IBM Journey to AI blog

FEBRUARY 13, 2024

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. The result will be unusable if a user prompts the model to write a factual news article.

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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. LLMs can perform many types of language tasks, such as translating languages, analyzing sentiments, chatbot conversations etc.

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Artificial Corner

JULY 30, 2023

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. Prompt engineering is a technique used in artificial intelligence to optimize and refine language models for specific activities and intended outcomes.

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ODSC - Open Data Science

NOVEMBER 8, 2023

Do you want a chatbot, a Q&A system, or an image generator? Prompt Engineering Another buzzword you’ve likely heard of lately, prompt engineering means designing inputs for LLMs once they’re developed. You can even fine-tune prompts to get exactly what you want. Plan accordingly!

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Unite.AI

AUGUST 28, 2023

These AI agents, transcending chatbots and voice assistants, are shaping a new paradigm for both industries and our daily lives. Chatbots & Early Voice Assistants : As technology evolved, so did our interfaces. Tools like Siri, Cortana, and early chatbots simplified user-AI interaction but had limited comprehension and capability.

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Auto-complete ChatGPT Large Language Models AI 240

Heartbeat

AUGUST 2, 2023

Large language models, such as GPT-3 (Generative Pre-trained Transformer 3), BERT, XLNet, and Transformer-XL, etc., It has become the backbone of many successful language models, like GPT-3, BERT, and their variants. They are usually trained on a massive amount of text data. Benefits of Using Language Models 1.

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Large Language Models Prompt Engineer Prompt Engineering OpenAI 52

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

FEBRUARY 13, 2024

The student model could be a simple model like logistic regression or a foundation model like BERT. In a Snorkel case study classifying user intents for a banking chatbot, our engineers started with labels from Google’s PaLM 2 to achieve an F1 of 50 as a baseline.

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Snorkel AI

FEBRUARY 13, 2024

The student model could be a simple model like logistic regression or a foundation model like BERT. In a Snorkel case study classifying user intents for a banking chatbot, our engineers started with labels from Google’s PaLM 2 to achieve an F1 of 50 as a baseline.

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LLM Data Scientist Neural Network Data Science 52

Pickl AI

SEPTEMBER 21, 2023

The early days of language models can be traced back to programs like ELIZA , a rudimentary chatbot developed in the 1960s, and continued with ALICE in the 1990s. Transformers, like BERT and GPT, brought a novel architecture that excelled at capturing contextual relationships in language. What is ChatGPT used for?

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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. To cover as many breakthroughs as possible we have broken down our review in four parts: ?

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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. Mass propaganda via coordinated networks of chatbots on social media platforms, aiming at distorting public discourse. months on average.

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Large Language Models Neural Network LLM Chatbots 130

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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Large Language Models BERT Neural Network LLM 52

Heartbeat

MARCH 19, 2024

LLM use cases range from chatbots and virtual assistants to content generation and translation services. Like machine learning operations, LLMOps involves efforts from several contributors, like prompt engineers, data scientists, DevOps engineers, business analysts, and IT operations.

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Large Language Models Prompt Engineer Prompt Engineering Natural Language Processing 52

Chatbots Life

MAY 12, 2023

There are many approaches to language modelling, we can for example ask the model to fill in the words in the middle of a sentence (as in the BERT model) or predict which words have been swapped for fake ones (as in the ELECTRA model). Prompt Engineering As mentioned above we can use ChatGPT to perform a number of different NLP tasks.

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ChatGPT Software Engineer NLP Prompt Engineer 105

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. Some of them are more geared and tuned toward actual question answering, or a chatbot kind of interaction. Then comes prompt engineering.

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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. Some of them are more geared and tuned toward actual question answering, or a chatbot kind of interaction. Then comes prompt engineering.

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Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

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. A great resource available through Hugging Face is the Open LLM Leaderboard.

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Unite.AI

AUGUST 8, 2023

These advances have fueled applications in document creation, chatbot dialogue systems, and even synthetic music composition. Information Retrieval: Using LLMs, such as BERT or GPT, as part of larger architectures to develop systems that can fetch and categorize information. Recent Big-Tech decisions underscore its significance.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

TGI’s versatility extends across domains, enhancing chatbots, improving machine translations, summarizing texts, and generating diverse content, from poetry to code. accuracy on the development set, while its counterpart bert-base-uncased boasts an accuracy of 92.7%. This model achieves a 91.3%

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Auto-classification LLM Auto-complete Generative AI 92

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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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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