Unite.AI

JANUARY 11, 2024

They serve as a core building block in many natural language processing (NLP) applications today, including information retrieval, question answering, semantic search and more. More recent methods based on pre-trained language models like BERT obtain much better context-aware embeddings. Adding it provided negligible improvements.

Large Language Models 147

Large Language Models Prompt Engineer Prompt Engineering BERT 147

Unite.AI

JANUARY 23, 2024

Unlike traditional NLP models which rely on rules and annotations, LLMs like GPT-3 learn language skills in an unsupervised, self-supervised manner by predicting masked words in sentences. Their foundational nature allows them to be fine-tuned for a wide variety of downstream NLP tasks. This enables pretraining at scale.

Large Language Models 130

Large Language Models Prompt Engineering Prompt Engineer LLM 130

Ehud Reiter

AUGUST 25, 2024

Many people in NLP seem to think that you need to work with the latest and trendiest technology in order to be relevant, both in research and in applications. At the time, the latest and trendiest NLP technology was LSTM (and variants such as biLSTM). LSTMs worked very well in lots of areas of NLP, including machine translation.

BERT 135

BERT NLP Natural Language Processing Prompt Engineer 135

Towards AI

DECEMBER 28, 2023

The introduction of attention mechanisms has notably altered our approach to working with deep learning algorithms, leading to a revolution in the realms of computer vision and natural language processing (NLP). Major language models like GPT-3 and BERT often come with Python APIs, making it easy to integrate them into various applications.

Large Language Models 108

Large Language Models Natural Language Processing Prompt Engineering Prompt Engineer 108

Marktechpost

JUNE 24, 2024

The study also identified four essential skills for effectively interacting with and leveraging ChatGPT: prompt engineering, critical evaluation of AI outputs, collaborative interaction with AI, and continuous learning about AI capabilities and limitations.

ChatGPT 114

ChatGPT Generative AI BERT AI 114

Artificial Corner

JULY 30, 2023

Natural Language Processing (NLP) is a subfield of artificial intelligence. 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. BERT (Bidirectional Encoder Representations from Transformers) — developed by Google.

Large Language Models 85

Large Language Models LLM Natural Language Processing Deep Learning 85

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

JUNE 25, 2024

Unlike traditional natural language processing (NLP) approaches, such as classification methods, LLMs offer greater flexibility in adapting to dynamically changing categories and improved accuracy by using pre-trained knowledge embedded within the model.

Automation 123

Automation Prompt Engineering Prompt Engineer Categorization 123

ODSC - Open Data Science

NOVEMBER 8, 2023

In this blog, we’ll explore ten key aspects of building generative AI applications, including large language model basics, fine-tuning, and core NLP competencies. Prompt Engineering Another buzzword you’ve likely heard of lately, prompt engineering means designing inputs for LLMs once they’re developed.

Generative AI 52

Generative AI Prompt Engineering Prompt Engineer LLM 52

The MLOps Blog

FEBRUARY 15, 2024

Due to the rise of LLMs and the shift towards pre-trained models and prompt engineering, specialists in traditional NLP approaches are particularly at risk. Data scientists and NLP specialists can move towards analytical roles or into engineering to stay relevant. Who are the people most at risk of being laid off?

NLP 59

NLP Natural Language Processing Data Scientist Software Engineer 59

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. Transformers and Advanced NLP Models : The introduction of transformer architectures revolutionized the NLP landscape.

Auto-complete 240

Auto-complete ChatGPT Large Language Models Neural Network 240

Towards AI

JANUARY 30, 2024

GPT4, Stable Diffusion, Llama, BERT, Gemini Large Language Models (LLMs) Foundation models, trained on the “Transformer Architecture”, that can perform a wide array of Natural Language Processing (NLP) tasks like text generation, classification, summarisation etc. Examples: GPT 3.5,

Generative AI 86

Generative AI LLM Prompt Engineering Prompt Engineer 86

deepsense.ai

FEBRUARY 6, 2024

Prompt engineering : the provided prompt plays a crucial role, especially when dealing with compound nouns. By using “car lamp” as a prompt, we are very likely to detect cars instead of car lamps. SegGPT Many successful approaches from NLP are now being translated into computer vision. Source: own study.

