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Snorkel AI

Building AI-Native Systems for Federal Infrastructure: A Conversation with Rezaur Rahman Code World Models and AutoHarness for LLM Agents Benchtalks #1: Alex Shaw (Terminal-Bench, Harbor) – Building the Benchmark Factory Building FinQA: An Open RL Environment for Financial Reasoning Agents How Tool Discipline Let a 4B Model Outsmart a 235B Giant on Financial Tasks Coding agents don’t need to be perfect, they need to recover Closing the Evaluation Gap in Agentic AI SlopCodeBench: Measuring Code Erosion as Agents Iterate Introducing the Snorkel Agentic Coding Benchmark 2026: The year of environments Part V: Future Direction and Emerging Trends in Rubric-Based AI Evaluation The self-critique paradox: Why AI verification fails where it’s needed most Chat With the Terminal-Bench Team | Snorkel AI Intelligence per watt: A new metric for AI’s future Terminal-Bench 2.0: Raising the bar for AI agent evaluation Snorkeling in RL environments Introducing SnorkelSpatial: A Benchmark for LLM Spatial Reasoning Scaling Trust: Rubrics in Snorkel's Quality Process Evaluating Multi-Agent Systems in Enterprise Tool Use Evaluating Coding Agents with Terminal-Bench 2.0 Parsing isn’t neutral: why evaluation choices matter The science of rubric design The right tool for the job: An A-Z of rubrics Data quality and rubrics: how to build trust in your models Building the benchmark: inside our agentic insurance underwriting dataset Evaluating AI agents for insurance underwriting LLM observability: key practices, tools, and challenges Anthropic Claude + AWS: revolutionizing pharma data analytics with Snorkel AI Data-centric development of an enterprise AI agent with Snorkel Building the data development platform for specialized AI LLM-as-a-judge for enterprises: evaluate model alignment at scale Why GenAI evaluation requires SME-in-the-loop for validation and trust Research spotlight: is long chain-of-thought structure all that matters when it comes to LLM reasoning distillation? Why enterprise GenAI evaluation requires fine-grained metrics to be insightful What is specialized GenAI evaluation, and why is it so critical to enterprise AI? LLM alignment techniques: 4 post-training approaches Research spotlight: Is intent analysis the key to unlocking more accurate LLM question answering? Why enterprises should embrace LLM distillation Retrieval-augmented generation (RAG) failure modes and how to fix them What is large language model (LLM) alignment? Databricks + Snorkel Flow: integrated, streamlined AI development How LLM evaluation drives better models in Snorkel Flow Unlock proprietary data with Snorkel Flow and Amazon SageMaker LLM evaluation in enterprise applications: a new era in ML Snorkel AI joins the AWS ISV Accelerate Program and launches Snorkel Flow Availability in AWS Marketplace AI data development: a guide for data science projects SnorkelCon 2024: Inaugural Snorkel AI user conference gathers leaders from 30+ Fortune 500 companies Snorkel Flow 2024.R3: Supercharge your AI development with enhanced data-centric workflows Explore the new GenAI Evaluation Suite: Snorkel 2024.R3 New NLP features in Snorkel Flow 2024.R3 Enterprise data compliance and security review: Snorkel Flow 2024.R3 How a global financial services company built a specialized AI copilot accurate enough for production Task Me Anything: innovating multimodal model benchmarks Alfred: Data labeling with foundation models and weak supervision RAG: LLM performance boost with retrieval-augmented generation Call center AI for customer experience management: a case study New GenAI features, data annotation: Snorkel Flow 2024.R2 How data slices transform enterprise LLM evaluation Meta’s Llama 3.1 405B is the new Mr. Miyagi, now what? Meta’s new Llama 3.1 models are here! Are you ready for it? Data-centric AI with Snorkel and MinIO Weak supervision for non-categorical applications + superalignment Snorkel AI signs strategic collaboration agreement with AWS to help enterprises cross the demo-to-production chasm AI alignment made simple: innovative solutions for businesses How does the Snorkel Flow label model work? Vision language models: how LLMs boost image classification Long context models in the enterprise: benchmarks and beyond How to build production-grade RAG retrieval with Snorkel Flow How Bonito helps fine-tune specialized LLMs faster than ever Walking safely before building flying saucer seatbelts: introducing Enterprise Alignment Role-based access controls in Snorkel Flow secure enterprise data Accelerating AI development in manufacturing with Snorkel Flow and AWS SageMaker How ROBOSHOT boosts zero-shot foundation model performance Discover what’s new in Snorkel Flow: Flexible data and LLM connectivity, secure data controls, and more! Faster than ever document intelligence with new Snorkel Flow FM-first workflow The art of data development for Enterprise LLMs Crossing the demo-to-production chasm with Snorkel Custom How Snorkel topped the AlpacaEval leaderboard (and why we're not there anymore) CRFM's HELM and enterprise LLM evaluation beyond accuracy How we achieved 89% accuracy on contract question answering Content filtering breakthrough: Snorkel client reaches 96% recall in 3 days Here's how Snorkel Flow + Google AI built an enterprise-ready model in a day Snorkel teams with Microsoft to showcase new AI research at NVIDIA GTC How Skill-it! enables faster, better LLM training Fine-tuned representation models boost LLM systems. Here's how Enterprise GenAI to surge in 2024: survey results Large language model training: how three training phases shape LLMs LoRA: Low-Rank Adaptation for LLMs LLM distillation demystified: a complete guide Enterprises must shift their focus from models to data in AI development Insurance’s GenAI revolution: a business perspective Scaling human preferences in AI: Snorkel's programmatic approach Building better enterprise AI: incorporating expert feedback in system development “Fall in love with your data”—Snorkel AI’s Enterprise LLM Summit Why QBE Ventures invested in Snorkel AI New benchmark results demonstrate value of Snorkel AI approach to LLM alignment Retrieval augmented generation (RAG): a conversation with its creator Snorkel Flow 2023.R4: enhanced UI + PDF and Databricks tools How Snorkel Flow users can register custom models to Databricks Stanford professor discusses exciting advances in foundation model evaluation
Five sessions not to miss at Google Cloud Next 24
Friea Berg · 2024-03-27 · via Snorkel AI

