AI News

SEPTEMBER 27, 2024

“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 ” Genie: Everts explains this as “a conversational interface for addressing ad-hoc and follow-up questions through natural language.”

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Towards AI

MAY 30, 2024

The Verbal Revolution: Unlocking Prompt Engineering with Langchain Peter Thiel, the visionary entrepreneur and investor, mentioned in a recent interview that the post-AI society may favour strong verbal skills over math skills. Buckle up, and let’s dive into the fascinating world of prompt engineering with Langchain!

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Towards AI

APRIL 10, 2023

It’s worth noting that prompt engineering plays a critical role in the success of training such models. In carefully crafting effective “prompts,” data scientists can ensure that the model is trained on high-quality data that accurately reflects the underlying task. Some examples of prompts include: 1.

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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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Flipboard

DECEMBER 19, 2023

It’s like a business technical skillset that’s also creative,” explained Greg Beltzer, head of technology at RBC Wealth Management. “It’s not just development.

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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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Heartbeat

APRIL 10, 2023

At this point, a new concept emerged: “Prompt Engineering.” What is Prompt Engineering? The output produced by language models varies significantly with the prompt served. If this reasoning process is explained with examples, the AI can generally achieve more accurate results.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

For now, we consider eight key dimensions of responsible AI: Fairness, explainability, privacy and security, safety, controllability, veracity and robustness, governance, and transparency. For example, you can ask the model to explain why it used certain information and created a certain output.

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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 98

Towards AI

FEBRUARY 13, 2024

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. Examples: “Explain the solar system. Assume that I am a curious 6-year-old.” “Act

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Prompt Engineering Prompt Engineer ChatGPT Large Language Models 105

Towards AI

OCTOBER 19, 2024

Yet, for all their sophistication, they often can’t explain their choices — this lack of transparency isn’t just frustrating — it’s increasingly problematic as AI becomes more integrated into critical areas of our lives. Enter Explainable AI (XAI), a field dedicated to making AI’s decision-making process more transparent and understandable.

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Explainability Explainable AI Natural Language Processing Prompt Engineer 105

AI Weekly

SEPTEMBER 7, 2023

singularityhub.com What You Should Know About AI Customer Service Tools Streamlining data capture to focus on relevant, premium data will support improved AI customer service tools functionality and precision-led machine learning. As expected, the AI’s responses were on point, sympathetic, and felt so utterly human.

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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.

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Marktechpost

AUGUST 5, 2024

Large Language Models (LLMs) have revolutionized problem-solving in machine learning, shifting the paradigm from traditional end-to-end training to utilizing pretrained models with carefully crafted prompts. The VML framework offers several advantages over traditional numerical machine learning approaches.

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Marktechpost

APRIL 28, 2024

and also allows the students to build an understanding of machine learning algorithms, including supervised, unsupervised, reinforcement, etc. The course covers the common terminologies of AI, including neural networks, machine learning, deep learning, etc., and what AI can and cannot do. taught by Andrew Ng.

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Marktechpost

AUGUST 1, 2024

Existing methods for integrating LLMs into algorithms typically involve using LLM calls and prompt engineering. These examples demonstrate the framework’s capability to explain empirical phenomena, guide parameter choices, and inspire future work in LLM-based algorithm design.

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Towards AI

JANUARY 21, 2025

Many articles about how-to-use, prompt engineering and the logic behind have been published. I will explain conceptually how LLMs calculate their responses step-by-step, go deep into the attention mechanism, and demonstrate the inner workings in a code example.So, lets get started! Introduction to Transformers1.2 Tokenization1.3

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AWS Machine Learning Blog

DECEMBER 23, 2024

In this post, we explore why GraphRAG is more comprehensive and explainable than vector RAG alone, and how you can use this approach using AWS services and Lettria. Results are then used to augment the prompt and generate a more accurate response compared to standard vector-based RAG.

