Flipboard

MARCH 31, 2025

It simplifies the creation and management of AI automations using either AI flows, multi-agent systems, or a combination of both, enabling agents to work together seamlessly, tackling complex tasks through collaborative intelligence. At a high level, CrewAI creates two main ways to create agentic automations: flows and crews.

LLM 177

LLM Automation Generative AI AI Automation 177

Towards AI

JUNE 9, 2024

Hands-On Prompt Engineering for LLMs Application Development Once such a system is built, how can you assess its performance? In this article, we will explore and share best practices for evaluating LLM outputs and provide insights into the experience of building these systems. Automating Evaluation Metrics1.3.

Prompt Engineering 103

Prompt Engineering Prompt Engineer LLM Machine Learning 103

Towards AI

MAY 6, 2024

Validating Output from Instruction-Tuned LLMs Checking outputs before showing them to users can be important for ensuring the quality, relevance, and safety of the responses provided to them or used in automation flows.

Prompt Engineering 96

Prompt Engineering Prompt Engineer LLM OpenAI 96

Marktechpost

MARCH 4, 2024

Despite advancements, prompt sensitivity remains a hurdle, especially in proprietary models where version changes can alter behavior significantly. Balancing prompt optimization with practical constraints is essential for real-world LLM applications. Estimators support various tasks like human annotation and LLM estimation.

Prompt Engineering 103

Prompt Engineering Prompt Engineer LLM Automation 103

AWS Machine Learning Blog

FEBRUARY 12, 2025

The evaluation of large language model (LLM) performance, particularly in response to a variety of prompts, is crucial for organizations aiming to harness the full potential of this rapidly evolving technology. Both features use the LLM-as-a-judge technique behind the scenes but evaluate different things.

LLM 89

LLM Generative AI Automation Machine Learning 89

AI News

NOVEMBER 15, 2023

It teaches the LLM to recognise the kinds of things that Wolfram|Alpha might know – our knowledge engine,” McLoone explains. Where I see it, [approaches to AI] all share something in common, which is all about using the machinery of computation to automate knowledge,” says McLoone. Our approach on that is completely different.

Generative AI 337

Generative AI LLM Big Data Explainability 337

AWS Machine Learning Blog

JANUARY 7, 2025

One of LLMs most fascinating strengths is their inherent ability to understand context. Localization relies on both automation and humans-in-the-loop in a process called Machine Translation Post Editing (MTPE). However, the industry is seeing enough potential to consider LLMs as a valuable option.

Large Language Models 101

Large Language Models Prompt Engineering Prompt Engineer Metadata 101

Snorkel AI

MARCH 26, 2025

LLM-as-Judge has emerged as a powerful tool for evaluating and validating the outputs of generative models. LLMs (and, therefore, LLM judges) inherit biases from their training data. In this article, well explore how enterprises can leverage LLM-as-Judge effectively , overcome its limitations, and implement best practices.

LLM 52

LLM Data Scientist Prompt Engineering Prompt Engineer 52

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 Engineering 133

Prompt Engineering Prompt Engineer Chatbots Generative AI 133

Marktechpost

OCTOBER 9, 2024

As the landscape of generative models evolves rapidly, organizations, researchers, and developers face significant challenges in systematically evaluating different models, including LLMs (Large Language Models), retrieval-augmented generation (RAG) setups, or even variations in prompt engineering.

Automation 126

Automation LLM AI Tools Prompt Engineering 126

ODSC - Open Data Science

SEPTEMBER 19, 2023

Prompt engineers are responsible for developing and maintaining the code that powers large language models or LLMs for short. But to make this a reality, prompt engineers are needed to help guide large language models to where they need to be. But what exactly is a prompt engineer ?

Prompt Engineering 98

Prompt Engineering Prompt Engineer Large Language Models Software Engineer 98

Flipboard

MARCH 4, 2025

We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices. The quality of prompt (the system prompt, in this case) has significant impact on the model output.

Generative AI 164

Generative AI Prompt Engineering Prompt Engineer AI 164

ODSC - Open Data Science

OCTOBER 3, 2023

Who hasn’t seen the news surrounding one of the latest jobs created by AI, that of prompt engineering ? If you’re unfamiliar, a prompt engineer is a specialist who can do everything from designing to fine-tuning prompts for AI models, thus making them more efficient and accurate in generating human-like text.

