Unite.AI

AUGUST 1, 2023

The spotlight is also on DALL-E, an AI model that crafts images from textual inputs. One such model that has garnered considerable attention is OpenAI's ChatGPT , a shining exemplar in the realm of Large Language Models. Our exploration into prompt engineering techniques aims to improve these aspects of LLMs.

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Prompt Engineer Prompt Engineering ChatGPT Convolutional Neural Networks 246

ODSC - Open Data Science

AUGUST 24, 2023

Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI Practices Editor’s note: Jayachandran Ramachandran and Rohit Sroch are speakers for ODSC APAC this August 22–23. Auto Eval Common Metric Eval Human Eval Custom Model Eval 3.

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Large Language Models Prompt Engineer Prompt Engineering Responsible AI 52

Unite.AI

AUGUST 28, 2023

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. Transformers and Advanced NLP Models : The introduction of transformer architectures revolutionized the NLP landscape.

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Auto-complete ChatGPT Large Language Models AI 240

Unite.AI

SEPTEMBER 4, 2023

Large Language Models (LLMs) capable of complex reasoning tasks have shown promise in specialized domains like programming and creative writing. Developed by Meta with its partnership with Microsoft, this open-source large language model aims to redefine the realms of generative AI and natural language understanding.

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ChatGPT Auto-complete Large Language Models LLM 290

Unite.AI

SEPTEMBER 11, 2023

With Large Language Models (LLMs) like ChatGPT, OpenAI has witnessed a surge in enterprise and user adoption, currently raking in around $80 million in monthly revenue. Last time we delved into AutoGPT and GPT-Engineering , the early mainstream open-source LLM-based AI agents designed to automate complex tasks.

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Python OpenAI Software Development Software Engineer 328

AWS Machine Learning Blog

DECEMBER 5, 2023

Customers can create the custom metadata using Amazon Comprehend , a natural-language processing (NLP) service managed by AWS to extract insights about the content of documents, and ingest it into Amazon Kendra along with their data into the index. For example, metadata can be used for filtering and searching. append(e["Text"].upper())

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Metadata Auto-classification Auto-complete Content Enrichment 93

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? Billions of parameters.

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Large Language Models Prompt Engineer Prompt Engineering Neural Network 52