📰 AI News & Updates

Data Scientists & Data Engineers: How the Best Teams Work // Panel // DE4AI

Putting the AI back in Medallion Lake Design // Simon Whiteley

Unpacking 3 Types of Feature Stores // Simba Khadder // MLOps Podcast #265

Data Quality and Tonic Textual // Adam Kamor // MLOps Podcast #262 clip

RAG Quality Starts with Data Quality // Adam Kamor // MLOps Podcast #262

Exploring Markovian Models // Yuri Plotkin // MLOps Podcast #253 clip

The Variational Book // Yuri Plotkin // MLOps Podcast #253

Balancing Speed and Safety // Panel // AIQCON

A Blueprint for Scalable & Reliable Enterprise AI/ML Systems // Panel // AIQCON

AI Training and Validation // Shaun Wei // MLOps Podcast #244 clip

AB Testing for Optimal ROI // Miguel Fierro // MLOps Podcast #240 clip

AI Agents for Consumers // Shaun Wei // MLOps Podcast #244

The Challenge of Establishing AI Quality Standards // Cody Peterson // MLOps podcast #234

Data Guardrails and Alert Systems // Chad Sanderson // MLOps podcast #226 clip

Beyond Guess-and-Check: Towards AI-assisted Prompt Engineering // Alex Cabrera // AI in Production

No GPU Before PMF // Stanislas Polu // AI in Production Conference Lightning Talk

Ghostwriter - AI Writing That Learns From You // Jonny Dimond // AI in Production Conference

Open Standards Make MLOps Easier and Silos Harder // Cody Peterson // MLOps podcast #234

Advances in AI Model Evaluation // Salman Avestimehr // MLOps podcast #230 clip 2

The Rise of Modern Data Management // Chad Sanderson // MLOps Podcast #226

Lessons from Building LLM-based Social Media Products // Faizaan Charania // AI in Production

Enabling Efficient Trillion Parameter Scale Training for Deep Learning Models // Tunji Ruwase

Seeing Like a Language Model // Linus Lee // AI in Production Conference Full Talk

Productionizing Health Insurance Appeal Generation // Holden Karau // AI in Production Talk

From MVP to Production // Day 2 Panel 2 // AI in Production Conference

Tecton's Approach to Scaling Data Aggregations // Mike Eastham // MLOps podcast #209 clip

Challenging Big Data Assumptions // Hannes Mühleisen & Jordan Tigani // MLOps Podcast #202 clip

PDF Parsing and Value Chain Analysis // Paco Nathan // MLOps Podcast #201 clip

Small Data, Big Impact: The Story Behind DuckDB // Hannes Mühleisen & Jordan Tigani // Podcast #202

Language, Graphs, and AI in Industry // Paco Nathan // MLOps Podcast #201

OpenAI's GPT Empowering Language Models with Code Execution // Gregory Kamradt // Podcast #191 clip

Building Defensible AI Apps // Gregory Kamradt @DataIndependent // MLOps Podcast #191

Authoring Interactive, Shareable AI Evaluation Reports with Zeno // Alex Cabrera // LLMs III Talk

Product Strategy for LLM features when LLM isn’t your Product // Harini Kannan // LLMs III LT

Feature Infrastructure // Mike Del Balso & Josh Wills // MLOps Podcast # 186 clip

Amplifying Impact with Generative AI: Insights from 10,000 Colleagues // Paul van der Boor // Talk 4

Rituals & Best Practices // Jean Machado, Meghana Satish, Olivia Houghton, Theodore Meynard // clip

Using Product Analytics to Build Better LLM Applications // Henry Scott-Green // Lightning Talk 6

Observability for LLMs // Phillip Carter // LLMs in Production Conference Lightning Talk 4

MLOps@GetYourGuide // Jean Machado, Meghana Satish, Olivia Houghton, Theodore Meynard// Podcast #182

Harnessing User Feedback for ML Platform Updates // Stephen Batifol // MLOps Podcast #178 clip

[Exclusive] Tecton Round-table // Get your ML Application Into Production

The Quest for a Unified MLOps Infrastructure // Lamia Youseff // MLOps Podcast # 175 clip

From Virtualization to AI Integration // Lamia Youseff // MLOps Podcast # 175

Steering a Large-Scale Data Migration // Michelle Marie Conway // MLOps Podcast Coffee #174 clip

Real User Data's Power in Product Iteration // Phillip Carter // MLOps Podcast #170 clip

All the Hard Stuff with LLMs in Product Development // Phillip Carter // MLOps Podcast #170

RLHF Data Collection in Practice // Andrew Mauboussin // LLMs in Prod Conference Part 2