Tag

NLP

Natural Language Processing (NLP) is the branch of AI that enables machines to understand, interpret, and generate human language. NLP applications include chatbots, virtual assistants, sentiment analysis, document processing, and more. Effective NLP models rely on high-quality text data and annotations.

All articles on NLP

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AMA technique: a trick to build systems with foundation models
Simran Arora is a machine learning researcher at Stanford University. She presented “Ask Me Anything: How are Foundation Models Changing the Way We Build Software” at Snorkel AI’s Foundation Model Virtual Summit 2023.
April 13, 2023
Team Snorkel
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Snorkel AI x Hugging Face: unlock foundation models for enterprises
Snorkel AI teamed up with Hugging Face to provide enterprises with even more flexibility and choice as they develop AI applications.
April 6, 2023
Friea Berg
Ananya Kumar, standfor student
Boost foundation model results with linear probing and fine-tuning
Ananya Kumar, Stanford Ph.D. student, explains methods to improve foundation model performance, including linear probing and fine-tuning.
April 5, 2023
Team Snorkel
Jimmy Lin SambaNova Systems FM Summit
Practical solutions: enterprise value from foundation models
Jimmy Lin is an NLP product lead at SambaNova Systems. He presented “A Practical Approach to Delivering Enterprise Value with Foundation Models” at Snorkel AI’s 2023 Foundation Model Virtual Summit.
March 31, 2023
Team Snorkel
Snorkel Flow Spring 2023 key features
Snorkel Flow Spring 2023: warm starts and foundation models
Snorkel Flow’s Spring 2023 release focuses on adapting foundation models for enterprise use—including fine-tuning and additional features.
March 30, 2023
Nick Harvey
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Adverse drug events: how to spot them with machine learning
Physician notes and other sources of unstructured data can offer insight into drugs’ negative side effects. Here’s how modern machine learning tools can help turn all that data into a useful resource.
March 29, 2023
Nazanin Makkinejad
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New research expands limitations of weak supervision, foundation models
Snorkel AI researchers continue to push the frontier of machine learning, as demonstrated by the 18 research papers recently added to our website.
March 24, 2023
Matt Casey
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Research roundup: dive into the latest foundation model research
Snorkel AI CEO and co-founder Alex Ratner recently spoke with five Snorkel researchers about their foundation model research.
March 23, 2023
Matt Casey
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McKinsey QuantumBlack experts: exciting foundation model future
McKinsey’s Carlo Giovine and David Harvey present “Trends in Enterprise ML and the potential impact of Foundation Models” at Snorkel’s Foundation Model Summit.
March 21, 2023
Team Snorkel
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Cohere’s Alammar encourages effective strategy for Generative AI
Jay Alammar, director and engineering fellow at Cohere, presents strategies to enhance the value of Generative AI.
March 15, 2023
Team Snorkel
Snorkel+Google Cloud banner
Snorkel AI Teams with Google Cloud and Vertex AI to speed AI deployment
Snorkel AI, Google Cloud and Vertex AI partner to help organizations transform data into AI-powered systems faster than ever.
March 14, 2023
Henry Ehrenberg
HuggingFace Amanpreet Singh
HuggingFace research lead on unified foundation models
Amanpreet Singh, Lead Researcher at Hugging Face gave a presentation entitled Towards Unified Foundation Models for Vision and Language Alignment a Snorkel AI’s Foundation Model Summit in January.
March 8, 2023
Team Snorkel
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Foundation Model Summit Sessions Show Challenges and Promise
Twelve speakers shared their insights into the present and future of foundation models January event; see what they had to say.
March 7, 2023
Matt Casey
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Google’s Dr. Arsanjani on Enterprise Foundation Model Promise and Challenges
Ali Arsanjani, director of cloud partner engineering at Google Cloud, presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit.
March 2, 2023
Team Snorkel
Scrabble tiles spelling "foundation." Relevant to Foundation Models, no?
Foundation Models 101: a guide with essential FAQs
Foundation Models (FMs), such as GPT-3 and Stable Diffusion, mark the beginning of a new era in machine learning and artificial intelligence. What are they and how will they impact your business? Find out in our guide.
March 1, 2023
Matt Casey
Combining foundation models with weak supervision blog banner
Combining foundation models with weak supervision