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Marktechpost

APRIL 1, 2024

and explains how they work. ChatGPT for Beginners The book explains the fundamentals and the technology behind ChatGPT and its innovative use cases in diverse fields. ChatGPT for Beginners The book explains the fundamentals and the technology behind ChatGPT and its innovative use cases in diverse fields.

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Unite.AI

OCTOBER 5, 2023

Developing the Persona Through Prompts Creating an AI persona isn’t just about conceptualization; it's about turning that concept into a functional, responsive model. The way to achieve this is through effective prompt engineering. Prompts serve as the guideline or ‘training manual' for ChatGPT.

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Marktechpost

MAY 30, 2024

This article lists the top AI courses by Google that provide comprehensive training on various AI and machine learning technologies, equipping learners with the skills needed to excel in the rapidly evolving field of AI. Participants learn how to improve model accuracy and write scalable, specialized ML models.

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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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ODSC - Open Data Science

MARCH 10, 2025

Over the past decade, data science has undergone a remarkable evolution, driven by rapid advancements in machine learning, artificial intelligence, and big data technologies. Topics such as explainability (XAI) and AI governance gained traction, reflecting the growing societal impact of AI technologies.

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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

DECEMBER 5, 2024

For use cases where accuracy is critical, customers need the use of mathematically sound techniques and explainable reasoning to help generate accurate FM responses. Despite the advancements in FMs, models can still produce hallucinationsa challenge many of our customers face.

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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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AWS Machine Learning Blog

JUNE 25, 2024

Although these traditional machine learning (ML) approaches might perform decently in terms of accuracy, there are several significant advantages to adopting generative AI approaches. Operational efficiency Uses prompt engineering, reducing the need for extensive fine-tuning when new categories are introduced.

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AWS Machine Learning Blog

APRIL 9, 2024

In the following sections, we explain how you can use these features with either the AWS Management Console or SDK. For this post, we gave a few examples for creating a “Financial Advisor AI system” using Amazon financial reports with custom prompts. For best practices on prompt engineering, refer to Prompt engineering guidelines.

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Machine Learning Prompt Engineer Prompt Engineering Artificial Intelligence 135

Towards AI

JULY 27, 2024

Emphasizes Explainability While many of the AI and LLMs currently operate as ‘black boxes’, Claude offers a high level of explainability surpassing other models. This means it can explain the reasoning and decision-making process behind all of its responses. Also, their explainability makes them more attractive.

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Marktechpost

APRIL 16, 2024

It explains the fundamentals of LLMs and generative AI and also covers prompt engineering to improve performance. Machine Learning Engineering with Python This book is a comprehensive guide to building and scaling machine-learning projects that solve real-world problems.

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Large Language Models Auto-complete Prompt Engineer Prompt Engineering 103

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.

ChatGPT 105

ChatGPT Prompt Engineer Prompt Engineering Large Language Models 105

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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ODSC - Open Data Science

DECEMBER 19, 2023

They need to be able to explain complex technical concepts to non-technical stakeholders and to identify and solve problems that arise during the development and implementation of AI models. Prompt Engineer Prompt engineers are in the wild west of AI.

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AWS Machine Learning Blog

JULY 26, 2023

If you are looking for a curated playlist of the top resources, concepts, and guidance to get up to speed on foundation models, and especially those that unlock generative capabilities in your data science and machine learning projects, then look no further. More of a reader than a video consumer?

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Generative AI Prompt Engineer Prompt Engineering Large Language Models 98

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. The prompt is better if containing examples. -

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Unite.AI

AUGUST 30, 2024

Jason Knight is Co-founder and Vice President of Machine Learning at OctoAI , the platform delivers a complete stack for app builders to run, tune, and scale their AI applications in the cloud or on-premises. Can you explain the advantages of deploying AI models in a private environment using OctoStack?

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Unite.AI

SEPTEMBER 19, 2024

Google Cloud Vertex AI Google Cloud Vertex AI provides a comprehensive platform for both building and deploying machine learning models, featuring Google's PaLM 2 and the newly released Gemini series. With strong integration into Google’s cloud infrastructure, it allows for seamless data operations and enterprise-level scalability.

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