
Practical Machine Learning and Deep learning
Machine Learning for Optimization
Efficient Scaling of Language Models
Data Science at Stitch Fix
The 2022 AI Index
Why You Need A Time-Series Database
Data Science at Shopify
An AI Risk Management Framework
An open source and end-to-end library for causal inference
The Graph Intelligence Stack
NLP and Language Models in Healthcare and the Life Sciences
Delivering Continuous Intelligence at Scale
Imperceptible NLP Attacks
Evolving Data Science Training Programs
Building Machine Learning Infrastructure at Netflix and beyond
Democratizing NLP
Machine Learning at Discord
Applications of Knowledge Graphs
Key AI and Data Trends for 2022
Large Language Models
Data and Machine Learning Platforms at Shopify
What is AI Engineering?
NLP and AI in Financial Services
Modern Experimentation Platforms
Reinforcement Learning in Real-World Applications
MLOps Anti-Patterns
Why You Need a Modern Metadata Platform
Making Large Language Models Smarter
AI Begins With Data Quality
Modernizing Data Integration
Deploying Machine Learning Models Safely and Systematically
Large-scale machine learning and AI on multi-modal data
Machine Learning in Astronomy and Physics
The Unreasonable Effectiveness of Multiple Dispatch
How To Lead In Data Science
Why interest in graph databases and graph analytics are growing
The State of Data Journalism
Auditing machine learning models for discrimination, bias, and other risks
An oscilloscope for deep learning
What’s new in data engineering
The evolution of the data science role and of data science tools
Data Augmentation in Natural Language Processing
Storage Technologies for a Multi-cloud World
Building a next-generation dataflow orchestration and automation system
Building a flexible, intuitive, and fast forecasting library
Neural Models for Tabular Data
Training and Sharing Large Language Models
Questioning the Efficacy of Neural Recommendation Systems
Automation in Data Management and Data Labeling
Reinforcement Learning For the Win
How Companies Are Investing in AI Risk and Liability Minimization
The Future of Machine Learning Lies in Better Abstractions
Why You Should Optimize Your Deep Learning Inference Platform
AI Beyond Automation
Injecting Software Engineering Practices and Rigor into Data Governance
Building a data store for unstructured data and deep learning applications
How Technology Companies Are Using Ray
Data quality is key to great AI products and services
Machine Learning in Healthcare
Measuring the Impact of AI and Machine Learning Research
The Mathematics of Data Integration and Data Quality
Pricing Data Products
Challenges, Opportunities, and Trends in EdTech
Towards Simple, Interpretable, and Trustworthy AI
The Rise of Metadata Management Systems
Tools for building robust, state-of-the-art machine learning models
Creating Master Data at Scale with AI
Bringing AI and computing closer to data sources
Deep Learning in the Sciences
Taking business intelligence and analyst tools to the next level
Data exchanges and their applications in healthcare and the life sciences
Key AI and Data Trends for 2021
A Unified Management Model for Successful Data-Focused Teams
Security and privacy for the disoriented
The State of Responsible AI
Improving the robustness of natural language applications
End-to-end deep learning models for speech applications
Securing machine learning applications
Testing Natural Language Models
Detecting Fake News
The Computational Limits of Deep Learning
Making deep learning accessible
Building and deploying knowledge graphs
Financial Time Series Forecasting with Deep Learning
A programming language for scientific machine learning and differentiable programming
Using machine learning to modernize medical triage and monitoring systems
Connecting Reinforcement Learning to Simulation Software
Using machine learning to detect shifts in government policy
What is AI Assurance?
Best practices for building conversational AI applications
Tools for scaling machine learning
From Python beginner to seasoned software engineer
Assessing Models and Simulations of Epidemic Infectious Diseases
Improving the hiring pipeline for software engineers
How to build state-of-the-art chatbots
Democratizing machine learning
How graph technologies are being used to solve complex business problems
Machines for unlocking the deluge of COVID-19 papers, articles, and conversations
Designing machine learning models for both consumer and industrial applications
Building open source developer tools for language applications
Viewing machine learning and data science applications as sociotechnical systems
Identifying and mitigating liabilities and risks associated with AI
How machine learning is being used in quantitative finance
Understanding machine learning model governance
Improving performance and scalability of data science libraries
Why TinyML will be huge
An open source platform for training deep learning models
Algorithms that continually invent both problems and solutions
Computational Models and Simulations of Epidemic Infectious Diseases
Human-in-the-loop machine learning
Next-generation simulation software will incorporate deep reinforcement learning
Business at the speed of AI: Lessons from Shopify
How deep learning is being used in search and information retrieval
The responsible development, deployment and operation of machine learning systems
Hyperscaling natural language processing
What businesses need to know about model explainability
Scalable Machine Learning, Scalable Python, For Everyone
Computational humanness, analogy and innovation, and soft concepts
Building domain specific natural language applications
The state of privacy-preserving machine learning
Taking messaging and data ingestion systems to the next level
Business at the speed of AI: Lessons from Rakuten
The combination of the right software and commodity hardware will prove capable of handling most machine learning tasks
Key AI and Data Trends for 2020
The evolution of TensorFlow and of machine learning infrastructure
Building large-scale, real-time computer vision applications
Taking stock of foundational tools for analytics and machine learning