AssemblyAI

MAY 23, 2023

With these complex algorithms often labeled as "giant black boxes" in media, there's a growing need for accurate and easy-to-understand resources, especially for Product Managers wondering how to incorporate AI into their product roadmap. Capabilities and Prompting Scaling language models leads to unexpected results.

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Large Language Models Neural Network LLM Chatbots 130

John Snow Labs

NOVEMBER 6, 2023

By providing an organized framework for logging and versioning, MLFlow Tracking helps teams ensure their models are developed and deployed with transparency and precision. On the other hand, LangTest has emerged as a transformative force in the realm of Natural Language Processing (NLP) and Large Language Model (LLM) evaluation.

ML 52

ML Natural Language Processing BERT Large Language Models 52

AWS Machine Learning Blog

NOVEMBER 30, 2023

You can directly use the FMEval wherever you run your workloads, as a Python package or via the open-source code repository, which is made available in GitHub for transparency and as a contribution to the Responsible AI community. FMEval allows you to upload your own prompt datasets and algorithms.

Large Language Models 88

Large Language Models LLM Algorithm Responsible AI 88

TheSequence

MAY 29, 2023

They address PII risks by training a PII reduction model through crowdsourcing, employing strategies like task decomposition, clear instructions, and quality control. This successful implementation demonstrates how responsible AI and high-performing models can align.

LLM 52

LLM Responsible AI Natural Language Processing Software Engineer 52

Heartbeat

OCTOBER 12, 2023

Large language models have been game-changers in artificial intelligence, but the world is much more than just text. These language models are breaking boundaries, venturing into a new era of AI — Multi-Modal Learning. However, the influence of large language models extends beyond text alone.

Large Language Models 59

Large Language Models Neural Network Artificial Intelligence Artificial Intelligence 59

Google Research AI blog

FEBRUARY 7, 2023

This led to significant computational savings while giving competitive results on auto-regressive language modeling and open domain question answering tasks. However, pre-trained large language models (LLMs) consume a significant amount of information through self-supervision on big training sets.

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Deep Learning Algorithm Neural Network ML 118

ODSC - Open Data Science

JANUARY 29, 2024

Think of them as architects of language-driven AI. They design intricate sequences of prompts, leveraging their knowledge of AI, machine learning, and data science to guide powerful LLMs (Large Language Models) towards complex tasks. series (Davinci, etc), GPT-4, and GPT-4 Turbo are immensely popular.

Prompt Engineer 52

Prompt Engineer Prompt Engineering LLM Data Science 52

John Snow Labs

NOVEMBER 8, 2023

Introduction Natural Language Processing (NLP) and Large Language Models (LLMs) in particular have evolved to enable new levels of comprehending and generating human language. Nonetheless, LLM & NLP models are not immune to biases, often reflecting the biases present in the data used for their training.

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BERT Natural Language Processing NLP Large Language Models 52

Snorkel AI

MARCH 2, 2023

Today we’re going to be talking essentially about how responsible generative-AI-model adoption can happen at the enterprise level, and what are some of the promises and compromises we face. The foundation of large language models started quite some time ago. What are the promises?

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

Today we’re going to be talking essentially about how responsible generative-AI-model adoption can happen at the enterprise level, and what are some of the promises and compromises we face. The foundation of large language models started quite some time ago. What are the promises?

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 19, 2024

Read on to see how Google and Snorkel AI customized PaLM 2 using domain expertise and data development to improve performance by 38 F1 points in a matter of hours. In the landscape of modern enterprise applications, large language models (LLMs) like Google Gemini and PaLM 2 stand at the forefront of transformative technologies.

Data Scientist 52

Data Scientist AI AI LLM 52

Snorkel AI

MARCH 19, 2024

Read on to see how Google and Snorkel AI customized PaLM 2 using domain expertise and data development to improve performance by 38 F1 points in a matter of hours. In the landscape of modern enterprise applications, large language models (LLMs) like Google Gemini and PaLM 2 stand at the forefront of transformative technologies.

Data Scientist 52

Data Scientist AI AI LLM 52

AWS Machine Learning Blog

AUGUST 11, 2023

Large language models (LLMs) are transformer-based models trained on a large amount of unlabeled text with hundreds of millions ( BERT ) to over a trillion parameters ( MiCS ), and whose size makes single-GPU training impractical.

Natural Language Processing 75

Natural Language Processing NLP Python Machine Learning 75

Google Research AI blog

FEBRUARY 10, 2023

While we have trained BERT and transformers with DP, understanding training example memorization in large language models (LLMs) is a heuristic way to evaluate their privacy. In particular, we investigated when and why LLMs forget (potentially memorized) training examples during training.

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Algorithm Neural Network Auto-classification ML 110

Sebastian Ruder

NOVEMBER 14, 2022

Models that allow interaction via natural language have become ubiquitious. Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. When is BERT Multilingual? Goyal, N.,

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics AI 52

Google Research AI blog

FEBRUARY 2, 2023

TensorStore is particularly useful for training large language models (LLMs) with multi-controller runtimes, where every process only manages a subset of all parameters, all of which must be collated into a consistent checkpoint. (See paper for details.)

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ML Neural Network Algorithm Automation 72