Prompt Engineering 97

Prompt Engineering Prompt Engineer Large Language Models Data Science 97

Unite.AI

SEPTEMBER 27, 2023

Having been there for over a year, I've recently observed a significant increase in LLM use cases across all divisions for task automation and the construction of robust, secure AI systems. Every financial service aims to craft its own fine-tuned LLMs using open-source models like LLAMA 2 or Falcon.

Generative AI 304

Generative AI Large Language Models Prompt Engineering Prompt Engineer 304

AWS Machine Learning Blog

FEBRUARY 27, 2025

In our previous blog posts, we explored various techniques such as fine-tuning large language models (LLMs), prompt engineering, and Retrieval Augmented Generation (RAG) using Amazon Bedrock to generate impressions from the findings section in radiology reports using generative AI. Part 1 focused on model fine-tuning.

LLM 80

LLM Generative AI AI AI 80

ODSC - Open Data Science

AUGUST 29, 2023

With that said, companies are now realizing that to bring out the full potential of AI, prompt engineering is a must. So we have to ask, what kind of job now and in the future will use prompt engineering as part of its core skill set?

Prompt Engineering 98

Prompt Engineering Prompt Engineer Large Language Models Natural Language Processing 98

Towards AI

FEBRUARY 13, 2024

Leading this revolution is ChatGPT, a state-of-the-art large language model (LLM) developed by OpenAI. ChatGPT’s advanced language understanding, and generation capacities have not only increased user engagement but also opened new avenues for increased productivity and automation in personal life as well as business problems.

Prompt Engineering 105

Prompt Engineering Prompt Engineer ChatGPT Large Language Models 105

AssemblyAI

FEBRUARY 21, 2025

transcribe(MEETING_URL) Step 2: Generate a meeting summary Now that we have a transcript, we can prompt it with LLMs. To do this we first we need to create this prompt. Here's an example that generates a comprehensive meeting summary, guiding the LLM in analyzing your meeting transcript. Add these lines to your main.py

Python 130

Python LLM Prompt Engineering Prompt Engineer 130

Unite.AI

FEBRUARY 6, 2025

Because Large Language Models (LLM) are general-purpose models that dont have all or even the most recent data, you need to augment queries, otherwise known as prompts, to get a more accurate answer. But GenAI agents can fully automate responses without involving people. Copilots are usually built using RAG pipelines.

LLM 113

LLM Automation Data Quality Prompt Engineering 113

AWS Machine Learning Blog

FEBRUARY 21, 2025

Fine-tuning a pre-trained large language model (LLM) allows users to customize the model to perform better on domain-specific tasks or align more closely with human preferences. You can use supervised fine-tuning (SFT) and instruction tuning to train the LLM to perform better on specific tasks using human-annotated datasets and instructions.

LLM 80

LLM AI AI Data Scientist 80

Artificial Corner

AUGUST 3, 2023

Prompt engineering in under 10 minutes — theory, examples and prompting on autopilot Master the science and art of communicating with AI. Prompt engineering is the process of coming up with the best possible sentence or piece of text to ask LLMs, such as ChatGPT, to get back the best possible response.

Prompt Engineering 98

Prompt Engineering Prompt Engineer Large Language Models Explainability 98

AWS Machine Learning Blog

DECEMBER 5, 2024

With the launch of the Automated Reasoning checks in Amazon Bedrock Guardrails (preview), AWS becomes the first and only major cloud provider to integrate automated reasoning in our generative AI offerings. Click on the image below to see a demo of Automated Reasoning checks in Amazon Bedrock Guardrails.

Responsible AI 103

Responsible AI AI Tools AI AI 103

Marktechpost

MARCH 23, 2025

Ensuring reliable instruction-following in LLMs remains a critical challenge. Traditional prompt engineering techniques fail to deliver consistent results. Traditional approaches to developing conversational LLM applications often fail in real-world use cases. You can find our research paper on ARQs vs. CoT on parlant.io

Prompt Engineering 86

Prompt Engineering Prompt Engineer LLM Explainability 86

Marktechpost

JANUARY 8, 2025

Traditional test case generation approaches rely on rule-based systems or manual engineering of prompts for Large Language Models (LLMs). Most researchers use manual methods to optimize prompt engineering for test case generation, which requires significant time investment.

