Marktechpost

MAY 30, 2024

Google plays a crucial role in advancing AI by developing cutting-edge technologies and tools like TensorFlow, Vertex AI, and BERT. Its AI courses provide valuable knowledge and hands-on experience, helping learners build and optimize AI models, understand advanced AI concepts, and apply AI solutions to real-world problems.

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Marktechpost

JUNE 24, 2024

This interest is not just about the impressive capabilities of ChatGPT in generating human-like text but also about its profound implications for the workforce. These skills underscore the need for workers to adapt and develop new competencies to work effectively alongside advanced AI systems like ChatGPT.

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Towards AI

JANUARY 30, 2024

Author(s): Abhinav Kimothi Originally published on Towards AI. Being new to the world of Generative AI, one can feel a little overwhelmed by the jargon. Designed to be general-purpose, providing a foundation for various AI applications. I’ve been asked many times about common terms used in this field.

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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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Prompt Engineer Prompt Engineering Data Science LLM 52

Marktechpost

APRIL 16, 2024

The book covers the inner workings of LLMs and provides sample codes for working with models like GPT-4, BERT, T5, LLaMA, etc. Introduction to Generative AI “Introduction to Generative AI” covers the fundamentals of generative AI and how to use it safely and effectively.

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Large Language Models Auto-complete Prompt Engineering Prompt Engineer 103

Mlearning.ai

JANUARY 17, 2024

Each section of this story comprises a discussion of the topic plus a curated list of resources, sometimes containing sites with more lists of resources: 20+: What is Generative AI? 95x: Generative AI history 600+: Key Technological Concepts 2,350+: Models & Mediums — Text, Image, Video, Sound, Code, etc.

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Generative AI Prompt Engineer Prompt Engineering Large Language Models 98

Snorkel AI

MARCH 26, 2025

LLM-as-Judge has emerged as a powerful tool for evaluating and validating the outputs of generative models. Closely observed and managed, the practice can help scalably evaluate and monitor the performance of Generative AI applications on specialized tasks. However, challenges remain. This takes several forms.

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ODSC - Open Data Science

MARCH 10, 2025

Starting with BERT and accelerating with the launch of GPT-3 , conference sessions on LLMs and transformers skyrocketed. The Generative AI Explosion and Rise of AI Agents (20232024) If theres one trend that has defined the past two years, its Generative AI.

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Marktechpost

APRIL 1, 2024

Ever since its inception, ChatGPT has taken the world by storm, marking the beginning of the era of generative AI. It provides codes for working with various models, such as GPT-4, BERT, T5, etc., The Art of Prompt Engineering with ChatGPT This book teaches the art of working with ChatGPT with the help of prompt engineering.

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Towards AI

DECEMBER 28, 2023

Major language models like GPT-3 and BERT often come with Python APIs, making it easy to integrate them into various applications. Prompt engineering refers to the practice of designing and crafting effective prompts/questions to elicit desired responses from language models or natural language processing systems.

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Large Language Models Natural Language Processing Deep Learning Prompt Engineer 122

AWS Machine Learning Blog

JUNE 25, 2024

With Amazon Bedrock, developers can experiment, evaluate, and deploy generative AI applications without worrying about infrastructure management. Its enterprise-grade security, privacy controls, and responsible AI features enable secure and trustworthy generative AI innovation at scale.

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Mlearning.ai

JULY 24, 2023

In Generative AI projects, there are five distinct stages in the lifecycle, centred around a Large Language Model 1️⃣ Pre-training : This involves building an LLM from scratch. The likes of BERT, GPT4, Llama 2, have undergone pre-training on a large corpus of data. The model generates a completion on the prompt.

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Generative AI Prompt Engineer Prompt Engineering Large Language Models 52

Unite.AI

AUGUST 28, 2023

Systems like ChatGPT by OpenAI, BERT, and T5 have enabled breakthroughs in human-AI communication. Current Landscape of AI Agents AI agents, including Auto-GPT, AgentGPT, and BabyAGI, are heralding a new era in the expansive AI universe.

