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

Measuring NLP Progress With Sebastian Ruder
In this episode of Science Talks, Sebastian Ruder, Research Scientist at DeepMind, shares his thoughts on making AI practical with Snorkel AI’s Braden Hancock. This conversation covers progress made in the NLP domain with emerging research, new benchmarks like SuperGLUE, rich repositories and news sources that keep you in the loop and on top of what’s new in NLP, and more.
March 10, 2021
Team Snorkel
Productionizing ML Research With Thomas Wolf
In this episode of ScienceTalks, Snorkel AI’s Braden Hancock Hugging Face’s Chief Science Officer, Thomas Wolf. Thomas shares his story about how he got into machine learning and discusses important design decisions behind the widely adopted Transformers library, as well as the challenges of bringing research projects into production. ScienceTalks is an interview series from Snorkel AI, highlighting some of the best work and ideas to make AI practical.
February 5, 2021
Team Snorkel
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How To Overcome Practical Challenges for AI in the Public Sector
AI is already transforming the business of government. But the positive impacts of this transformation, from increasing the efficiency of public services to enhancing the effectiveness of tax dollars, are still in the earliest stages. Public sector organizations generally have access to the same talent, software models, and hardware infrastructure as any private sector company, but they face a number of relatively unique practical challenges that hinder their operationalization of AI.
January 7, 2021
Charlie Greenbacker
How To Overcome Practical Challenges for AI in Finance
Advancements in artificial intelligence promise efficiency gains for financial institutions. AI-powered applications can revolutionize an organization’s risk management, fraud detection, compliance monitoring, and other processes. Financial services companies have smart data scientists and good infrastructure needed for deploying AI. But their ability to rapidly develop and deploy AI applications is hampered by several unique challenges.
December 29, 2020
Manas Joglekar
Machine Learning Production Myths
Takeaways from MLSys Seminars with Chip HuyenIn November, I had the opportunity to come back to Stanford to participate in MLSys Seminars, a series about Machine Learning Systems. It was great to see the growing interest of the academic community in building practical AI applications. Here is a recording of the talk.The talk was originally about the principles of good
December 23, 2020
Chip Huyen
Meet a Snorkeler at an Upcoming Event
We love meeting people in the data science and machine learning community. Here are a few upcoming events where you can meet Snorkelers.
November 17, 2020
Team Snorkel