Combining foundation model outputs with weak supervision yields faster model development and requires fewer ground truth labels.
March 1, 2023
Matt Hoffman
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Operationalizing knowledge for data-centric AI
Snorkel AI CEO and Co-Founder Alex Ratner’s introduction to data-centric AI from the 2022 Future of Data-Centric AI virtual conference.
February 27, 2023
Team Snorkel
Ian Eisenberg from Credo AI
Credo AI DS head on operationalizing responsible AI
Credo AI’s head of data science explains at Snorkel’s FDCAI 2022 how his team works to operationalize responsible AI assessment tools.
February 22, 2023
Team Snorkel
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How a Brown professor sharpened and shrunk GPT-3
Brown professor Stephen Bach tells Snorkel CEO Alex Ratner about his research into improving foundation models like GPT-3 with curated data.
February 21, 2023
Team Snorkel
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Aspect-based sentiment analysis in Snorkel Flow
Understanding and quantifying people’s opinions has become increasingly important to businesses, but the way people can express multiple thoughts in the same sentence has frustrated practitioners’ efforts to extract those opinions cleanly—a problem we can solve through aspect-based sentiment analysis (ABSA).
February 15, 2023
Lia Chin-Purcell
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Comcast’s data-centric approach to speech interfaces
Jan Neumann, Vice President of Machine Learning for Comcast Applied AI and Discovery, describes Comcast’s data-centric AI approach to speech.
February 14, 2023
Team Snorkel
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Meta research manager talks speech and search
Meta senior applied research manager Anoop Sinha and Snorkel AI co-founder Braden Hancock discuss mastering speech and search with TWIML host Sam Charrington.
February 10, 2023
Team Snorkel
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Accuracy top concern for Foundation Model adoption—Poll
Most poll respondents at Snorkel AI’s recent Foundation Model Virtual Summit named questionable accuracy as the biggest barrier preventing them from getting organizational value from Foundation Models.
January 31, 2023
Matt Casey
Liger: Fusing foundation model embeddings & weak supervision blog image
How Foundation Models bolster programmatic labeling
Snorkel CEO Alex Ratner interviews Mayee Chen about how Liger improves the effectiveness of programmatic labeling through foundation model embeddings.
January 26, 2023
Team Snorkel
Unmasking Trafficking Risk in Commercial Sex Supply Chains with Machine Learning Blo image
Unmasking Trafficking Risk in Commercial Sex Supply Chains with Machine Learning
Hamsa Bastani presented a summary of her and her co-authors’ ongoing work using machine learning and Snorkel AI’s tools to detect and track activities that are associated with a high risk for global sex trafficking.
January 20, 2023
Team Snorkel
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Prompting and weak supervision to build better, smaller models
Snorkel AI co-founder and CEO Alex Ratner recently interviewed several Snorkel researchers about their published academic papers. In this video, Alex talks with Ryan Smith, Senior Applied Scientist at Snorkel, about the work he did on using foundation models to build compact, deployable, and effective models.
January 19, 2023
Team Snorkel
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FM Summit shows Foundation Model hurdles and potential
Snorkel AI held its Foundation Model Summit Jan 17, bringing together 12 presenters and over 600 attendees at 10 virtual sessions. The event drew registrants from across many sectors, including the tech industry, healthcare, and financial services.
January 18, 2023
Matt Casey
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Contrastive Learning boosts Foundation Model specialization
Snorkel AI co-founder and CEO Alex Ratner talks with Ananya Kumar about the work he did on improving the effectiveness of foundation models by using contrastive learning, image augmentations, and labeled subsamples.
January 13, 2023
Team Snorkel
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Adapting language-based models beyond English
While a majority of Natural Language Processing (NLP) models focus on English, the real world requires solutions that work with languages across the globe. This demo shows how effectively users can build cross-language models in Snorkel Flow.
January 12, 2023
Anastassia Kornilova
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April Guo
Pixability logo for a Snorkel Flow customer success case study
How Pixability uses foundation models to accelerate NLP application development by months
Using Snorkel Flow, Pixability has created a way to build classifiers for massive amounts of YouTube data quickly—that was previously out of reach.
January 11, 2023
Nick Harvey