Automation 83

Automation LLM Prompt Engineering Prompt Engineer 83

Snorkel AI

MARCH 4, 2025

Misaligned LLMs can generate harmful, unhelpful, or downright nonsensical responsesposing risks to both users and organizations. This is where LLM alignment techniques come in. LLM alignment techniques come in three major varieties: Prompt engineering that explicitly tells the model how to behave.

LLM 52

LLM Large Language Models Data Quality Prompt Engineering 52

AWS Machine Learning Blog

JUNE 25, 2024

Operational efficiency Uses prompt engineering, reducing the need for extensive fine-tuning when new categories are introduced. The raw data is processed by an LLM using a preconfigured user prompt. The LLM generates output based on the user prompt. The Step Functions workflow starts.

Automation 120

Automation Prompt Engineering Prompt Engineer Categorization 120

Flipboard

NOVEMBER 15, 2024

By harnessing the capabilities of generative AI, you can automate the generation of comprehensive metadata descriptions for your data assets based on their documentation, enhancing discoverability, understanding, and the overall data governance within your AWS Cloud environment.

Metadata 148

Metadata Generative AI LLM AI 148

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

Unite.AI

JULY 22, 2024

At my company Jotform, we have incorporated AI tools to automate tedious tasks, or as I call it, “busywork,” and free up employees to focus on the meaningful work that only humans can do. And it’s only as effective as the prompts you give it. I recently asked ChatGPT how to develop your prompt engineering skills.

ChatGPT 278

ChatGPT Prompt Engineering Prompt Engineer Explainability 278

ODSC - Open Data Science

APRIL 2, 2025

In 2025, artificial intelligence isnt just trendingits transforming how engineering teams build, ship, and scale software. Whether its automating code, enhancing decision-making, or building intelligent applications, AI is rewriting what it means to be a modern engineer. At the heart of this workflow is prompt engineering.

Prompt Engineering 52

Prompt Engineering Prompt Engineer Large Language Models ML Engineer 52

AWS Machine Learning Blog

MARCH 27, 2025

After achieving the desired accuracy, you can use this ground truth data in an ML pipeline with automated machine learning (AutoML) tools such as AutoGluon to train a model and inference the support cases. If labeled data is unavailable, the next question is whether the testing process should be automated.

Categorization 89

Categorization ETL Prompt Engineering Prompt Engineer 89

Marktechpost

JULY 21, 2024

The relief from this manual work comes with prompt engineering or the development of a unique optimization procedure, which is necessary for LLM evaluations to function as intended. To get the most out of an LLM evaluation, tailor it to the company’s unique use case and facts.

LLM 108

LLM Prompt Engineering Prompt Engineer AI 108

Towards AI

APRIL 7, 2024

This process is known as inference — Source : Image by Author Getting the most out of LLMs requires carefully crafted prompts — the instructions given to the LLM to guide its output. While we will talk about a few of these, our focus will be on one novel approach called Chain of Thought (CoT) prompting.

LLM 104

LLM Auto-complete Prompt Engineering Prompt Engineer 104

AWS Machine Learning Blog

NOVEMBER 6, 2023

The good news is that automating and solving the summarization challenge is now possible through generative AI. The best LLMs can process even complex, non-linear sentence structures with ease and determine various aspects, including topic, intent, next steps, outcomes, and more.

Automation 125

Automation Generative AI LLM AI 125

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 Engineer 133

Prompt Engineer Prompt Engineering Auto-complete Large Language Models 133

O'Reilly Media

MARCH 25, 2025

Lets be real: building LLM applications today feels like purgatory. The truth is, we’re in the earliest days of understanding how to build robust LLM applications. What makes LLM applications so different? Theyre fundamentally non-deterministicwe call it the flip-floppy nature of LLMs: same input, different outputs.

LLM 67

LLM Software Development Prompt Engineering Prompt Engineer 67

Flipboard

JANUARY 23, 2025

The study of autonomous agents powered by large language models (LLMs) has shown great promise in enhancing human productivity. They allow users to focus on creative and strategic work by automating routine digital tasks. Traditional techniques relied on human-annotated data and prompt engineering to enhance the performance of LLMs.

LLM 117

LLM Prompt Engineering Prompt Engineer Large Language Models 117