IBM Journey to AI blog

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” The result will be unusable if a user prompts the model to write a factual news article.

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Unite.AI

AUGUST 28, 2023

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. Neural Networks & Deep Learning : Neural networks marked a turning point, mimicking human brain functions and evolving through experience.

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Artificial Corner

JULY 30, 2023

Photo by Shubham Dhage on Unsplash Introduction Large language Models (LLMs) are a subset of Deep Learning. Some Terminologies related to Artificial Intelligence (Ai) Deep Learning is a technique used in artificial intelligence (AI) that teaches computers to interpret data in a manner modeled after the human brain.

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Unite.AI

JANUARY 23, 2024

LLMs are a class of deep learning models that are pretrained on massive text corpora, allowing them to generate human-like text and understand natural language at an unprecedented level. Prompt engineering is crucial to steering LLMs effectively. What are Large Language Models and Why are They Important?

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Large Language Models Prompt Engineering Prompt Engineer LLM 100

Mlearning.ai

JANUARY 17, 2024

350x: Application Areas , Companies, Startups 3,000+: Prompts , Prompt Engineering, & Prompt Lists 250+: Hardware, Frameworks , Approaches, Tools, & Data 300+: Achievements, Impacts on Society , AI Regulation, & Outlook 20x: What is Generative AI? Deep learning neural network.

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Generative AI Prompt Engineer Prompt Engineering Large Language Models 98

deepsense.ai

FEBRUARY 6, 2024

Harnessing the power of deep learning for image segmentation is revolutionizing numerous industries, but often encounters a significant obstacle – the limited availability of training data. Over the years, various successful deep learning architectures have been developed for this task, such as U-Net or SegFormer.

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AWS Machine Learning Blog

APRIL 17, 2023

However, as the size and complexity of the deep learning models that power generative AI continue to grow, deployment can be a challenging task. Then, we highlight how Amazon SageMaker large model inference deep learning containers (LMI DLCs) can help with optimization and deployment.

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ODSC - Open Data Science

NOVEMBER 19, 2024

Topological Deep Learning Made Easy with TopoX with Dr. Mustafa Hajij Slides In these AI slides, Dr. Mustafa Hajij introduced TopoX, a comprehensive Python suite for topological deep learning. The open-source nature of TopoX positions it as a valuable asset for anyone exploring topological deep learning.

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ODSC - Open Data Science

SEPTEMBER 18, 2023

A lot goes into learning a new skill, regardless of how in-depth it is. Getting started with natural language processing (NLP) is no exception, as you need to be savvy in machine learning, deep learning, language, and more. To get you started on your journey, we’ve released a new on-demand Introduction to NLP course.

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NLP Neural Network Deep Learning Large Language Models 52

Heartbeat

AUGUST 2, 2023

Introduction to LLMs LLM in the sphere of AI Large language models (often abbreviated as LLMs) refer to a type of artificial intelligence (AI) model typically based on deep learning architectures known as transformers. Large language models, such as GPT-3 (Generative Pre-trained Transformer 3), BERT, XLNet, and Transformer-XL, etc.,

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Large Language Models Prompt Engineer Prompt Engineering ChatGPT 52

Bugra Akyildiz

FEBRUARY 9, 2025

Prompt engineering: Carefully designing prompts to guide the model's behavior. Curriculum learning: Gradually increasing the difficulty of tasks during training. Bidirectional language understanding with BERT. Tensorgrad is a tensor & deep learning framework. PyTorch meets SymPy.

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Heartbeat

MARCH 19, 2024

Large language models are foundational, based on deep learning and artificial intelligence (AI), and are usually trained on massive datasets that create the foundation of their knowledge and abilities. Popular LLMs include Falcon 40B, GPT-4, LLaMa 2, and BERT. This is the stage at which prompt engineering is crucial.

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Large Language Models Prompt Engineering Prompt Engineer Natural Language Processing 52

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.

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Large Language Models Neural Network LLM Chatbots 130

Heartbeat

OCTOBER 5, 2023

Unsurprisingly, Machine Learning (ML) has seen remarkable progress, revolutionizing industries and how we interact with technology. The emergence of Large Language Models (LLMs) like OpenAI's GPT , Meta's Llama , and Google's BERT has ushered in a new era in this field. We pay our contributors, and we don't sell ads.

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Large Language Models DevOps Machine Learning Prompt Engineer 52

deepsense.ai

FEBRUARY 12, 2024

Harnessing the power of deep learning for image segmentation is revolutionizing numerous industries, but often encounters a significant obstacle the limited availability of training data. Over the years, various successful deep learning architectures have been developed for this task, such as U-Net or SegFormer.

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Prompt Engineer Prompt Engineering NLP Computer Vision 52

Heartbeat

JANUARY 9, 2024

BERT and GPT are examples. You can adapt foundation models to downstream tasks in the following ways: Prompt Engineering: Prompt engineering is a powerful technique that enables LLMs to be more controllable and interpretable in their outputs, making them more suitable for real-world applications with specific requirements and constraints.

