Unite.AI

NOVEMBER 22, 2024

The Three Pillars of the Product Alchemist To understand the evolution of a product manager, we can categorize their responsibilities into three distinct pillars: Ideation, Execution, and Alignment and Leading with Influence. This affects everything from ideation and execution to alignment with stakeholders and leading with influence.

Data Analysis 147

Data Analysis AI AI Artificial Intelligence 147

AWS Machine Learning Blog

JANUARY 22, 2025

The key to the capability of the solution is the prompts we have engineered to instruct Anthropics Claude what to do. Prompt engineering Prompt engineering is the process of carefully designing the input prompts or instructions that are given to LLMs and other generative AI systems.

Generative AI 110

Generative AI Prompt Engineer Prompt Engineering AI 110

AWS Machine Learning Blog

DECEMBER 23, 2024

Lettrias in-house team manually assessed the answers with a detailed evaluation grid, categorizing results as correct, partially correct (acceptable or not), or incorrect. Results are then used to augment the prompt and generate a more accurate response compared to standard vector-based RAG.

Generative AI 129

Generative AI Natural Language Processing Prompt Engineer Prompt Engineering 129

AWS Machine Learning Blog

JANUARY 22, 2025

Users can review different types of events such as security, connectivity, system, and management, each categorized by specific criteria like threat protection, LAN monitoring, and firmware updates. 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

AWS Machine Learning Blog

JUNE 25, 2024

Manually analyzing and categorizing large volumes of unstructured data, such as reviews, comments, and emails, is a time-consuming process prone to inconsistencies and subjectivity. Operational efficiency Uses prompt engineering, reducing the need for extensive fine-tuning when new categories are introduced.

Automation 126

Automation Prompt Engineer Prompt Engineering Categorization 126

Unite.AI

SEPTEMBER 20, 2023

To install and import the library, use the following commands: pip install -q transformers from transformers import pipeline Having done that, you can execute NLP tasks starting with sentiment analysis, which categorizes text into positive or negative sentiments.

LLM 342

LLM NLP BERT Python 342

Marktechpost

MAY 7, 2024

Researchers have primarily focused on enhancing NL2SQL methods, which can be categorized into pre-trained and Supervised Fine-Tuning (SFT) methods, prompt engineering-based LLMs, and LLMs specifically trained for NL2SQL. The researchers propose novel solutions tailored to the NL2BI scenario to address these challenges.

Business Intelligence 117

Business Intelligence Prompt Engineering Prompt Engineer Natural Language Processing 117

Marktechpost

AUGUST 31, 2024

This includes careful prompt engineering for the LLM and potential feedback loops where the LLM’s explanations can be used to refine the SLM’s detection criteria over time. The experimental results demonstrate the effectiveness of the proposed hallucination detection framework, particularly the Categorized approach.

Large Language Models 128

Large Language Models Categorization LLM Explainability 128

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 Sonnet across various tasks.

LLM 96

LLM Prompt Engineer Prompt Engineering Generative AI 96

Unite.AI

AUGUST 8, 2023

Information Retrieval: Using LLMs, such as BERT or GPT, as part of larger architectures to develop systems that can fetch and categorize information. This recent post demystifies Midjourney in a detailed guide, elucidating both the platform and its prompt engineering intricacies.

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243

AWS Machine Learning Blog

MAY 7, 2024

This post walks through examples of building information extraction use cases by combining LLMs with prompt engineering and frameworks such as LangChain. Prompt engineering Prompt engineering enables you to instruct LLMs to generate suggestions, explanations, or completions of text in an interactive way.

Prompt Engineering 122

Prompt Engineering Prompt Engineer Large Language Models LLM 122

Unite.AI

JANUARY 11, 2024

As the paper demonstrated, prompt engineering allows creating training data for hundreds of thousands of embedding tasks. Yet, current prompt design practices remain more an art than science. However, critical research directions remain to translate this potential into real-world impact.

Large Language Models 147

Large Language Models Prompt Engineer Prompt Engineering BERT 147

Marktechpost

AUGUST 10, 2024

Software engineers have shown reluctance to use LLMs for higher-level design tasks due to concerns about complex requirement comprehension. Despite this, LLMs’ use in requirement engineering has gradually increased, driven by advancements in contextual analysis and reasoning through prompt engineering and Chain-of-Thought techniques.