In just a few weeks, Snorkel is excited to join Google in sunny Las Vegas for Google Cloud Next (April 9-11).

At Google Cloud Next, you’ll have the opportunity to hear directly from Snorkel, Google, and AI innovators like Wayfair and Wells Fargo about how you can move AI prototypes into production by programmatically developing your data. You’ll learn how Fortune 500 enterprises have built production-ready, highly custom AI solutions using Google Gemini and PaLM 2 models, Vertex AI, and Snorkel Flow. You also get the chance to meet Snorkel AI co-founder Paroma Varma and get insights into how she’s building an innovative, adaptable, and flexible AI/ML company.

With about 750 sessions – and more than 200 on the AI track alone – it will be a busy week!  Here are our team’s picks for five sessions you won’t want to miss.

Full disclosure: this list includes two sessions that feature speakers from Snorkel AI. And, while certainly biased, we also think these sessions promise to be both impactful and useful.

How Wayfair is transforming customer experiences with data-centric AI

Description: Learn how Wayfair is harnessing the power of machine learning and data to make it easier for customers to find the exact home products they’re looking for with Snorkel AI on Google Cloud. You’ll find out how highly accurate product tags can be extracted from supplier-provided labels and product images to clean and enrich online catalogs. This delivers higher-quality content for customers and the ability to quickly adapt as customer searches evolve.

