AWS Machine Learning Blog

FEBRUARY 14, 2024

It enables you to privately customize the FMs with your data using techniques such as fine-tuning, prompt engineering, and Retrieval Augmented Generation (RAG), and build agents that run tasks using your enterprise systems and data sources while complying with security and privacy requirements.

Prompt Engineer 140

Prompt Engineer Prompt Engineering Generative AI Chatbots 140

Marktechpost

JULY 4, 2023

What is prompt engineering? For developing any GPT-3 application, it is important to have a proper training prompt along with its design and content. Prompt is the text fed to the Large Language Model. Prompt engineering involves designing a prompt for a satisfactory response from the model.

Prompt Engineer 113

Prompt Engineer Prompt Engineering Artificial Intelligence Artificial Intelligence 113

AWS Machine Learning Blog

NOVEMBER 15, 2023

Prompt engineering has become an essential skill for anyone working with large language models (LLMs) to generate high-quality and relevant texts. Although text prompt engineering has been widely discussed, visual prompt engineering is an emerging field that requires attention.

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Prompt Engineer Prompt Engineering Computer Vision Machine Learning 115

AWS Machine Learning Blog

NOVEMBER 29, 2024

Prompt engineering refers to the practice of writing instructions to get the desired responses from foundation models (FMs). You might have to spend months experimenting and iterating on your prompts, following the best practices for each model, to achieve your desired output.

Generative AI 133

Generative AI Prompt Engineer Prompt Engineering Data Scientist 133

Marktechpost

AUGUST 11, 2024

However, the true potential of these LLMs is realized through effective prompt engineering. One of the main challenges in prompt engineering is the significant expertise and time required to design effective prompts. Most existing methods assume access to labeled data, a significant limitation for many users.

Prompt Engineer 117

Prompt Engineer Prompt Engineering Natural Language Processing Large Language Models 117

Unite.AI

AUGUST 30, 2024

OctoAI was spun out of the University of Washington by the original creators of Apache TVM, an open source stack for ML portability and performance. TVM enables ML models to run efficiently on any hardware backend, and has quickly become a key part of the architecture of popular consumer devices like Amazon Alexa.

ML 162

ML Prompt Engineer Prompt Engineering Generative AI 162

Flipboard

MARCH 4, 2025

Customizable Uses prompt engineering , which enables customization and iterative refinement of the prompts used to drive the large language model (LLM), allowing for refining and continuous enhancement of the assessment process. The quality of prompt (the system prompt, in this case) has significant impact on the model output.

Generative AI 156

Generative AI Prompt Engineer Prompt Engineering AI 156

Marktechpost

MARCH 4, 2024

The system iteratively refines prompts, akin to curriculum learning, generating challenging cases to align with user intent efficiently. In conclusion, the IPC system automates prompt engineering by combining synthetic data generation and prompt optimization modules, iteratively refining prompts using prompting LLMs until convergence.

Prompt Engineer 103

Prompt Engineer Prompt Engineering Automation LLM 103

Marktechpost

JANUARY 1, 2025

Foundations of Prompt Engineering Offered by AWS, this course delves into crafting effective prompts for AI agents, ensuring optimal performance and accuracy. Also, dont forget to join our 60k+ ML SubReddit. It covers frameworks, coordination strategies, and real-world applications.

Prompt Engineering 102

Prompt Engineering Prompt Engineer Large Language Models LLM 102

Marktechpost

MARCH 26, 2024

Don’t Forget to join our 39k+ ML SubReddit The post Exploration of How Large Language Models Navigate Decision Making with Strategic Prompt Engineering and Summarization appeared first on MarkTechPost. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup. If you like our work, you will love our newsletter.

Large Language Models 103

Large Language Models Prompt Engineer Prompt Engineering Algorithm 103

Marktechpost

DECEMBER 7, 2023

These findings build on earlier research that suggests activation probing can generalize out-of-distribution when prompted. Also, don’t forget to join our 33k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and Email Newsletter , where we share the latest AI research news, cool AI projects, and more.

Large Language Models 120

Large Language Models Prompt Engineer Prompt Engineering Neural Network 120

Towards AI

AUGUST 23, 2024

Model Development <> Prompt Engineering Machine learning app development typically involves two main obstacles: acquiring a dataset and training a model on it. Interestingly, developing zero/few-shot applications follows a similar path: gathering a high-quality dataset and using it to find a fitting prompt.

LLM 98

LLM ML Prompt Engineer Prompt Engineering 98

AWS Machine Learning Blog

JANUARY 22, 2025

Customizing an FM that is specialized on a specific task is often done using one of the following approaches: Prompt engineering Add instructions in the context/input window of the model to help it complete the task successfully. For our specific task, weve found prompt engineering sufficient to achieve the results we needed.