Prompt Engineering 105

Prompt Engineering Prompt Engineer NLP Computer Vision 105

Unite.AI

SEPTEMBER 25, 2023

However, as technology advanced, so did the complexity and capabilities of AI music generators, paving the way for deep learning and Natural Language Processing (NLP) to play pivotal roles in this tech. Initially, the attempts were simple and intuitive, with basic algorithms creating monotonous tunes.

Generative AI 296

Generative AI Deep Learning Algorithm AI 296

Heartbeat

MARCH 19, 2024

Like machine learning operations, LLMOps involves efforts from several contributors, like prompt engineers, data scientists, DevOps engineers, business analysts, and IT operations. This is, in fact, a baseline, and the actual LLMOps workflow usually involves more stakeholders like prompt engineers, researchers, etc.

Large Language Models 52

Large Language Models Prompt Engineering Prompt Engineer Natural Language Processing 52

IBM Journey to AI blog

FEBRUARY 13, 2024

They are now capable of natural language processing ( NLP ), grasping context and exhibiting elements of creativity. The quality of outputs depends heavily on training data, adjusting the model’s parameters and prompt engineering, so responsible data sourcing and bias mitigation are crucial.

Generative AI 354

Generative AI AI AI Chatbots 354

Snorkel AI

AUGUST 17, 2023

Users can easily constrain an LLM’s output with clever prompt engineering. When prompted for a classification task, a genAI LLM may give a reasonable baseline, but prompt engineering and fine-tuning can only take you so far. BERT for misinformation. In-context learning. A GPT-3 model—82.5%

Generative AI 52

Generative AI BERT LLM Prompt Engineering 52

Chatbots Life

MAY 12, 2023

As everything is explained from scratch but extensively I hope you will find it interesting whether you are NLP Expert or just want to know what all the fuss is about. We will discuss how models such as ChatGPT will affect the work of software engineers and ML engineers.

ChatGPT 105

ChatGPT Software Engineer NLP Prompt Engineer 105

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.

Automation 82

Automation Python BERT Prompt Engineer 82

Snorkel AI

MAY 25, 2023

BERT, the first breakout large language model In 2019, a team of researchers at Goole introduced BERT (which stands for bidirectional encoder representations from transformers). By making BERT bidirectional, it allowed the inputs and outputs to take each others’ context into account. BERT), or consist of both (e.g.,

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

Snorkel AI

MAY 25, 2023

BERT, the first breakout large language model In 2019, a team of researchers at Goole introduced BERT (which stands for bidirectional encoder representations from transformers). By making BERT bidirectional, it allowed the inputs and outputs to take each others’ context into account. BERT), or consist of both (e.g.,

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

Explosion

MAY 17, 2023

But if you’re working on the same sort of Natural Language Processing (NLP) problems that businesses have been trying to solve for a long time, what’s the best way to use them? However, LLMs are not a direct solution to most of the NLP use-cases companies have been working on. That’s definitely new.

LLM 135

LLM NLP Large Language Models OpenAI 135

Heartbeat

OCTOBER 5, 2023

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. These LLMs can generate human-like text, understand context, and perform various Natural Language Processing (NLP) tasks. The focus shifts towards prompt engineering and fine-tuning.

Large Language Models 52

Large Language Models DevOps Prompt Engineering Prompt Engineer 52

AWS Machine Learning Blog

APRIL 17, 2023

Prompt engineering Prompt engineering refers to efforts to extract accurate, consistent, and fair outputs from large models, such text-to-image synthesizers or large language models. For more information, refer to EMNLP: Prompt engineering is the new feature engineering.