Featured speakers:

  • Kieran Kavanagh, Principal Architect, Retail Google Cloud
  • Margaret Pierson, Director of Machine Learning, Wayfair
  • Saanjeith Varathan, Machine Learning Success Manager, Snorkel AI

Time: April 10th 1:45-2:30pm

a poster with the words google cloud next to it

Operationalizing GenAI with Vertex AI

Description: The emergence of foundation models and generative AI has introduced a new era for building AI systems. Selecting the right model from a range of architectures and sizes, curating data, engineering optimal prompts, tuning models for specific tasks, grounding model outputs in real-world data, optimizing hardware – these are just a few of the novel challenges that large models introduce. Delve into the fundamental tenets of MLOps, the necessary adaptations required for generative AI, and capabilities within Vertex AI to support this new workflow.

Featured speakers:

  • Mikhail Chrestkha, Product Manager, Vertex AI, Google Cloud
  • Debasish Das, Director of Engineering, Machine learning, Credit Karma
  • Matt Ferrari, Head of Data, Wayfair
  • Chase Lyall, Product Manager, Vertex AI, Google Cloud

Time: Day 3, April 11 11:00 AM – 11:45 AM PDT

What’s next with generative AI at Google Cloud

Description: In this spotlight, we will explore Google Cloud’s approach to getting started with generative AI and share examples of how organizations are putting generative AI into production with Google Cloud to create new value for their customers, employees and partners. Join the session to learn about all our new announcements planned for the best foundation models and the best integrated platform to work with when it comes to generative AI.

Featured speakers:

  • Warren Barkley, Sr. Director, Product Management Vertex, Google
  • Polong Lin, Developer Advocate, Google Cloud
  • Kalyan Pamarthy, Group Product Manager, Vertex AI, Google Cloud
  • Fiona Tan, CTO, Wayfair

Times:

  • Tuesday, April 9 • 11:00 AM – 11:45 AM
  • Wednesday, April 10 • 4:15 PM – 5:00 PM

The past, present, and future of Google Kubernetes Engine

Description: Kubernetes is the de facto standard for running modern, containerized workloads in cloud. Google open-sourced Kubernetes 10 years ago and has built the easiest to use and most scalable managed service in Google Kubernetes Engine (GKE). Join this keynote to learn how top customers are leveraging GKE to run their businesses and to hear about the latest innovations and future directions of GKE.

Featured speakers:

  • Ameer Abbas, Outbound Product Manager, Google Cloud
  • Drew Bradstock, Sr Director, PM, Cloud Runtimes, Google Cloud
  • Gari Singh, Product Manager, Google Cloud

Time: Day 3, April 11, 09:00 AM – 09:45 AM PDT

Diversity in Startups: Tactics for Accelerating Success

Description: As organizations – especially startups! – strive for innovation, adaptability, and flexibility, the ability to tap diverse perspectives represents a vital competitive advantage. Recruiting and nurturing diverse teams is an ongoing challenge, and the current competitive climate intensifies the difficulties associated with hiring. Join this panel discussion to hear strategies and actionable advice for capitalizing on diverse workforces.

Featured speakers:

  • Bella Liu, Co-founder and CEO, Orby AI
  • Paroma Varma, Co-Founder & Head of Applied ML, Snorkel AI
  • Dwayne Forde, Co-Founder & CTO, Mantle
  • Melonie Parker, Chief Diversity Officer, Google
  • Beth Rogozinski, CEO, Oncoustics

Time: Wednesday, April 10, 11:45 AM – 12:30 PM PDT

a black background with a white text that reads how wayfair is transforming customer

How to find Snorkel AI at Google Cloud Next

For a deeper conversation, we invite you to stop by the Snorkel booth in the AI Innovation Space.  Our team can explain how top banks, insurers, healthcare providers, and other enterprises are working with Google and Snorkel to solve real business challenges today.  Plus, you can learn more about how Snorkel seamlessly integrates with Google AI and how Snorkel Flow + Google AI built an enterprise-ready model in a day.

We’re excited to understand more about your challenge and explore how Snorkel can help you build enterprise AI applications faster (and more accurately) than ever before.

We look forward to seeing you at Google Next!

Learn More

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