Unite.AI

JANUARY 11, 2024

They serve as a core building block in many natural language processing (NLP) applications today, including information retrieval, question answering, semantic search and more. Model Training: Fine-tune a powerful open-source LLM such as Mistral on the synthetic data using contrastive loss.

Large Language Models 147

Large Language Models Prompt Engineer Prompt Engineering BERT 147

Explosion

MAY 17, 2023

A lot of people are building truly new things with Large Language Models (LLMs), like wild interactive fiction experiences that weren’t possible before. But if you’re working on the same sort of Natural Language Processing (NLP) problems that businesses have been trying to solve for a long time, what’s the best way to use them?

LLM 135

LLM NLP Large Language Models OpenAI 135

AWS Machine Learning Blog

MARCH 13, 2024

The LLM analysis provides a violation result (Y or N) and explains the rationale behind the model’s decision regarding policy violation. The audio moderation workflow activates the LLM’s policy evaluation only when the toxicity analysis exceeds a set threshold. The LLM model returns an analysis result based on the prompt instructions.

LLM 112

LLM Natural Language Processing Prompt Engineer Prompt Engineering 112

Unite.AI

AUGUST 4, 2023

This, coupled with the challenges of understanding AI concepts and complex algorithms, contributes to the learning curve associated with developing applications using LLMs. Nevertheless, the integration of LLMs with other tools to form LLM-powered applications could redefine our digital landscape.

Prompt Engineer 245

Prompt Engineer Prompt Engineering Python NLP 245

AWS Machine Learning Blog

OCTOBER 24, 2023

You can use LLMs in one or all phases of IDP depending on the use case and desired outcome. In this architecture, LLMs are used to perform specific tasks within the IDP workflow. Document classification – In addition to using Amazon Comprehend , you can use an LLM to classify documents using few-shot prompting.

IDP 118

IDP LLM Prompt Engineer Prompt Engineering 118

AWS Machine Learning Blog

SEPTEMBER 14, 2023

Amazon Comprehend is a natural-language processing (NLP) service that uses machine learning to uncover valuable insights and connections in text. Knowledge management – Categorizing documents in a systematic way helps to organize an organization’s knowledge base. This allows for better monitoring and auditing.

Categorization 100

Categorization Machine Learning Data Scientist Natural Language Processing 100

Snorkel AI

MAY 25, 2023

in the linked article) in a process that results not only in a set of valuable weights for the model, but also an embedding for each word fed to it. At inference time, users provide “prompts” to the LLM—snippets of text that the model uses as a jumping-off point. A week later, Google introduced Bard, its own LLM-backed chatbot.

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

Snorkel AI

MAY 25, 2023

in the linked article) in a process that results not only in a set of valuable weights for the model, but also an embedding for each word fed to it. At inference time, users provide “prompts” to the LLM—snippets of text that the model uses as a jumping-off point. A week later, Google introduced Bard, its own LLM-backed chatbot.

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

AWS Machine Learning Blog

DECEMBER 5, 2023

The custom metadata helps organizations and enterprises categorize information in their preferred way. His focus area is AI/ML, and he helps customers with generative AI, large language models, and prompt engineering. Recently, her focus has been on exploring the potential of Generative AI and LLM.

Metadata 103

Metadata Auto-classification Auto-complete Content Enrichment 103

Unite.AI

SEPTEMBER 20, 2023

How Hugging Face Facilitates NLP and LLM Projects Hugging Face has made working with LLMs simpler by offering: A range of pre-trained models to choose from. A great resource available through Hugging Face is the Open LLM Leaderboard. Tools and examples to fine-tune these models to your specific needs.

LLM 342

LLM BERT NLP Python 342

deepsense.ai

NOVEMBER 14, 2023

In short, EDS is the problem of the widespread lack of a rational approach to and methodology for the objective, automated and quantitative evaluation of performance in terms of generative model finetuning and prompt engineering for specific downstream GenAI tasks related to practical business applications. There is a ‘but’, however.

Generative AI 100

Generative AI ML Prompt Engineer Prompt Engineering 100

Unite.AI

AUGUST 8, 2023

Processing these numbers through a latent vector gives birth to art that mirrors the complexities of human aesthetics. Generative AI Types: Text to Text, Text to Image Transformers & LLM The paper “ Attention Is All You Need ” by Google Brain marked a shift in the way we think about text modeling. Supports 13 programming languages.

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243

AWS Machine Learning Blog

NOVEMBER 1, 2023

Visual language processing (VLP) is at the forefront of generative AI, driving advancements in multimodal learning that encompasses language intelligence, vision understanding, and processing. Central to the architecture are the fine-tuned VLM and LLM, both instrumental in decoding visual and textual data streams.

Auto-classification 97

Auto-classification LLM Auto-complete Generative AI 97

Flipboard

DECEMBER 6, 2023

Tools like LangChain , combined with a large language model (LLM) powered by Amazon Bedrock or Amazon SageMaker JumpStart , simplify the implementation process. Types of summarizations There are several techniques to summarize text, which are broadly categorized into two main approaches: extractive and abstractive summarization.

BERT 128

BERT Large Language Models Artificial Intelligence Artificial Intelligence 128