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.

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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?

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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.

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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,

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Generative AI LLM Prompt Engineer Prompt Engineering 85

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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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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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.,

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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.,

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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.

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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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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.

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Large Language Models Prompt Engineer Prompt Engineering Natural Language Processing 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.

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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.

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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.

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Large Language Models Prompt Engineer Prompt Engineering Neural Network 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.

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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.

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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.

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Large Language Models NLP Prompt Engineer Prompt Engineering 59

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.

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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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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.

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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?

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AWS Machine Learning Blog

NOVEMBER 1, 2023

accuracy on the development set, while its counterpart bert-base-uncased boasts an accuracy of 92.7%. He is a dedicated applied AI/ML researcher, concentrating on CV, NLP, and multimodality. This model achieves a 91.3% The Hugging Face Hub provides access to over 1,000 pre-trained text classification models.

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Topbots

JUNE 6, 2023

In October 2022, I published an article on LLM selection for specific NLP use cases , such as conversation, translation and summarisation. Developers can now focus on efficient prompt engineering and quick app prototyping.[11] Open-source competes with for-profits, spurring innovation in LLM efficiency and scaling.

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