Tag

Foundation Models

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

Building better enterprise AI: incorporating expert feedback in system development banner
Building better enterprise AI: incorporating expert feedback in system development
Enterprises that aim to build valuable GenAI applications must view them from a systems-level. LLMs are just one part of an ecosystem.
January 30, 2024
Chris Glaze
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“Fall in love with your data”—Snorkel AI’s Enterprise LLM Summit
Snorkel AI’s Jan. 25 Enterprise LLM Summit focused on one theme: AI data development drives enterprise AI success.
January 26, 2024
Snorkel Team
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Why QBE Ventures invested in Snorkel AI
QBE Ventures made a strategic investment in Snorkel AI because it provides what Insurers need: scalable and affordable ways to customize AI.
January 25, 2024
Alex Taylor
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Lynn Thompson
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Daniel Wypler
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Retrieval augmented generation (RAG): a conversation with its creator
Snorkel CEO Alex Ratner spoke with Douwe Keila, an author of the original paper about retrieval augmented generation (RAG).
January 16, 2024
Team Snorkel
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Snorkel Flow 2023.R4: enhanced UI + PDF and Databricks tools
New unified prompting UI + RAG features, PDF annotation, Databricks MLflow integration, Snorkel Flow Studio, and datasets load 2x faster!
January 9, 2024
Nick Harvey
How Snorkel Flow users can register custom models to Databricks
How Snorkel Flow users can register custom models to Databricks
The Databricks Model Registry integration equips Snorkel Flow users to automatically register custom, use case-specific models.
January 9, 2024
Hiromu Hota
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Stanford professor discusses exciting advances in foundation model evaluation
Snorkel CEO Alex Ratner chatted with Stanford Professor Percy Liang about evaluation in machine learning and in AI generally.
January 2, 2024
Team Snorkel
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BERT models: Google’s NLP for the enterprise
LLMs have claimed the spotlight since the debut of ChatGPT, but BERT models quietly handle most enterprise production NLP tasks.
December 27, 2023
Matt Casey
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How to tackle advanced classification challenges using Snorkel Flow
When done right, advanced classification applications cultivate business value and automation, unlock new business lines, and reduce costs.
December 14, 2023
Vincent Sunn Chen
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How predictive AI + generative AI build amazing document understanding
A proof-of-concept project that combines predictive AI + generative AI to minimize LLM’s risks while keeping their advantages.
December 5, 2023
Shahebaz Mohammad
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How to fine-tune Llama 2 in Snorkel Flow
Data scientists can fine-tune Llama 2 to adapt it to specific tasks. The Snorkel Flow data development platform makes it easy to do so.
November 28, 2023
Hoang Tran
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Enterprise LLM challenges and how to overcome them
Large language models open many new opportunities for data science teams, but enterprise LLM challenges persist—and customization is key.
November 16, 2023
Hoang Tran
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Snorkel Flow 2023.R3 release: PaLM integration, streamlined onboarding, and enhanced user experience
The 2023.R3 Snorkel Flow release is packed with improvements that amplify user experience, streamline workflows, and enhance performance, ensuring our users derive unparalleled value from our platform.
November 1, 2023
Nick Harvey
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Navigating Biden’s AI executive order with AI data development
The Biden administration issued an executive order that creates new AI standards and challenges. AI data development can help.
October 31, 2023
Vinny Corsi
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Snorkel AI researchers present 18 papers at NeurIPS 2023
The Snorkel AI team will present 18 research papers and talks at the 2023 Neural Information Processing Systems (NeurIPS) conference from December 10-16. The Snorkel papers cover a broad range of topics including fairness, semi-supervised learning, large language models (LLMs), and domain-specific models. Snorkel AI is proud of its roots in the research community and endeavors to remain at the forefront
October 31, 2023
Team Snorkel
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Two approaches to distill LLMs for better enterprise value
Distillation techniques allow enterprises to access the full predictive power of large language models at a tiny fraction of their cost.
October 31, 2023
Jason Fries
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Enterprise LLM Summit highlights the importance of data development
Snorkel AI’s Enterprise LLM Virtual Summit drew 1,000 attendees with speakers from Contextual AI, Google, Meta, Stanford, and Together AI.
October 27, 2023
Matt Casey
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How AI-powered claims processing creates new efficiencies in insurance
Insurance claims processing has long required a lot of tedious and expensive human labor, but artificial intelligence (AI) can help.
October 18, 2023
Team Snorkel
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Bloomberg’s Gideon Mann on the power of domain specialist LLMs
Gideon Mann, head of ML Product and Research at Bloomberg LP, chatted with Snorkel CEO Alex Ratner about building BloombergGPT.
October 17, 2023
Team Snorkel
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How to fine-tune GPT-3.5 Turbo in Snorkel Flow
Snorkel Flow makes it easy to fine tune LLMs like GPT-3.5 Turbo to work better for specific domain and enterprise requirements.
October 13, 2023
Hoang Tran
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Watch all Future of Data-Centric AI 2023 videos now!
Sessions at the Future of Data-Centric AI covered LLMs, gen AI, and more. All recordings are now publicly available. See them here!
October 12, 2023
Team Snorkel
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How AI facilitates more fair and accurate credit scoring
Ai and ML offer new avenues for credit scoring solutions and could usher in a new era of fairness, efficiency, and risk management.
October 4, 2023
Team Snorkel
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How AI is powering the next generation of trade surveillance
Regulators and compliance officers face a constantly evolving landscape of financial markets. Rule-based systems struggle where AI succeeds.
September 26, 2023
Team Snorkel
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How AI speeds patient classification and recruitment in clinical trials
The medical industry is exploding with data. Manually labeling data for clinical trials is a challenge. Fortunately, AI can help.
September 21, 2023
Team Snorkel
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Which is better, retrieval augmentation (RAG) or fine-tuning? Both.
Professionals in the data science space often debate whether RAG or fine-tuning yields the better result. The answer is “both.”
September 20, 2023
Hoang Tran
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Former U.S. Chief Data Scientist on past and future of data science
Past U.S. Chief Data Scientist DJ Patil talked with Snorkel AI CEO Alex Ratner on topics including the origin of the title “data scientist.”
September 12, 2023
Team Snorkel
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4 new papers show foundation models can build on themselves
The surest way to improve foundation models is through more and better data, but Snorkel researchers showed FMs can learn from themselves.
August 31, 2023
Fred Sala
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How AI saves money and improves banking complaint handling
Handling complaints effectively and efficiently with AI is essential to maintain customer satisfaction and protect the bank’s reputation.
August 24, 2023
Team Snorkel
Wayfair Logo
How Wayfair built better, faster catalog tagging with Snorkel Flow
The following was originally published on Wayfair’s tech blog. We have cross-posted it here, edited only to fit Snorkel’s formatting guidelines. — One of our missions at Wayfair is to help our 22 million customers find the products they are looking for. For example, when a customer searches for a “modern yellow sofa” on Wayfair, we want to show the most
August 22, 2023
Archana Sapkota
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Accelerating predictive task time to value with generative AI
Generative AI can write poems, recite common knowledge, and extract information. GenAI can also help quickly build predictive pipelines.
August 17, 2023
Bradley Fowler