Unite.AI

SEPTEMBER 11, 2023

Last time we delved into AutoGPT and GPT-Engineering , the early mainstream open-source LLM-based AI agents designed to automate complex tasks. Enter MetaGPT — a Multi-agent system that utilizes Large Language models by Sirui Hong fuses Standardized Operating Procedures (SOPs) with LLM-based multi-agent systems.

Python 328

Python Software Development OpenAI Software Engineer 328

Marktechpost

JUNE 15, 2024

This limitation hinders the advancement of LLM capabilities and their application in diverse, real-world scenarios. Existing methods for generating instruction datasets fall into two categories: human-curated data and synthetic data produced by LLMs. The model then generates diverse user queries based on these templates.

Prompt Engineering 134

Prompt Engineering Prompt Engineer Auto-complete Large Language Models 134

Marktechpost

APRIL 16, 2024

LangChain is an open-source framework that allows developers to build LLM-based applications easily. It provides for easily connecting LLMs with external data sources to augment the capabilities of these models and achieve better results. It teaches how to build LLM-powered applications using LangChain using hands-on exercises.

Large Language Models 104

Large Language Models Auto-complete Prompt Engineering Prompt Engineer 104

Flipboard

JUNE 13, 2023

Redfin Photo) “We’ve already found a number of places where AI tools are making our engineers more efficient. The auto-complete and auto-suggestions in Visual Studio Code are pretty good, too, without being annoying. ” We’ve also found ways to use these tools to help us serve customers more efficiently.

Generative AI 181

Generative AI Auto-complete Software Engineer AI 181

Marktechpost

OCTOBER 1, 2024

Here are ten proven strategies to reduce LLM inference costs while maintaining performance and accuracy: Quantization Quantization is a technique that decreases the precision of model weights and activations, resulting in a more compact representation of the neural network.

Large Language Models 70

Large Language Models LLM Prompt Engineering Prompt Engineer 70

AWS Machine Learning Blog

MAY 17, 2024

A prompt is the information you pass into an LLM to elicit a response. The process of designing and refining prompts to get specific responses from these models is called prompt engineering. With prompt chaining, you construct a set of smaller subtasks as individual prompts.

Generative AI 137

Generative AI LLM Prompt Engineer Prompt Engineering 137

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. Various prompting techniques, such as Zero/Few Shot, Chain-of-Thought (CoT)/Self-Consistency, ReAct, etc.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models Responsible AI 52

The MLOps Blog

SEPTEMBER 26, 2024

TL;DR Hallucinations are an inherent feature of LLMs that becomes a bug in LLM-based applications. Effective mitigation strategies involve enhancing data quality, alignment, information retrieval methods, and prompt engineering. What are LLM hallucinations? In 2022, when GPT-3.5

LLM 72

LLM Prompt Engineer Prompt Engineering Auto-complete 72

AWS Machine Learning Blog

AUGUST 22, 2024

The following figure shows the Discovery Navigator generative AI auto-summary pipeline. Verisk’s evaluation involved three major parts: Prompt engineering – Prompt engineering is the process where you guide generative AI solutions to generate desired output.

Generative AI 115

Generative AI Auto-complete Software Development Automation 115

AWS Machine Learning Blog

JUNE 20, 2024

It allows LLMs to reference authoritative knowledge bases or internal repositories before generating responses, producing output tailored to specific domains or contexts while providing relevance, accuracy, and efficiency. Generation is the process of generating the final response from the LLM.

Auto-classification 135

Auto-classification LLM Prompt Engineer Prompt Engineering 135

AWS Machine Learning Blog

NOVEMBER 1, 2023

Combined with large language models (LLM) and Contrastive Language-Image Pre-Training (CLIP) trained with a large quantity of multimodality data, visual language models (VLMs) are particularly adept at tasks like image captioning, object detection and segmentation, and visual question answering.

