NYU Center for Data Science

MARCH 13, 2025

Their comparative analysis included decoder-only transformers like Pythia, encoder-only models like BERT, and state space models (SSMs) like Mamba. The teams latest research expands the analysis to more models and training regimes while offering a comprehensive theoretical framework to explain why intermediate representations excel.

BERT 82

BERT Large Language Models Explainability LLM 82

Unite.AI

MAY 8, 2024

However, some key limitations of traditional GNN-based self-supervised methods remain, which we will explore leveraging LLMs to address next. Beyond better text encoders, LLMs can be used to generate augmented information from the original text attributes in a semi-supervised manner.

Neural Network 182

Neural Network Large Language Models LLM BERT 182

TheSequence

NOVEMBER 26, 2024

An analysis of the MT-BERT multi-teacher distillation method. A review of the Portkey framework for LLM guardrailing. 💡 ML Concept of the Day: Understanding Multi-Teacher Distillation Distillation is typically explained using a teacher-student architecture, where we often conceptualize it as involving a single teacher model.

BERT 59

BERT Explainability LLM ML 59

Explosion

MAY 17, 2023

In 2014 I started working on spaCy , and here’s an excerpt of how I explained the motivation for the library: Computers don’t understand text. I don’t want to undersell how impactful LLMs are for this sort of use-case. You can give an LLM a group of comments and ask it to summarize the texts or identify key themes.

LLM 135

LLM NLP Large Language Models OpenAI 135

Marktechpost

APRIL 21, 2024

Introduction to Generative AI: This course provides an introductory overview of Generative AI, explaining what it is and how it differs from traditional machine learning methods. It introduces learners to responsible AI and explains why it is crucial in developing AI systems.

Artificial Intelligence 137

Artificial Intelligence Artificial Intelligence BERT Large Language Models 137

Artificial Corner

JULY 30, 2023

In this world of complex terminologies, someone who wants to explain Large Language Models (LLMs) to some non-tech guy is a difficult task. So that’s why I tried in this article to explain LLM in simple or to say general language. No need to train the LLM but one only has to think about Prompt design.

Large Language Models 98

Large Language Models LLM Natural Language Processing Deep Learning 98

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. Introduction to Generative AI This introductory microlearning course explains Generative AI, its applications, and its differences from traditional machine learning.

Artificial Intelligence 130

Artificial Intelligence Artificial Intelligence BERT Computer Vision 130

Flipboard

FEBRUARY 16, 2023

In this post, we use a Hugging Face BERT-Large model pre-training workload as a simple example to explain how to useTrn1 UltraClusters. Launch your training job We use the Hugging Face BERT-Large Pretraining Tutorial as an example to run on this cluster. Each compute node has Neuron tools installed, such as neuron-top.

Large Language Models 132

Large Language Models LLM BERT Deep Learning 132

IBM Journey to AI blog

AUGUST 1, 2023

A specific kind of foundation model known as a large language model (LLM) is trained on vast amounts of text data for NLP tasks. BERT (Bi-directional Encoder Representations from Transformers) is one of the earliest LLM foundation models developed. An open-source model, Google created BERT in 2018.

Generative AI 176

Generative AI Data Scientist Machine Learning BERT 176

Unite.AI

AUGUST 1, 2023

Paper Title: "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding" Key Takeaway: Introduced BERT, showcasing the efficacy of pre-training deep bidirectional models, thereby achieving state-of-the-art results on various NLP tasks. This demonstrates a classic case of ‘knowledge conflict'.

Prompt Engineering 246

Prompt Engineering Prompt Engineer ChatGPT Convolutional Neural Networks 246

Marktechpost

APRIL 1, 2024

Although large language models (LLMs) had been developed prior to the launch of ChatGPT, the latter’s ease of accessibility and user-friendly interface took the adoption of LLM to a new level. It provides codes for working with various models, such as GPT-4, BERT, T5, etc., and explains how they work.

ChatGPT 114

ChatGPT Large Language Models Prompt Engineer Prompt Engineering 114

Marek Rei

NOVEMBER 4, 2024

link] The paper investigates LLM robustness to prompt perturbations, measuring how much task performance drops for different models with different attacks. link] The paper proposes query rewriting as the solution to the problem of LLMs being overly affected by irrelevant information in the prompts. ArXiv 2023. Oliveira, Lei Li.

Machine Learning 80

Machine Learning NLP Large Language Models LLM 80

AssemblyAI

JUNE 27, 2023

In this article, we take an overview of some exciting new advances in the space of Generative AI for audio that have all happened in the past few months , explaining where the key ideas come from and how they come together to bring audio generation to a new level. This blog post is part of a series on generative AI.

