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Fine-tuning adapts a pre-trained machine learning model to perform well on new tasks. Data scientists call these "foundation models." Foundation model providers train these enormous neural networks on millions of documents. This diversity of training data allows foundation models to perform many tasks that they were not specifically trained for—though at low accuracy.
Instead of starting from scratch, fine-tuning allows data scientists to build upon these foundations. They feed the models additional input and output examples to adapt them to specific business use cases.
This approach reduces the time and resources needed to deploy AI solutions while maintaining high performance.
All articles on Fine-Tuning
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
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New benchmark results demonstrate value of Snorkel AI approach to LLM alignment
Snorkel researchers’ state-of-the-art methods created a 7B LLM that ranked 2nd, behind only GPT-4 Turbo, on AlpacaEval 2.0 leaderboard.
January 24, 2024
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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
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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
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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
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First cohort of Snorkel GenAI customers sees gains up to 54 points
In its first six months, Snorkel Foundry collaborated on high-value projects with notable companies and produced impressive results.
December 20, 2023
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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
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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
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LLM distillation techniques to explode in importance in 2024
LLM distillation will become a more important in 2024, according to a poll of attendees at Snorkel AI’s 2023 Enterprise LLM virtual summit.
November 9, 2023
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How to fine-tune large language models for enterprise use cases
LLMs have a broad but shallow knowledge, but fall short on specialized tasks. For best performance, enterprises must fine tune their LLMs.
November 2, 2023
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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
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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
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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
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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
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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
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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
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Standard LLMs are not enough. How to make them work for your business
Most data science leaders expect to customize LLMS, but the process of making LLMs work for your business is still a fresh challenge.
October 6, 2023
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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
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Data labeling: a practical guide (2024)
Data labeling remains a core requirement for machine learning projects—especially in the age of genAI and LLMs. Here’s a handy guide.
September 29, 2023
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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
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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
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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
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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
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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
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Beyond prompting: getting production quality LLM performance with Snorkel Flow
As enterprises look toward deploying LLM-powered, business-critical applications, they’re learning to use strategies beyond prompting.
August 9, 2023
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Data fuels enterprise AI value: 6 takeaways from the Gartner Hype Cycle for Artificial Intelligence, 2023
GenAI may be the most transformative technology of the past decade but data is where enterprises are able to realize real value from AI today.
August 2, 2023
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GenAI most impactful tech of the decade | Gartner AI Hype Cycle
Generative AI is at peak hype and poised to dive into the “trough of despair,” according to the 2023 Gartner® Hype Cycle™ for AI.
July 24, 2023
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How we built better GenAI with programmatic data development
We used weak supervision to programmatically curate instruction tuning data for open-source LLMs to build a better GenAI.
July 19, 2023
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