AWS Machine Learning Blog

AUGUST 2, 2024

The initial draft of a large language model (LLM) generated earnings call script can be then refined and customized using feedback from the company’s executives. Amazon Bedrock offers a straightforward way to build and scale generative AI applications with foundation models (FMs) and LLMs.

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Artificial Corner

SEPTEMBER 16, 2024

Pixabay OpenAI just released a new model and I have more reasons to believe that learning prompt engineering is becoming less relevant. I’m not saying prompt engineering is already dead (later in this article I explain why) but things have changed since OpenAI released ChatGPT in 2022.

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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.

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Towards AI

FEBRUARY 13, 2024

Leading this revolution is ChatGPT, a state-of-the-art large language model (LLM) developed by OpenAI. Understanding Prompt Engineering At the heart of effectively leveraging ChatGPT lies ‘prompt engineering’ — a crucial skill that involves crafting specific inputs or prompts to guide the AI in producing the desired outputs.

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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?

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ODSC - Open Data Science

JANUARY 29, 2024

The role of prompt engineer has attracted massive interest ever since Business Insider released an article last spring titled “ AI ‘Prompt Engineer Jobs: $375k Salary, No Tech Backgrund Required.” It turns out that the role of a Prompt Engineer is not simply typing questions into a prompt window.

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Marktechpost

JULY 4, 2023

For the unaware, ChatGPT is a large language model (LLM) trained by OpenAI to respond to different questions and generate information on an extensive range of topics. 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.

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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.

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Prompt Engineering Prompt Engineer Large Language Models Explainability 83

Heartbeat

AUGUST 25, 2023

Introduction Prompt Engineering is arguably the most critical aspect in harnessing the power of Large Language Models (LLMs) like ChatGPT. However; current prompt engineering workflows are incredibly tedious and cumbersome. Logging prompts and their outputs to .csv First install the package via pip.

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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 Engineering Prompt Engineer Computer Vision Machine Learning 113

TheSequence

DECEMBER 8, 2023

In this post, Jordan Burgess, co-founder and Chief Product Officer at Humanloop , discusses the techniques for going from an initial demo to a robust production-ready application and explain how tools like Humanloop can help you get there. He covers best practices in prompt engineering, retrieval-augmented generation (RAG) and fine-tuning.

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LLM Prompt Engineering Prompt Engineer OpenAI 97

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.

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Prompt Engineering Prompt Engineer Large Language Models Responsible AI 52

Marktechpost

AUGUST 1, 2024

The primary issue addressed in the paper is the need for formal analysis and structured design principles for LLM-based algorithms. This approach is inefficient and lacks a theoretical foundation, making it difficult to optimize and accurately predict the performance of LLM-based algorithms.

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Algorithm LLM Machine Learning Prompt Engineering 124

Bugra Akyildiz

MARCH 30, 2024

Before going further, taking a step back to explain the key concepts in Mamba: State: Mamba maintains a state that captures the essential information about the past that is relevant for predicting the next element in the sequence. The logic of the prompt specifies what the LLM should do, while the wording is how the prompt is phrased.

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Unite.AI

JULY 22, 2024

And it’s only as effective as the prompts you give it. I recently asked ChatGPT how to develop your prompt engineering skills. The first response was: “Experimentation and Iteration: Continuously experiment with different types of prompts and refine them based on the AI's outputs.

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AI News

NOVEMBER 15, 2023

The truth is, however, that such hallucinations are an inevitability when dealing with LLMs. As McLoone explains, it is all a question of purpose. “I So you get these fun things where you can say ‘explain why zebras like to eat cacti’ – and it’s doing its plausibility job,” says McLoone. “It It doesn’t have to be right.”

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Towards AI

JULY 27, 2024

Claude AI is an LLM based on the powerful transformer architecture and like OpenAI’s ChatGPT, it can generate text, translate languages, as well as write different kinds of compelling content. This means it can explain the reasoning and decision-making process behind all of its responses. But they are designed for various purposes.

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AWS Machine Learning Blog

JULY 24, 2024

Large language models (LLMs) have achieved remarkable success in various natural language processing (NLP) tasks, but they may not always generalize well to specific domains or tasks. You may need to customize an LLM to adapt to your unique use case, improving its performance on your specific dataset or task.

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ODSC - Open Data Science

DECEMBER 21, 2023

Your Guide to Starting With RAG for LLM-Powered Applications In this post, we take a closer look at how RAG has emerged as the ideal starting point when it comes to designing enterprise LLM-powered applications. RAG vs Finetuning — Which Is the Best Tool to Boost Your LLM Application? Grab your tickets for 70% off by Friday!

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LLM Prompt Engineering Prompt Engineer Data Science 98

Artificial Corner

JULY 30, 2023

In this world of complex terminologies, someone who wants to explain Large Language Models (LLMs) to some non-tech guy is a difficult task. So that’s why I tried in this article to explain LLM in simple or to say general language. No need to train the LLM but one only has to think about Prompt design.