Software Engineer 113

Software Engineer LLM Large Language Models Categorization 113

Marktechpost

MAY 11, 2024

IE tasks compel models to discern and categorize text in formats that align with predefined structures, such as named entity recognition and relation classification. However, existing LLMs typically falter when tasked with the nuanced understanding and alignment necessary for effective IE.

Large Language Models 109

Large Language Models Prompt Engineering Prompt Engineer Categorization 109

AWS Machine Learning Blog

OCTOBER 6, 2023

For instance, in ecommerce, image-to-text can automate product categorization based on images, enhancing search efficiency and accuracy. With millions of products listed, effective sorting and categorization poses a significant challenge. This is where the power of auto-tagging and attribute generation comes into its own.

Generative AI 125

Generative AI Prompt Engineer Prompt Engineering Computer Vision 125

Artificial Corner

JULY 30, 2023

Machine translation, summarization, ticket categorization, and spell-checking are among the examples. Prompts design is a process of creating prompts which are the instructions and context that are given to Large Language Models to achieve the desired task. What are large language models used for?

Large Language Models 98

Large Language Models LLM Natural Language Processing Deep Learning 98

AWS Machine Learning Blog

SEPTEMBER 14, 2023

Document categorization or classification has significant benefits across business domains – Improved search and retrieval – By categorizing documents into relevant topics or categories, it makes it much easier for users to search and retrieve the documents they need. They can search within specific categories to narrow down results.

Categorization 121

Categorization Machine Learning Data Scientist Natural Language Processing 121

AWS Machine Learning Blog

NOVEMBER 7, 2024

Some components are categorized in groups based on the type of functionality they exhibit. Prompt catalog – Crafting effective prompts is important for guiding large language models (LLMs) to generate the desired outputs. Having a centralized prompt catalog is essential for storing, versioning, tracking, and sharing prompts.

Generative AI 113

Generative AI Machine Learning AI AI 113

AWS Machine Learning Blog

FEBRUARY 12, 2025

Curated judge models : Amazon Bedrock provides pre-selected, high-quality evaluation models with optimized prompt engineering for accurate assessments. Users dont need to bring external judge models, because the Amazon Bedrock team maintains and updates a selection of judge models and associated evaluation judge prompts.

LLM 94

LLM Generative AI Automation Machine Learning 94

Unite.AI

AUGUST 28, 2023

link] The process can be categorized into three agents: Execution Agent : The heart of the system, this agent leverages OpenAI’s API for task processing. Given an objective and a task, it prompts OpenAI's API and retrieves task outcomes.

Auto-complete 240

Auto-complete ChatGPT Large Language Models Neural Network 240

Marktechpost

NOVEMBER 19, 2024

Current methods to limit these LLM vulnerabilities include adversarial testing, red-teaming exercises, and manual prompt engineering. The identified vulnerabilities are categorized based on their impact, severity, and potential exploitability, providing a structured approach to addressing risks.

LLM 84

LLM Prompt Engineering Prompt Engineer Large Language Models 84

AWS Machine Learning Blog

MARCH 13, 2024

Use LLM prompt engineering to accommodate customized policies The pre-trained Toxicity Detection models from Amazon Transcribe and Amazon Comprehend provide a broad toxicity taxonomy, commonly used by social platforms for moderating user-generated content in audio and text formats.

Natural Language Processing 134

Natural Language Processing LLM Prompt Engineer Prompt Engineering 134

Unite.AI

JANUARY 19, 2024

Taxonomy of Hallucination Mitigation Techniques Researchers have introduced diverse techniques to combat hallucinations in LLMs, which can be categorized into: 1. Prompt Engineering This involves carefully crafting prompts to provide context and guide the LLM towards factual, grounded responses.

Large Language Models 113

Large Language Models LLM Prompt Engineer Prompt Engineering 113

Marktechpost

SEPTEMBER 15, 2024

These sources can be categorized into three types: textual documents (e.g., Techniques like Uprise and DaSLaM use lightweight retrievers or small models to optimize prompts, break down complex problems, or generate pseudo labels. KD methods can be categorized into white-box and black-box approaches.

BERT 120

BERT LLM Large Language Models Categorization 120

Flipboard

DECEMBER 6, 2023

Types of summarizations There are several techniques to summarize text, which are broadly categorized into two main approaches: extractive and abstractive summarization. Given their versatile nature, these models require specific task instructions provided through input text, a practice referred to as prompt engineering.