Generative AI 298

Generative AI BERT Neural Network AI 298

Marktechpost

NOVEMBER 22, 2023

An embedding similarity search looks at the embeddings of previously trained models (like BERT) to discover related and maybe polluted cases. In addition, there is a developing trend in model training that uses synthetic data generated by LLMs (e.g., However, its precision is somewhat low. It’s also found that GPT-3.5’s

Large Language Models 120

Large Language Models BERT LLM Explainability 120

Marktechpost

APRIL 16, 2024

LangChain is an open-source framework that allows developers to build LLM-based applications easily. It provides for easily connecting LLMs with external data sources to augment the capabilities of these models and achieve better results. It teaches how to build LLM-powered applications using LangChain using hands-on exercises.

Large Language Models 103

Large Language Models Auto-complete Prompt Engineering Prompt Engineer 103

Ehud Reiter

AUGUST 25, 2024

I remember once trying to carefully explain why an LSTM approach was not appropriate for what a potential client wanted to do, and the response was “I’m a techie and I agree with you, but my manager insists that we have to use LSTMs because this is what everyone is talking about.”

BERT 135

BERT NLP Natural Language Processing Prompt Engineer 135

ODSC - Open Data Science

SEPTEMBER 6, 2023

Most people who have experience working with large language models such as Google’s Bard or OpenAI’s ChatGPT have worked with an LLM that is general, and not industry-specific. This is why over the last few months multiple examples of domain/industry-specific LLMs have gone live. Well, that’s what CaseHOLD does. So what does it do?

Large Language Models 98

Large Language Models NLP LLM BERT 98

Marktechpost

JULY 4, 2023

Applications of LLMs The chart below summarises the present state of the Large Language Model (LLM) landscape in terms of features, products, and supporting software. ” Even for seasoned programmers, the syntax of shell commands might need to be explained. It is pre-trained using a generalized autoregressive model.

Large Language Models 103

Large Language Models BERT Natural Language Processing Categorization 103

AWS Machine Learning Blog

JUNE 25, 2024

Whether you’re a developer seeking to incorporate LLMs into your existing systems or a business owner looking to take advantage of the power of NLP, this post can serve as a quick jumpstart. Explainability Provides explanations for its predictions through generated text, offering insights into its decision-making process.

Automation 124

Automation Prompt Engineer Prompt Engineering Categorization 124

Towards AI

AUGUST 10, 2023

Applying LLMs to make E-commerce search engines robust to colloquial queries Photo by Oberon Copeland @veryinformed.com on Unsplash In recent years, web search engines have been quickly embracing Large Language Models (LLMs) to increase their search capability. One of the most successful examples is Google search powered by BERT [1].

LLM 98

LLM BERT Large Language Models Explainability 98

Heartbeat

SEPTEMBER 12, 2023

Implementing end-to-end deep learning projects has never been easier with these awesome tools Image by Freepik LLMs such as GPT, BERT, and Llama 2 are a game changer in AI. Here are the topics we’ll cover in this article: Fine-tuning the BERT model with the Transformers library for text classification.

BERT 52

BERT Deep Learning Machine Learning ML 52

Mlearning.ai

JUNE 14, 2023

Learning Large Language Models The LLM (Foundational Models) space has seen tremendous and rapid growth. I used this foolproof method of consuming the right information and ended up publishing books , artworks , Podcasts and even an LLM powered consumer facing app ranked #40 on the app store. Transformer Neural Networks — EXPLAINED!

Neural Network 52

Neural Network BERT Large Language Models Natural Language Processing 52

AWS Machine Learning Blog

DECEMBER 22, 2023

We start off with a baseline foundation model from SageMaker JumpStart and evaluate it with TruLens , an open source library for evaluating and tracking large language model (LLM) apps. These functions can be implemented in several ways, including BERT-style models, appropriately prompted LLMs, and more. args.args[0]).on(Select.Record.calls[0].args.args[1])

LLM 117

LLM Large Language Models BERT Prompt Engineer 117

Chatbots Life

AUGUST 23, 2024

The use cases of LLM for chatbots and LLM for conversational AI can be seen across all industries like FinTech, eCommerce, healthcare, cybersecurity, and the list goes on. The next section explains in detail how LLM-powered chatbot solutions help businesses enhance their customer experience.

Conversational AI 72

Conversational AI Chatbots Large Language Models LLM 72

Flipboard

JULY 10, 2023

Examples of LLMs include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representations from Transformers). LLMs are trained on massive amounts of data, often billions of words, to develop a broad understanding of language.

