LLM Distillation: How Step-by-Step LLM Distillation Yields Incredible Results #shorts

LLM Application Improvements: The View That Developers Need

Building Better LLM Applications in Snorkel Flow: An Overview #shorts

We Need Thousands of Research Papers to Flesh Out Data-Centric AI, Andrew Ng #shorts

The LLM application iteration loop within Snorkel Flow #shorts

Why You Should Never Fully Trust a Reward Model #shorts

The Importance of Data Quality for Successful Applications #shorts

The Importance of Alignment in AI for Ensuring Safe Interactions #shorts

What is AI alignment? A concise explanation. #shorts

Revolutionizing Enterprise AI Alignment with Programmatic Labeling #shorts

Data-centric AI for iterating on vast data sets: Andrew Ng's view

#llms have made massive progress, but #enterpriseai projects still come down to #data #shorts

The secret ingredient to #LLMs: reinforcement learning with human feedback (#RLHF) #shorts

How vision language models (#vlm) "see" images with non-visual concepts. #shorts #ai

What are vision language models (#vlm)? A cutting-edge researcher explains. #shorts #ai #airesearch

How #LLMs Help Build Powerful Models That Cost 0.1% as Much to Run! #shorts #enterprisea

The Benefits of Programmatic Labeling in Building a Spam Classifier #shorts

LLM customization made easier with synthetic data sets for specialized domains #shorts

Topic chunking boosts question-answering accuracy with large language models #shorts

How reusable are custom domain rules? (Spoiler: not very!) #shorts

Will Gemini or similar LLMs with long context windows make RAG obsolete? No. 🤔 #shorts

How to Handle Unavailable Data in Open Source Models? #shorts

Why large language models will never do everything you want off the shelf #shorts

Why #enterpriseai alignment is more important to focus on than #superalignment right now. #shorts

Enterprise Alignment explained in less than 20 seconds. #ai #enterpriseai #shorts

Forget #superalignment. First we must align current-generation #ai systems to enterprise needs

See #GPT4o in action on Snorkel Flow and learn how we got it there so fast. #shrts

How Snorkel Flow's labeling functions boost coverage and model performance fast! #shorts

How a data development platform eases data extraction in #banking #shorts

Why #LLM fine-tuning makes #ai applications better. #artificialintelligence #shorts

Has #data always been important? Yes. But #datacentricai focuses on data development over algorithms

Document intelligence: #llm #prompting is a great start, but then what? Turn to Snorkel AI #shorts

Build #ai applications fast with Snorkel Flow's programmatic #data labeling #shorts

How should enterprises use #foundationmodels? #stanford’s Percy Liang answers #enterpriseai #shorts

Large language model evaluation: how do you do it? #ai #evaluation #airesearch #stanford #shorts

BNY Mellon's Sarthak Pattanaik on what #AI means for banking #bankingai #enterpriseai #shorts

#LLM systems: #RAG is just a special case of an #AI system. #enterpriseai #shorts

DPO-aligned LLM takes second on AlpacaEval Leaderboard (behind GPT-4) #DPO #RLHF #shorts

Building a novel #DPO-aligned #largelanguagemodel posed some... challenges#alpacaeval #shorts

A 64-point accuracy boost on an #enterpriseai application? What had the biggest impact? #shorts

What does #datacentricai mean to #ai development workflows? Focus on data, over algorithms. #shorts

We automated cumbersome contract question-answering tasks with #ai through a #rag system #shorts

Super-fast enterprise AI! From no labeled data to 96% recall in three weeks. #shorts

What one client was able to do in Snorkel Flow in just two days: revalidating a model fast! #shorts

What's the biggest impact of enterprise AI systems this year? Snorkel AI CEO: "zero to one" #shorts

Where might AI assistants pop up first in the enterprise? Chris Glaze of Snorkel AI answers. #shorts

"How do you fall in love with your data?" BNY Mellon's Sarthak Pattanaik #shorts

Collaboration is vital to enterprise data science success #shorts