Prompt Engineer 96

Prompt Engineer Prompt Engineering Deep Learning Large Language Models 96

Heartbeat

JANUARY 9, 2024

Large language models have emerged as ground-breaking technologies with revolutionary potential in the fast-developing fields of artificial intelligence (AI) and natural language processing (NLP). BERT and GPT are examples. The way we create and manage AI-powered products is evolving because of LLMs.

Large Language Models 52

Large Language Models Natural Language Processing LLM Machine Learning 52

Snorkel AI

OCTOBER 17, 2023

What are the key advantages that it offers for financial NLP tasks? For years you’ve been a big leader in applying AI—generally in the NLP and AI research communities, but also specifically for finance. And, at Bloomberg, we’ve been doing NLP for a long time. You were able to share what you did with the community.

Large Language Models 52

Large Language Models NLP Prompt Engineer Prompt Engineering 52

Snorkel AI

OCTOBER 17, 2023

What are the key advantages that it offers for financial NLP tasks? For years you’ve been a big leader in applying AI—generally in the NLP and AI research communities, but also specifically for finance. And, at Bloomberg, we’ve been doing NLP for a long time. You were able to share what you did with the community.

Large Language Models 64

Large Language Models NLP Prompt Engineer Prompt Engineering 64

Snorkel AI

OCTOBER 17, 2023

What are the key advantages that it offers for financial NLP tasks? For years you’ve been a big leader in applying AI—generally in the NLP and AI research communities, but also specifically for finance. And, at Bloomberg, we’ve been doing NLP for a long time. You were able to share what you did with the community.

Large Language Models 59

Large Language Models NLP Prompt Engineer Prompt Engineering 59

Snorkel AI

MARCH 2, 2023

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. As we look at the progression, we see that these state-of-the-art NLP models are getting larger and larger over time. Then comes prompt engineering.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

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. As we look at the progression, we see that these state-of-the-art NLP models are getting larger and larger over time. Then comes prompt engineering.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

FEBRUARY 13, 2024

The student model could be a simple model like logistic regression or a foundation model like BERT. With a little prompt engineering (encouraging the LLM to behave as an expert in banking and giving one example per label), the team boosted the PaLM 2’s F1 score to 69.

LLM 52

LLM Data Scientist Neural Network Data Science 52

Applied Data Science

DECEMBER 23, 2022

In our review of 2019 we talked a lot about reinforcement learning and Generative Adversarial Networks (GANs), in 2020 we focused on Natural Language Processing (NLP) and algorithmic bias, in 202 1 Transformers stole the spotlight. Useful links: prompt OpenAI’s Dalle-2 with an online demo prompt Huggin face’s Stable diffusion with this demo.

Neural Network 52

Neural Network AI AI Data Science 52

Unite.AI

JUNE 27, 2024

Artificial Intelligence (AI) has witnessed rapid advancements over the past few years, particularly in Natural Language Processing (NLP). Two key techniques driving these advancements are prompt engineering and few-shot learning. To improve customer engagement and efficiency, they implemented IBM's Watsonx Assistant.

Prompt Engineering 147

Prompt Engineering Prompt Engineer AI Modeling Large Language Models 147

Unite.AI

SEPTEMBER 20, 2023

Transformers in NLP In 2017, Cornell University published an influential paper that introduced transformers. These are deep learning models used in NLP. Hugging Face , started in 2016, aims to make NLP models accessible to everyone. This discovery fueled the development of large language models like ChatGPT.

LLM 342

LLM BERT NLP Python 342

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.,

Generative AI 111

Generative AI Prompt Engineer Prompt Engineering ML 111

Flipboard

DECEMBER 6, 2023

Extractive summarization Extractive summarization is a technique used in NLP and text analysis to create a summary by extracting key sentences. In this post, we focus on the BERT extractive summarizer. BERT is a pre-trained language model that can be fine-tuned for a variety of tasks, including text summarization.

BERT 167

BERT Large Language Models Artificial Intelligence Artificial Intelligence 167

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. How Are LLMs Used?

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243