Prompt Engineer 111

Prompt Engineer Prompt Engineering Natural Language Processing Machine Learning 111

Marktechpost

NOVEMBER 19, 2024

Current LLM-based methods for anomaly detection include prompt engineering, which uses LLMs in zero/few-shot setups, and fine-tuning, which adapts models to specific datasets. Don’t Forget to join our 55k+ ML SubReddit. Researchers from SJTU, Shanghai, developed LogLLM, a log-based anomaly detection framework utilizing LLMs.

Large Language Models 80

Large Language Models BERT Prompt Engineering Prompt Engineer 80

Marktechpost

FEBRUARY 16, 2025

SOLOMON leverages prompt engineering techniques to guide LLM-generated solutions, allowing it to adapt to semiconductor layout tasks with minimal retraining. Also,feel free to follow us on Twitter and dont forget to join our 75k+ ML SubReddit. Check out the Paper.

LLM 94

LLM Large Language Models Prompt Engineer Prompt Engineering 94

AI News

SEPTEMBER 27, 2024

.” Mosaic AI offers several key components, which Everts outlines: Unified tooling: Provides “tools for building, deploying, evaluating, and governing AI and ML solutions, supporting predictive models and generative AI applications.”

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Large Language Models Big Data Explainability ETL 298

AWS Machine Learning Blog

JANUARY 22, 2025

These services use advanced machine learning (ML) algorithms and computer vision techniques to perform functions like object detection and tracking, activity recognition, and text and audio recognition. The key to the capability of the solution is the prompts we have engineered to instruct Anthropics Claude what to do.

Generative AI 111

Generative AI Prompt Engineer Prompt Engineering AI 111

AWS Machine Learning Blog

NOVEMBER 15, 2024

To help with fairness in AI applications that are built on top of Amazon Bedrock, application developers should explore model evaluation and human-in-the-loop validation for model outputs at different stages of the machine learning (ML) lifecycle.

Responsible AI 111

Responsible AI Prompt Engineer Prompt Engineering AI 111

AWS Machine Learning Blog

FEBRUARY 5, 2025

This includes retrieval of required data for analysis, analysis of the data using insights from other custom-built machine learning (ML) models, and risk scoring. The response limitations enforced through proprietary prompt engineering and reference data constrain the response space, limiting hallucinations and inaccuracies in the response.

Prompt Engineer 110

Prompt Engineer Prompt Engineering Generative AI Automation 110

Marktechpost

MARCH 5, 2025

A task-specific LLM enhances predictions through prompt engineering and RAG. Prompting includes zero-shot or few-shot learning with chain-of-thought reasoning, while RAG retrieves relevant knowledge via semantic embeddings and HNSW indexing. Also,feel free to follow us on Twitter and dont forget to join our 80k+ ML SubReddit.

Large Language Models 79

Large Language Models LLM Machine Learning Prompt Engineer 79

Towards AI

MAY 1, 2023

TheSequence is a no-BS (meaning no hype, no news etc) ML-oriented newsletter that takes 5 minutes to read. Created Using Midjourney I recently started an AI-focused educational newsletter, that already has over 150,000 subscribers. The goal is to keep you up to date with machine learning projects, research papers and concepts.

Prompt Engineering 98

Prompt Engineering Prompt Engineer LLM Large Language Models 98

AWS Machine Learning Blog

MARCH 12, 2025

Compelling AI-generated images start with well-crafted prompts. In this follow-up to our Amazon Nova Canvas Prompt Engineering Guide , we showcase a curated gallery of visuals generated by Nova Canvascategorized by real-world use casesfrom marketing and product visualization to concept art and design exploration.

Prompt Engineer 101

Prompt Engineer Prompt Engineering Generative AI Software Engineer 101

AWS Machine Learning Blog

JANUARY 28, 2025

By documenting the specific model versions, fine-tuning parameters, and prompt engineering techniques employed, teams can better understand the factors contributing to their AI systems performance. SageMaker is a data, analytics, and AI/ML platform, which we will use in conjunction with FMEval to streamline the evaluation process.

LLM 113

LLM Large Language Models ML Algorithm 113

Marktechpost

MAY 26, 2024

Machine Learning Terminology and Process This course introduces basic machine learning concepts and details each step of the ML process. It covers common terms and techniques used in ML projects, aiming to help you understand and discuss the entire ML process comprehensively.

Data Scientist 130

Data Scientist Prompt Engineering Prompt Engineer Machine Learning 130

AWS Machine Learning Blog

JANUARY 4, 2024

Specifically, we discuss the following: Why do we need Text2SQL Key components for Text to SQL Prompt engineering considerations for natural language or Text to SQL Optimizations and best practices Architecture patterns Why do we need Text2SQL? Effective prompt engineering is key to developing natural language to SQL systems.