Auto-classification 121

Auto-classification LLM Auto-complete Generative AI 121

AWS Machine Learning Blog

DECEMBER 5, 2023

The insurance provider receives payout claims from the beneficiary’s attorney for different insurance types, such as home, auto, and life insurance. When this is complete, the document can be routed to the appropriate department or downstream process. The following diagram outlines the proposed solution architecture. append(e["Text"].upper())

Metadata 125

Metadata Auto-classification Auto-complete Content Enrichment 125

AWS Machine Learning Blog

SEPTEMBER 14, 2023

To improve the quality of output, approaches like n-short learning, Prompt engineering, Retrieval Augmented Generation (RAG) and fine tuning are used. In addition to QLoRA, bitsanbytes is used to convert to 4-bit precision to quantize frozen LLM to 4-bit and attach LoRA adapters on it.

Python 129

Python Machine Learning Auto-complete Data Science 129

Marktechpost

MARCH 6, 2025

Whether you’re interfacing with models remotely or running them locally, understanding key techniques like prompt engineering and output structuring can substantially improve performance for your specific applications. These services handle the complex computational requirements, allowing developers to focus on implementation.

Large Language Models 54

Large Language Models Auto-complete Prompt Engineer Prompt Engineering 54

The MLOps Blog

MARCH 12, 2024

TL;DR LLMOps involves managing the entire lifecycle of Large Language Models (LLMs), including data and prompt management, model fine-tuning and evaluation, pipeline orchestration, and LLM deployment. Prompt-response management: Refining LLM-backed applications through continuous prompt-response optimization and quality control.

Prompt Engineering 52

Prompt Engineering Prompt Engineer Large Language Models LLM 52

AWS Machine Learning Blog

APRIL 16, 2024

To store information in Secrets Manager, complete the following steps: On the Secrets Manager console, choose Store a new secret. Complete the following steps: On the Secrets Manager console, choose Store a new secret. This adaptation is facilitated through the use of LLM prompts.

Data Scientist 120

Data Scientist Generative AI Machine Learning ML 120

Snorkel AI

JUNE 7, 2023

Foundation models, Alex said, yield results that are “nothing short of breathtaking,” but they’re not a complete answer for enterprises who aim to solve challenges using machine learning. “We We are, in our view, in a bit of a hype cycle,” he said.

Data Scientist 52

Data Scientist Large Language Models Machine Learning Data Science 52

Snorkel AI

JUNE 7, 2023

Foundation models, Alex said, yield results that are “nothing short of breathtaking,” but they’re not a complete answer for enterprises who aim to solve challenges using machine learning. “We We are, in our view, in a bit of a hype cycle,” he said.

Data Scientist 52

Data Scientist Large Language Models Machine Learning Data Science 52

The MLOps Blog

JUNE 27, 2023

The platform also offers features for hyperparameter optimization, automating model training workflows, model management, prompt engineering, and no-code ML app development. Can you see the complete model lineage with data/models/experiments used downstream? Is it fast and reliable enough for your workflow?

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. Others, toward language completion and further downstream tasks.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. Others, toward language completion and further downstream tasks.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Topbots

JUNE 29, 2023

On a more advanced stance, everyone who has done SQL query optimisation will know that many roads lead to the same result, and semantically equivalent queries might have completely different syntax. 3] provides a more complete survey of Text2SQL data augmentation techniques.

Algorithm 52

Algorithm Auto-complete Data Scientist Auto-classification 52

AWS Machine Learning Blog

FEBRUARY 3, 2025

Not only are large language models (LLMs) capable of answering a users question based on the transcript of the file, they are also capable of identifying the timestamp (or timestamps) of the transcript during which the answer was discussed. Each citation can point to a different video, or to different timestamps within the same video.

UX Design 100

UX Design Auto-complete LLM Prompt Engineer 100

AWS Machine Learning Blog

DECEMBER 11, 2024

Two open-source libraries, Ragas (a library for RAG evaluation) and Auto-Instruct, used Amazon Bedrock to power a framework that evaluates and improves upon RAG. Generating improved instructions for each question-and-answer pair using an automatic prompt engineering technique based on the Auto-Instruct Repository.

Generative AI 76

Generative AI Chatbots Prompt Engineering Prompt Engineer 76