Large Language Models 65

Large Language Models Deep Learning Natural Language Processing BERT 65

Snorkel AI

MARCH 1, 2023

BERT BERT, an acronym that stands for “Bidirectional Encoder Representations from Transformers,” was one of the first foundation models and pre-dated the term by several years. BERT proved useful in several ways, including quantifying sentiment and predicting the words likely to follow in unfinished sentences.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

ODSC - Open Data Science

FEBRUARY 14, 2023

Some examples of large language models include GPT (Generative Pre-training Transformer), BERT (Bidirectional Encoder Representations from Transformers), and RoBERTa (Robustly Optimized BERT Approach). Researchers are developing techniques to make LLM training more efficient.

ChatGPT 124

ChatGPT Large Language Models OpenAI Conversational AI 124

Mlearning.ai

JUNE 8, 2023

Hidden secret to empower semantic search This is the third article of building LLM-powered AI applications series. From the previous article , we know that in order to provide context to LLM, we need semantic search and complex query to find relevant context (traditional keyword search, full-text search won’t be enough).

Machine Learning 52

Machine Learning BERT Neural Network OpenAI 52

Snorkel AI

SEPTEMBER 21, 2023

Pre-trained LLMs can be limited by the low quality of their data sources and struggle to adapt to domain-specific tasks. They can be limited in their multi-modality, and they can be difficult to explain, adapt, or control. Starting from an LLM pre-trained on EMR/EHR data, like ehrBERT, UCSF-Bert, and GatorTron, can speed this process.

BERT 64

BERT Data Scientist Natural Language Processing AI 64

deepsense.ai

OCTOBER 8, 2023

We compare the existing solutions and explain how they work behind the scenes. Introduction While the concept of AI agents has been around for decades, it is undeniable that recent advancements in Large Language Models (LLMs) have revolutionized this field, opening up a whole new realm of possibilities and applications.

Auto-complete 111

Auto-complete LLM Software Engineer AI 111

Snorkel AI

MAY 25, 2023

At inference time, users provide “prompts” to the LLM—snippets of text that the model uses as a jumping-off point. 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). The new tool caused a stir.

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

Snorkel AI

MAY 25, 2023

At inference time, users provide “prompts” to the LLM—snippets of text that the model uses as a jumping-off point. 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). The new tool caused a stir.

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

AWS Machine Learning Blog

JULY 24, 2023

Inf2 instances are ideal for Deep Learning workloads like Generative AI, Large Language Models (LLM) in OPT/GPT family and vision transformers like Stable Diffusion. Also in this folder, we provide all the scripts necessary to trace a bert-base-uncased model on AWS Inferentia. code as the entry point. The fastapi-server.py

BERT 92

BERT Deep Learning Python Machine Learning 92

Snorkel AI

SEPTEMBER 21, 2023

Pre-trained LLMs can be limited by the low quality of their data sources and struggle to adapt to domain-specific tasks. They can be limited in their multi-modality, and they can be difficult to explain, adapt, or control. Starting from an LLM pre-trained on EMR/EHR data, like ehrBERT, UCSF-Bert, and GatorTron, can speed this process.

BERT 59

BERT Data Scientist Natural Language Processing AI 59

Heartbeat

MAY 29, 2023

LLMs like GPT-3 and T5 have already shown promising results in various NLP tasks such as language translation, question-answering, and summarization. However, LLMs are complex, and training and improving them require specific skills and knowledge. LLMs rely on vast amounts of text data to learn patterns and generate coherent text.

Large Language Models 78

Large Language Models Machine Learning LLM Natural Language Processing 78

Snorkel AI

SEPTEMBER 21, 2023

Pre-trained LLMs can be limited by the low quality of their data sources and struggle to adapt to domain-specific tasks. They can be limited in their multi-modality, and they can be difficult to explain, adapt, or control. Starting from an LLM pre-trained on EMR/EHR data, like ehrBERT, UCSF-Bert, and GatorTron, can speed this process.

Data Scientist 52

Data Scientist BERT Natural Language Processing AI 52

deepsense.ai

NOVEMBER 9, 2024

On the other hand, the more demanding the task – the higher the risk of LLM hallucinations. In this article, you’ll find: what the problem with hallucination is, which techniques we use to reduce them, how to measure hallucinations using methods such as LLM-as-a-judge tips and tricks from my experience as an experienced data scientist.

Prompt Engineer 59

Prompt Engineer Prompt Engineering LLM ChatGPT 59