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Applying Responsible NLP in Real-World Projects

John Snow Labs

Responsible AI: Getting from Goals to Daily Practices How is it possible to develop AI models that are transparent, safe, and equitable? As AI impacts more aspects of our daily lives, concerns about discrimination, privacy, and bias are on the rise.

NLP 52
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? Guest Post: How to build a responsible code LLM with crowdsourcing*

TheSequence

This successful implementation demonstrates how responsible AI and high-performing models can align. Responsible AI starts with a responsible approach to data The promise of Large Language Models (LLMs) is that they will help us with a variety of different tasks.

LLM 52
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NLP Summit Insights: How LLMs Are Shaping the Future of Modern Business

John Snow Labs

In my experience, models like GPT-3 and BERT have consistently excelled in diverse areas, from generating text to evaluating sentiments” adds Dr. Fatema Nafa, Assistant Professor, Computer Science Department at Salem State University. Swagata Ashwani, Data Science Lead at Boomi, adds, “Domain-specific knowledge is pivotal.

NLP 52
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Will You Find These Shortcuts?

Google Research AI blog

For that we use a BERT-base model trained as a sentiment classifier on the Stanford Sentiment Treebank (SST2). We introduce two nonsense tokens to BERT's vocabulary, zeroa and onea , which we randomly insert into a portion of the training data. Input Salience Method Precision Gradient L2 1.00 Gradient x Input 0.31

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Google’s Dr. Arsanjani on Enterprise Foundation Model Challenges

Snorkel AI

It came to its own with the creation of the transformer architecture: Google’s BERT, OpenAI, GPT2 and then 3, LaMDA for conversation, Mina and Sparrow from Google DeepMind. So the application started to go from the pure software-engineering/machine-learning domain to industry and the sciences, essentially.

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Google’s Arsanjani on Enterprise Foundation Model Challenges

Snorkel AI

It came to its own with the creation of the transformer architecture: Google’s BERT, OpenAI, GPT2 and then 3, LaMDA for conversation, Mina and Sparrow from Google DeepMind. So the application started to go from the pure software-engineering/machine-learning domain to industry and the sciences, essentially.