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Large Language Models Natural Language Processing LLM Machine Learning 52

Applied Data Science

DECEMBER 23, 2022

This year is intense: we have, among others, a new generative model that beats GANs , an AI-powered chatbot that discusses with more than 1 million people in a week and prompt engineering , a job that did not exist a year ago. It is not surprising that it has become a major application area for deep learning.

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Heartbeat

NOVEMBER 17, 2023

Considerations for Choosing a Distance Metric for Text Embeddings: Scale or Magnitude : Embeddings from models like Word2Vec, FastText, BERT, and GPT are often normalized to unit length. We’re committed to supporting and inspiring developers and engineers from all walks of life. We pay our contributors, and we don’t sell ads.

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Snorkel AI

OCTOBER 17, 2023

Then, we had a lot of machine-learning and deep-learning engineers. The work involved in training something like a BERT model and a large language model is very similar. That knowledge transfers, but the skillset that you’re operating in, there are unique engineering challenges.

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Large Language Models NLP Prompt Engineer Prompt Engineering 64

Pickl AI

SEPTEMBER 21, 2023

Transformers, like BERT and GPT, brought a novel architecture that excelled at capturing contextual relationships in language. Techniques such as prompt engineering, context windowing, and reinforcement learning from human feedback (RLHF) are used to reduce the chances of generating harmful or biased content.

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ChatGPT Conversational AI Chatbots Natural Language Processing 52

Snorkel AI

OCTOBER 17, 2023

Then, we had a lot of machine-learning and deep-learning engineers. The work involved in training something like a BERT model and a large language model is very similar. That knowledge transfers, but the skillset that you’re operating in, there are unique engineering challenges.

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Large Language Models NLP Prompt Engineer Prompt Engineering 59

Snorkel AI

OCTOBER 17, 2023

Then, we had a lot of machine-learning and deep-learning engineers. The work involved in training something like a BERT model and a large language model is very similar. That knowledge transfers, but the skillset that you’re operating in, there are unique engineering challenges.

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Large Language Models NLP Prompt Engineer Prompt Engineering 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

SEPTEMBER 20, 2023

These are deep learning models used in NLP. Machine learning is about teaching computers to perform tasks by recognizing patterns, while deep learning, a subset of machine learning, creates a network that learns independently. We choose a BERT model fine-tuned on the SQuAD dataset.

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Unite.AI

JUNE 27, 2024

These advancements have been driven by significant breakthroughs in deep learning and the availability of large datasets, allowing models to understand and generate human-like text with significant accuracy. Two key techniques driving these advancements are prompt engineering and few-shot learning.

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Prompt Engineering Prompt Engineer AI Modeling Large Language Models 144

Unite.AI

AUGUST 8, 2023

These advanced AI deep learning models have seamlessly integrated into various applications, from Google's search engine enhancements with BERT to GitHub’s Copilot, which harnesses the capability of Large Language Models (LLMs) to convert simple code snippets into fully functional source codes.

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Marktechpost

SEPTEMBER 15, 2024

The pre-train and fine-tune paradigm, exemplified by models like ELMo and BERT, has evolved into prompt-based reasoning used by the GPT family. Techniques like Uprise and DaSLaM use lightweight retrievers or small models to optimize prompts, break down complex problems, or generate pseudo labels.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

Utilizing the latest Hugging Face LLM modules on Amazon SageMaker, AWS customers can now tap into the power of SageMaker deep learning containers (DLCs). accuracy on the development set, while its counterpart bert-base-uncased boasts an accuracy of 92.7%. He focuses on developing scalable machine learning algorithms.

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AWS Machine Learning Blog

JUNE 27, 2024

Examples include our Deep Researcher, Deep Coder, and Advisor models. After testing available open source models, we felt that the out-of-the-box capabilities and responses were insufficient with prompt engineering alone to meet our needs.

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AWS Machine Learning Blog

DECEMBER 11, 2024

Generating improved instructions for each question-and-answer pair using an automatic prompt engineering technique based on the Auto-Instruct Repository. The value of Amazon Bedrock in text generation for automatic prompt engineering and text summarization for evaluation helped tremendously in the collaboration with Tealium.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

This skill simplifies the data extraction process, allowing security analysts to conduct investigations more efficiently without requiring deep technical knowledge. We used prompt engineering guidelines to tailor our prompts to generate better responses from the LLM. A three-shot prompting strategy is used for this task.

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LLM Machine Learning ML Prompt Engineer 94

Topbots

JUNE 6, 2023

Autoencoding models, which are better suited for information extraction, distillation and other analytical tasks, are resting in the background — but let’s not forget that the initial LLM breakthrough in 2018 happened with BERT, an autoencoding model. Developers can now focus on efficient prompt engineering and quick app prototyping.[11]

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LLM ChatGPT Prompt Engineer Prompt Engineering 105

Marktechpost

NOVEMBER 14, 2024

Devvret: We started Predibase in 2021 with the mission to democratize deep learning. Initially, we believed the way to democratize deep learning would be through platforms like ours, but we were surprised by how quickly the field evolved. What I mean is introducing a real active learning process for LLMs.

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