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Artificial Corner

JULY 30, 2023

So that’s why I tried in this article to explain LLM in simple or to say general language. 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. RoBERTa (Robustly Optimized BERT Approach) — developed by Facebook AI.

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ODSC - Open Data Science

NOVEMBER 8, 2023

Generative AI is a new field. Over the past year, new terms, developments, algorithms, tools, and frameworks have emerged to help data scientists and those working with AI develop whatever they desire. Do you want a chatbot, a Q&A system, or an image generator? Don’t go in aimlessly expecting it to do everything.

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Generative AI Prompt Engineer Prompt Engineering LLM 52

Snorkel AI

AUGUST 17, 2023

The former will make the generative model’s outputs (mostly) fall into an expected range. Users can easily constrain an LLM’s output with clever prompt engineering. The problem of accuracy Text-generating AIs are trained to understand language largely by filling in missing tokens. BERT for misinformation.

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Generative AI BERT LLM Prompt Engineer 52

Snorkel AI

AUGUST 17, 2023

The former will make the generative model’s outputs (mostly) fall into an expected range. Users can easily constrain an LLM’s output with clever prompt engineering. The problem of accuracy Text-generating AIs are trained to understand language largely by filling in missing tokens. BERT for misinformation.

Generative AI 52

Generative AI BERT LLM Prompt Engineer 52

Snorkel AI

AUGUST 17, 2023

The former will make the generative model’s outputs (mostly) fall into an expected range. Users can easily constrain an LLM’s output with clever prompt engineering. The problem of accuracy Text-generating AIs are trained to understand language largely by filling in missing tokens. BERT for misinformation.

Generative AI 52

Generative AI BERT LLM Prompt Engineer 52

AWS Machine Learning Blog

APRIL 17, 2023

Sparked by the release of large AI models like AlexaTM , GPT , OpenChatKit , BLOOM , GPT-J , GPT-NeoX , FLAN-T5 , OPT , Stable Diffusion , and ControlNet , the popularity of generative AI has seen a recent boom. For more information, refer to EMNLP: Prompt engineering is the new feature engineering.

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Prompt Engineer Prompt Engineering Deep Learning Machine Learning 93

deepsense.ai

NOVEMBER 9, 2024

Prompt engineering Let’s start simple. With this in mind, we strongly recommend starting with prompt engineering. Tell me what you don’t know When prompting LLMs to solve a chosen problem, we can add an instruction to return an “I don’t know” answer when the model is in doubt.

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Prompt Engineer Prompt Engineering LLM ChatGPT 59

AssemblyAI

MAY 23, 2023

This trend started with models like the original GPT and ELMo, which had millions of parameters, and progressed to models like BERT and GPT-2, with hundreds of millions of parameters. Learn more about it in our dedicated blog series on Generative AI. months on average. Try LeMUR in our Playground

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Large Language Models Neural Network LLM Chatbots 130

AWS Machine Learning Blog

MAY 31, 2023

In 2018, BERT-large made its debut with its 340 million parameters and innovative transformer architecture, setting the benchmark for performance on NLP tasks. For text tasks such as sentence classification, text classification, and question answering, you can use models such as BERT, RoBERTa, and DistilBERT.

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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.

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AWS Machine Learning Blog

DECEMBER 22, 2023

These functions can be implemented in several ways, including BERT-style models, appropriately prompted LLMs, and more. Although new components have worked their way into the compute layer (fine-tuning, prompt engineering, model APIs) and storage layer (vector databases), the need for observability remains.

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LLM Large Language Models BERT Prompt Engineer 112

ODSC - Open Data Science

NOVEMBER 19, 2024

Building an Agentic Rag Application with LangGraph with Valentina Alto Slides Valentina Alto’s hands-on workshop focused on integrating AI agents with Retrieval Augmented Generation (RAG) to enhance generative AI workflows.