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ODSC - Open Data Science

AUGUST 24, 2023

5 Jobs That Will Use Prompt Engineering in 2023 Whether you’re looking for a new career or to enhance your current path, these jobs that use prompt engineering will become desirable in 2023 and beyond. In addition, we’ll discuss a variety of tools that form the modern LLM application development stack.

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Prompt Engineering Prompt Engineer Data Science NLP 52

Unite.AI

NOVEMBER 3, 2023

Introduction Prompt engineering focuses on devising effective prompts to guide Large Language Models (LLMs) such as GPT-4 in generating desired responses. A well-crafted prompt can be the difference between a vague or inaccurate answer and a precise, insightful one.

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Mlearning.ai

JULY 8, 2023

High level process and flow LLM Ops is people, process and technology. LLM Ops flow — Architecture Architecture explained. Prompt Engineering — this is where figuring out what is the right prompt to use for the problem. Develop the LLM application using existing models or train a new model.

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Large Language Models LLM Prompt Engineering Prompt Engineer 52

Marktechpost

MAY 3, 2024

Prompt Engineering for ChatGPT This course teaches how to effectively work with large language models, like ChatGPT, by applying prompt engineering. It covers leveraging prompt patterns to tap into powerful capabilities within these models.

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Marktechpost

JULY 20, 2023

A new study from the University of California, Santa Barbara, and Microsoft proposes the Directional Stimulus Prompting (DSP) architecture that enhances the frozen black-box LLM on downstream tasks using a tiny tuneable LM (RL). To help the LLM produce the required summary based on the keywords, keywords act as the stimulus (hints).

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LLM AI Research AI Researcher Prompt Engineering 98

Explosion

MAY 17, 2023

In 2014 I started working on spaCy , and here’s an excerpt of how I explained the motivation for the library: Computers don’t understand text. I don’t want to undersell how impactful LLMs are for this sort of use-case. You can give an LLM a group of comments and ask it to summarize the texts or identify key themes.

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Unite.AI

NOVEMBER 20, 2024

That said, AgentOps (the tool) offers developers insight into agent workflows with features like session replays, LLM cost tracking, and compliance monitoring. Agents are built to interact with specific datasets, tools, and prompts while maintaining compliance with predefined rules. What is AgentOps?

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AI News

SEPTEMBER 27, 2024

One of Databricks’ notable achievements is the DBRX model, which set a new standard for open large language models (LLMs). “Upon release, DBRX outperformed all other leading open models on standard benchmarks and has up to 2x faster inference than models like Llama2-70B,” Everts explains. “It

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Marktechpost

APRIL 1, 2024

Although large language models (LLMs) had been developed prior to the launch of ChatGPT, the latter’s ease of accessibility and user-friendly interface took the adoption of LLM to a new level. and explains how they work. The book also provides a guide for leveraging and deploying LLMs to solve practical problems.

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Marktechpost

AUGUST 31, 2024

This approach aims to balance latency and interpretability by combining a small classification model, specifically a small language model (SLM), with a downstream LLM module called a “constrained reasoner.” ” The SLM performs initial hallucination detection, while the LLM module explains the detected hallucinations.

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AWS Machine Learning Blog

SEPTEMBER 5, 2024

As generative artificial intelligence (AI) continues to revolutionize every industry, the importance of effective prompt optimization through prompt engineering techniques has become key to efficiently balancing the quality of outputs, response time, and costs. In the Prompt field, write your prompt evaluation template.

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Towards AI

APRIL 12, 2024

Fine-Tuning AI Responses with Savvy Prompt Engineering I don’t know about you, but as much as I love ChatGPT, specifically GPT 4, one thing I cannot stand is the tone in which it writes, and its habit of inundating me with reams of text when I ask a basic question. Join thousands of data leaders on the AI newsletter.

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AWS Machine Learning Blog

APRIL 24, 2024

To increase training samples for better learning, we also used another LLM to generate feedback scores. We present the reinforcement learning process and the benchmarking results to demonstrate the LLM performance improvement. They can also provide a better answer to the question or comment on why the LLM response is not satisfactory.

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AWS Machine Learning Blog

AUGUST 6, 2024

The wide applicability of LLMs explains why customers across healthcare, financial services, and media and entertainment are moving quickly to adopt them. Customization includes varied techniques such as Prompt Engineering, Retrieval Augmented Generation (RAG), and fine-tuning and continued pre-training. Learn more here.

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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.

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Heartbeat

FEBRUARY 13, 2024

Learning Path to Building LLM-Based Solutions — For Practitioner Data Scientists As everyone would agree, the advent of LLM has transformed the technology industry, and technocrats have had a huge surge of interest in learning about LLMs. Langchain is very comprehensive, and its applications are evolving rapidly.

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deepsense.ai

NOVEMBER 9, 2024

On the other hand, the more demanding the task – the higher the risk of LLM hallucinations. In this article, you’ll find: what the problem with hallucination is, which techniques we use to reduce them, how to measure hallucinations using methods such as LLM-as-a-judge tips and tricks from my experience as an experienced data scientist.

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