Prompt Engineer 139

Prompt Engineer Prompt Engineering Generative AI LLM 139

AWS Machine Learning Blog

APRIL 20, 2023

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. Based on Inference Recommender’s instance type recommendations, we can find the right real-time serving ML instances that yield the right price-performance for this use case.

ML 101

ML Auto-classification Python Auto-complete 101

AWS Machine Learning Blog

NOVEMBER 1, 2024

Fine-tuning Anthropic’s Claude 3 Haiku has demonstrated superior performance compared to few-shot prompt engineering on base Anthropic’s Claude 3 Haiku, Anthropic’s Claude 3 Sonnet, and Anthropic’s Claude 3.5 Yanyan graduated from Texas A&M University with a PhD in Electrical Engineering. Sonnet across various tasks.

LLM 97

LLM Prompt Engineer Prompt Engineering Generative AI 97

Marktechpost

JUNE 19, 2024

It covers how generative AI works, its applications, and its limitations, with hands-on exercises for practical use and effective prompt engineering. Introduction to Generative AI This beginner-friendly course provides a solid foundation in generative AI, covering concepts, effective prompting, and major models.

Artificial Intelligence 124

Artificial Intelligence Artificial Intelligence Prompt Engineer Prompt Engineering 124

AWS Machine Learning Blog

NOVEMBER 12, 2024

In this blog post, we demonstrate prompt engineering techniques to generate accurate and relevant analysis of tabular data using industry-specific language. This is done by providing large language models (LLMs) in-context sample data with features and labels in the prompt. For certain use cases, fine-tuning may be required.

ESG 116

ESG Generative AI LLM Prompt Engineer 116

AWS Machine Learning Blog

DECEMBER 23, 2024

Results are then used to augment the prompt and generate a more accurate response compared to standard vector-based RAG. Implementing such process requires teams to develop specific skills in topics such as graph modeling, graph queries, prompt engineering, or LLM workflow maintenance.

Generative AI 130

Generative AI Natural Language Processing Prompt Engineer Prompt Engineering 130

AWS Machine Learning Blog

NOVEMBER 14, 2024

It enables you to privately customize the FM of your choice with your data using techniques such as fine-tuning, prompt engineering, and retrieval augmented generation (RAG) and build agents that run tasks using your enterprise systems and data sources while adhering to security and privacy requirements.

LLM 111

LLM Generative AI Prompt Engineer Prompt Engineering 111

AWS Machine Learning Blog

NOVEMBER 7, 2024

SageMaker JumpStart is a machine learning (ML) hub that provides a wide range of publicly available and proprietary FMs from providers such as AI21 Labs, Cohere, Hugging Face, Meta, and Stability AI, which you can deploy to SageMaker endpoints in your own AWS account. It’s serverless so you don’t have to manage the infrastructure.

Generative AI 113

Generative AI Machine Learning AI AI 113

AWS Machine Learning Blog

MAY 13, 2024

In this part of the blog series, we review techniques of prompt engineering and Retrieval Augmented Generation (RAG) that can be employed to accomplish the task of clinical report summarization by using Amazon Bedrock. It can be achieved through the use of proper guided prompts. There are many prompt engineering techniques.

Generative AI 135

Generative AI Prompt Engineering Prompt Engineer LLM 135

AWS Machine Learning Blog

MAY 7, 2024

SageMaker JumpStart is a machine learning (ML) hub with foundation models (FMs), built-in algorithms, and prebuilt ML solutions that you can deploy with just a few clicks. This post walks through examples of building information extraction use cases by combining LLMs with prompt engineering and frameworks such as LangChain.

Prompt Engineer 123

Prompt Engineer Prompt Engineering Large Language Models LLM 123

ODSC - Open Data Science

MARCH 13, 2025

Just Do Something with AI: Bridging the Business Communication Gap forML This blog explores how ML practitioners can navigate AI business communication, ensuring AI initiatives align with real businessvalue.

Data Science 52

Data Science Prompt Engineer Prompt Engineering ML 52

IBM Journey to AI blog

JANUARY 15, 2024

As such, organizations are increasingly interested in seeing how they can apply the whole suite of artificial intelligence (AI) and machine learning (ML) technologies to improve their business processes. For example, applied ML will help organizations that depend on the supply chain engage in better decision making, in real time.

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Machine Learning Automation DevOps Artificial Intelligence 219

Marktechpost

JUNE 15, 2024

On the other hand, synthetic data generation methods involve using LLMs to produce instructions based on initial seed questions and prompt engineering. This method involves prompting the LLM with only predefined templates, allowing the model to create user queries and their corresponding responses autonomously.

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Prompt Engineering Prompt Engineer Auto-complete Large Language Models 134