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ODSC - Open Data Science

SEPTEMBER 18, 2023

Especially now with the growth of generative AI and prompt engineering  — both skills that use NLP — now’s a good time to get into the field while it’s hot with this introduction to NLP course. Large Language Models Finally, the course concludes with a look at large language models, such as BERT, ELMo, GPT, and ULMFiT.

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Snorkel AI

MARCH 2, 2023

I am Ali Arsanjani, and I lead partner engineering for Google Cloud, specializing in the area of AI-ML, and I’m very happy to be here today with everyone. It came to its own with the creation of the transformer architecture: Google’s BERT, OpenAI, GPT2 and then 3, LaMDA for conversation, Mina and Sparrow from Google DeepMind.

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Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

I am Ali Arsanjani, and I lead partner engineering for Google Cloud, specializing in the area of AI-ML, and I’m very happy to be here today with everyone. It came to its own with the creation of the transformer architecture: Google’s BERT, OpenAI, GPT2 and then 3, LaMDA for conversation, Mina and Sparrow from Google DeepMind.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

FEBRUARY 13, 2024

Data scientists can use distillation to jumpstart classification models or to align small-format generative AI (GenAI) models to produce better responses. LLM distillation positions a large generative model as a “teacher” and the smaller model as a “student.” How does LLM distillation work?

LLM 52

LLM Data Scientist Neural Network Data Science 52

Snorkel AI

FEBRUARY 13, 2024

Data scientists can use distillation to jumpstart classification models or to align small-format generative AI (GenAI) models to produce better responses. LLM distillation positions a large generative model as a “teacher” and the smaller model as a “student.” How does LLM distillation work?

LLM 52

LLM Data Scientist Neural Network Data Science 52

deepsense.ai

NOVEMBER 14, 2023

In short, EDS is the problem of the widespread lack of a rational approach to and methodology for the objective, automated and quantitative evaluation of performance in terms of generative model finetuning and prompt engineering for specific downstream GenAI tasks related to practical business applications. Garrido-Merchán E.C.,

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Generative AI ML Prompt Engineer Prompt Engineering 111

Unite.AI

AUGUST 8, 2023

That is Generative AI. Generative models have blurred the line between humans and machines. With the advent of models like GPT-4, which employs transformer modules, we have stepped closer to natural and context-rich language generation. billion R&D budget to generative AI, as indicated by CEO Tim Cook.

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Unite.AI

SEPTEMBER 20, 2023

Post-Processor : Enhances construction features to facilitate compatibility with many transformer-based models, like BERT, by adding tokens such as [CLS] and [SEP]. We choose a BERT model fine-tuned on the SQuAD dataset.

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LLM NLP BERT Python 342

Flipboard

DECEMBER 6, 2023

In this post, we focus on the BERT extractive summarizer. BERT extractive summarizer The BERT extractive summarizer is a type of extractive summarization model that uses the BERT language model to extract the most important sentences from a text. It works by first embedding the sentences in the text using BERT.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

Visual language processing (VLP) is at the forefront of generative AI, driving advancements in multimodal learning that encompasses language intelligence, vision understanding, and processing. Solution overview The proposed VLP solution integrates a suite of state-of-the-art generative AI modules to yield accurate multimodal outputs.

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Topbots

JUNE 29, 2023

While you will absolutely need to go for this approach if you want to use Text2SQL on many different databases, keep in mind that it requires considerable prompt engineering effort. 4] In the open-source camp, initial attempts at solving the Text2SQL puzzle were focussed on auto-encoding models such as BERT, which excel at NLU tasks.[5,

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AWS Machine Learning Blog

DECEMBER 11, 2024

In this post, we illustrate the importance of generative AI in the collaboration between Tealium and the AWS Generative AI Innovation Center (GenAIIC) team by automating the following: Evaluating the retriever and the generated answer of a RAG system based on the Ragas Repository powered by Amazon Bedrock.

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