BERT 167

BERT Large Language Models Artificial Intelligence Artificial Intelligence 167

AWS Machine Learning Blog

AUGUST 22, 2024

Verisk’s evaluation involved three major parts: Prompt engineering – Prompt engineering is the process where you guide generative AI solutions to generate desired output. Verisk framed prompts using their in-house clinical experts’ knowledge on medical claims.

Generative AI 113

Generative AI Auto-complete Software Development Automation 113

AWS Machine Learning Blog

SEPTEMBER 1, 2023

Operationalization journey per generative AI user type To simplify the description of the processes, we need to categorize the main generative AI user types, as shown in the following figure. Strong domain knowledge for tuning, including prompt engineering, is required as well. We will cover monitoring in a separate post.

Generative AI 127

Generative AI Prompt Engineer Prompt Engineering ML 127

AWS Machine Learning Blog

OCTOBER 24, 2023

When a new document type introduced in the IDP pipeline needs classification, the LLM can process text and categorize the document given a set of classes. For example, we can follow prompt engineering best practices to fine-tune an LLM to format dates into MM/DD/YYYY format, which may be compatible with a database DATE column.

IDP 137

IDP LLM Prompt Engineer Prompt Engineering 137

Unite.AI

AUGUST 4, 2023

In this article, we will delve deeper into these issues, exploring the advanced techniques of prompt engineering with Langchain, offering clear explanations, practical examples, and step-by-step instructions on how to implement them. Prompts play a crucial role in steering the behavior of a model.

Prompt Engineering 245

Prompt Engineering Prompt Engineer Python NLP 245

AWS Machine Learning Blog

MAY 1, 2024

It allows you to retrieve data from sources beyond the foundation model, enhancing prompts by integrating contextually relevant retrieved data. You can use prompt engineering to prevent hallucination and make sure that the answer is grounded in the source documentations.

Chatbots 129

Chatbots Automation Machine Learning DevOps 129

Towards AI

SEPTEMBER 26, 2023

OpenAI Announces DALL·E 3 OpenAI is launching DALL·E 3, an improved version that excels in following instructions, requires less prompt engineering, and can communicate with ChatGPT. This integration enables users to refine DALL·E 3 prompts by describing their ideas to ChatGPT. Five 5-minute reads/videos to keep you learning 1.Adept.ai

Prompt Engineer 64

Prompt Engineer Prompt Engineering OpenAI ChatGPT 64

Marktechpost

JANUARY 11, 2024

We have categorized them to make it easier to cover maximum tools. Built on ChatGPT, this version enhances user-friendliness by eliminating the need for complex prompt engineering. Operating based on natural language inputs or prompts, the model generates accurate images corresponding to the provided descriptions.

Large Language Models 104

Large Language Models Natural Language Processing Artificial Intelligence Artificial Intelligence 104

Bugra Akyildiz

AUGUST 27, 2023

LARs are a type of embedding that can be used to represent high-dimensional categorical data in a lower-dimensional continuous space. Prompt engineering aims to solve these problems, but comes with a steep learning curve and increased fragility as the prompt increases in size.

OpenAI 52

OpenAI Large Language Models Categorization LLM 52

AWS Machine Learning Blog

APRIL 9, 2025

The Send your feedback form provides the user the option to categorize the feedback and provide additional details for the administrator to review. For example, consider if a user asks about their vacation policy and no answer is returned. The user can then choose the thumbs down icon and send feedback to the administrator.

Generative AI 67

Generative AI Metadata Software Engineer Prompt Engineer 67

AWS Machine Learning Blog

FEBRUARY 14, 2024

In-context learning, prompt engineering, and model invocation We use in-context learning to be able to use a foundation model to accomplish this task. In-context learning is the ability for LLMs to learn the task using just what’s in the prompt without being pre-trained or fine-tuned for the particular task. and 1.0.

Generative AI 126

Generative AI LLM Large Language Models AI 126

Snorkel AI

JUNE 23, 2023

This approach was less popular among our attendees from the wealthiest of corporations, who expressed similar levels of interest in fine-tuning with prompts and responses, fine-tuning with unstructured data, and prompt engineering.

Data Science 64

Data Science Large Language Models Data Scientist Machine Learning 64

Snorkel AI

JUNE 23, 2023

This approach was less popular among our attendees from the wealthiest of corporations, who expressed similar levels of interest in fine-tuning with prompts and responses, fine-tuning with unstructured data, and prompt engineering.

Data Science 64

Data Science Large Language Models Data Scientist Machine Learning 64