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Foundation models refer to large, pre-trained AI models that serve as the basis for a wide range of downstream tasks. Some generate text. Others can classify images. These models train on vast amounts of diverse data, and data scientists can fine-tune them to specific use cases, making them valuable for enterprises looking to deploy AI quickly and effectively across multiple domains.
All articles on Foundation Models
Why enterprises should embrace LLM distillation
Unlock possibilities for your enterprise with LLM distillation. Learn how distilled, task-specific models boost performance and shrink costs.
February 18, 2025
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Unlock proprietary data with Snorkel Flow and Amazon SageMaker
Accelerate LLM development with Snorkel Flow and SageMaker. Automate dataset curation, accelerate training, and gain a competitive advantage.
December 2, 2024
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Task Me Anything: innovating multimodal model benchmarks
“Task Me Anything” empowers data scientists to generate bespoke benchmarks to assess and choose the right multimodal model for their needs.
September 4, 2024
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Alfred: Data labeling with foundation models and weak supervision
Introducing Alfred: an open-source tool for combining foundation models with weak supervision for faster development of academic data sets.
August 27, 2024
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Meta’s new Llama 3.1 models are here! Are you ready for it?
Meta released Llama 3 405B today, signaling a new era of open source AI. The model is ready to use on Snorkel Flow.
July 23, 2024
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Data-centric AI with Snorkel and MinIO
High-performing AI systems require more than a well-designed model. They also require properly constructed training and testing data.
July 12, 2024
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Weak supervision for non-categorical applications + superalignment
We need more labeled data than ever, so we have explored weak supervision for non-categorical applications—with notable results.
July 2, 2024
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Snorkel AI signs strategic collaboration agreement with AWS to help enterprises cross the demo-to-production chasm
To tackle generative AI use cases, Snorkel AI + AWS launched an accelerator program to address the biggest blocker: unstructured data.
June 27, 2024
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AI alignment made simple: innovative solutions for businesses
AI alignment ensures that AI systems align with human values, ethics, and policies. Here’s a primer on how developers can build safer AI.
June 27, 2024
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Vision language models: how LLMs boost image classification
Vision language models demonstrate impressive image classification capabilities, but LLMs can help improve their performance. Learn how.
June 12, 2024
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Long context models in the enterprise: benchmarks and beyond
Snorkel researchers devised a new way to evaluate long context models and address their “lost-in-the-middle” challenges with mediod voting.
June 6, 2024
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How to build production-grade RAG retrieval with Snorkel Flow
See a walkthrough of how Snorkel Flow users build applications with production-grade RAG retrieval components.
June 4, 2024
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Walking safely before building flying saucer seatbelts: introducing Enterprise Alignment
Snorkel takes a step on the path to enterprise superalignment with new data development workflows for enterprise alignment
May 20, 2024
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Accelerating AI development in manufacturing with Snorkel Flow and AWS SageMaker
The manufacturing industry has experienced a massive influx of data. Snorkel AI and AWS Sage Maker can make that data actionable.
May 1, 2024
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How ROBOSHOT boosts zero-shot foundation model performance
ROBOSHOT acts like a lens on foundation models and improves their zero-shot performance without additional fine-tuning.
April 30, 2024
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Discover what’s new in Snorkel Flow: Flexible data and LLM connectivity, secure data controls, and more!
Unlock advanced LLM customization with Snorkel Flow’s new release! Explore flexible data integrations, secure controls, and multimodal support to fine-tune language models for enterprise use. Discover how to leverage images and diverse data types for AI-driven insights.
April 24, 2024
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Faster than ever document intelligence with new Snorkel Flow FM-first workflow
Snorkel Flow’s new FM-first workflow for building document intelligence applications will get you from demo to production faster than ever.
April 24, 2024
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The art of data development for Enterprise LLMs
Snorkel’s Paroma Varma and Google’s Ali Arsenjani discus the role of data in the development and implementation of LLMs.
April 16, 2024
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CRFM’s HELM and enterprise LLM evaluation beyond accuracy
As Snorkel AI prepares to build better enterprise LLM evaluations, we spoke with Yifan Mail from Stanford’s CRFM HELM project.
April 3, 2024
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How we achieved 89% accuracy on contract question answering
A customer wanted an llm system for complex contract question answering tasks. We helped them build it—beating the baseline by 64 points.
April 2, 2024
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Five sessions not to miss at Google Cloud Next 24
Snorkel AI will be at Google Cloud Next. The event will feature more than 700 sessions, so we picked five that we think you shouldn’t miss.
March 27, 2024
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Here’s how Snorkel Flow + Google AI built an enterprise-ready model in a day
Google and Snorkel AI customized PaLM 2 using domain expertise and data development to improve performance by 38 F1 points in a matter of hours.
March 19, 2024
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Snorkel teams with Microsoft to showcase new AI research at NVIDIA GTC
Microsoft infrastructure facilitates Snorkel AI research experiments, including our recent high rank on the AlpacaEval 2.0 LLM leaderboard.
March 18, 2024
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Snorkel Team
How Skill-it! enables faster, better LLM training
Humans learn tasks better when taught in a logical order. So do LLMs. Researchers developed a way to exploit this tendency called “Skill-it!”
March 12, 2024
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Enterprise GenAI to surge in 2024: survey results
Enterprise GenAI 2024: applications will likely surge toward production, according to Snorkel AI Enterprise LLM Summit survey results .
February 29, 2024
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Large language model training: three phases that shape LLM training
Training large language models is a multi-layered stack of processes, each with its unique role and contribution to the model’s performance.
February 27, 2024
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LoRA: Low-Rank Adaptation for LLMs
Low-rank adaptation (LoRA) lets data scientists customize GenAI models like LLMs faster than traditional full fine-tuning methods.
February 21, 2024
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LLM distillation demystified: a complete guide
LLM distillation isolates task-specific LLM performance and mirrors it in a smaller format—creating faster and cheaper performance.
February 13, 2024
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