Unite.AI

AUGUST 8, 2023

Generative AI Types: Text to Text, Text to Image Transformers & LLM The paper “ Attention Is All You Need ” by Google Brain marked a shift in the way we think about text modeling. Large Language Models (LLMs) like GPT-4, Bard, and LLaMA, are colossal constructs designed to decipher and generate human language, code, and more.

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243

Unite.AI

JANUARY 11, 2024

More recent methods based on pre-trained language models like BERT obtain much better context-aware embeddings. Existing methods predominantly use smaller BERT-style architectures as the backbone model. They are unable to take advantage of more advanced LLMs and related techniques. Adding it provided negligible improvements.

Large Language Models 147

Large Language Models Prompt Engineering Prompt Engineer BERT 147

Flipboard

DECEMBER 6, 2023

Tools like LangChain , combined with a large language model (LLM) powered by Amazon Bedrock or Amazon SageMaker JumpStart , simplify the implementation process. Types of summarizations There are several techniques to summarize text, which are broadly categorized into two main approaches: extractive and abstractive summarization.

BERT 167

BERT Large Language Models Artificial Intelligence Artificial Intelligence 167

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

Marktechpost

SEPTEMBER 15, 2024

Large Language Models (LLMs) have revolutionized natural language processing in recent years. 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. SMs play a crucial role in enhancing LLMs through data curation.

BERT 120

BERT LLM Large Language Models Categorization 120

AWS Machine Learning Blog

JUNE 25, 2024

Manually analyzing and categorizing large volumes of unstructured data, such as reviews, comments, and emails, is a time-consuming process prone to inconsistencies and subjectivity. The raw data is processed by an LLM using a preconfigured user prompt. The LLM generates output based on the user prompt.

Automation 124

Automation Prompt Engineering Prompt Engineer Categorization 124

Snorkel AI

DECEMBER 27, 2023

While large language models (LLMs) have claimed the spotlight since the debut of ChatGPT, BERT language models have quietly handled most enterprise natural language tasks in production. As foundation models , large LLMs like GPT-4 and Gemini consolidate internet-scale text datasets and excel at a wide range of tasks.

BERT 52

BERT NLP Data Scientist Large Language Models 52

Marktechpost

JANUARY 4, 2024

The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. Meet ‘Unicron,’ a novel system that Alibaba Group and Nanjing University researchers developed to enhance and streamline the LLM training process.

Computational Linguistics 120

Computational Linguistics Large Language Models LLM BERT 120

AWS Machine Learning Blog

AUGUST 7, 2023

AWS received about 100 samples of labeled data from the customer, which is a lot less than the 1,000 samples recommended for fine-tuning an LLM in the data science community. The solution was to find and fine-tune an LLM to classify toxic language. LLMs are truly capable of learning from internet-scale data.

Large Language Models 90

Large Language Models LLM BERT ML 90

Marktechpost

JULY 4, 2023

Natural language processing (NLP) activities, including speech-to-text, sentiment analysis, text summarization, spell-checking, token categorization, etc., 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.

Large Language Models 104

Large Language Models BERT Natural Language Processing Categorization 104

Marktechpost

SEPTEMBER 6, 2024

The primary issue lies in the substantial computational costs of LLM-based augmentation, resulting in high power consumption and CO2 emissions. Researchers need help with the need to balance the improved performance of LLM-augmented classifiers against their environmental and economic costs. and Llama-3-8B.

LLM 57

LLM BERT Large Language Models Categorization 57

Unite.AI

AUGUST 28, 2023

Systems like ChatGPT by OpenAI, BERT, and T5 have enabled breakthroughs in human-AI communication. link] The process can be categorized into three agents: Execution Agent : The heart of the system, this agent leverages OpenAI’s API for task processing.

Auto-complete 240

Auto-complete ChatGPT Large Language Models Neural Network 240

The MLOps Blog

SEPTEMBER 26, 2024

TL;DR Hallucinations are an inherent feature of LLMs that becomes a bug in LLM-based applications. This “making up” event is what we call a hallucination, a term popularized by Andrej Karpathy in 2015 in the context of RNNs and extensively used nowadays for large language models (LLMs). What are LLM hallucinations?

LLM 72

LLM Prompt Engineering Prompt Engineer Auto-complete 72

AWS Machine Learning Blog

OCTOBER 30, 2024

We showcase two different sentence transformers, paraphrase-MiniLM-L6-v2 and a proprietary Amazon large language model (LLM) called M5_ASIN_SMALL_V2.0 , and compare their results. M5 LLMS are BERT-based LLMs fine-tuned on internal Amazon product catalog data using product title, bullet points, description, and more.

BERT 92

BERT Categorization Data Scientist Machine Learning 92

Marktechpost

SEPTEMBER 9, 2024

NLI models offer significant advantages in terms of efficiency, as they can operate with much smaller parameter counts compared to generative LLMs. For instance, a BERT model with 86 million parameters can perform NLI tasks, while the smallest effective zero-shot generative LLMs require 7-8 billion parameters. Also, Claude 3.5

BERT 104

BERT Large Language Models LLM Categorization 104

AWS Machine Learning Blog

APRIL 25, 2024

It uses BERT, a popular NLP technique, to understand the meaning and context of words in the candidate summary and reference summary. The more similar the words and meanings captured by BERT, the higher the BERTScore. It uses neural networks like BERT to measure semantic similarity beyond just exact word or phrase matching.

BERT 131

BERT NLP Algorithm Neural Network 131

AWS Machine Learning Blog

NOVEMBER 1, 2023

Combined with large language models (LLM) and Contrastive Language-Image Pre-Training (CLIP) trained with a large quantity of multimodality data, visual language models (VLMs) are particularly adept at tasks like image captioning, object detection and segmentation, and visual question answering.

Auto-classification 117

Auto-classification LLM Auto-complete Generative AI 117

Becoming Human

MARCH 12, 2024

By extracting information, identifying patterns, and categorizing content within minutes, these tools enhance efficiency for legal professionals. By creating custom LLM-based applications using clients’ proprietary legal data, ZBrain optimizes legal research workflows, ensuring operational efficiency and delivering improved legal insights.

Automation 105

Automation NLP Artificial Intelligence Artificial Intelligence 105

Snorkel AI

AUGUST 17, 2023

Its categorical power is brittle. Even if the total text length fits within the context window, users may want to avoid in-context learning for tasks with high cardinality; when using LLM APIs, users pay by the token. Sends the prompt to the LLM. Over thousands of executions, those extra tokens can add up.

Generative AI 52

Generative AI BERT LLM Prompt Engineering 52

Snorkel AI

AUGUST 17, 2023

Its categorical power is brittle. Even if the total text length fits within the context window, users may want to avoid in-context learning for tasks with high cardinality; when using LLM APIs, users pay by the token. Sends the prompt to the LLM. Over thousands of executions, those extra tokens can add up.

Generative AI 52

Generative AI BERT LLM Prompt Engineering 52

Snorkel AI

AUGUST 17, 2023

Its categorical power is brittle. Even if the total text length fits within the context window, users may want to avoid in-context learning for tasks with high cardinality; when using LLM APIs, users pay by the token. Sends the prompt to the LLM. Over thousands of executions, those extra tokens can add up.

Generative AI 52

Generative AI BERT LLM Prompt Engineering 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

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

Mlearning.ai

OCTOBER 2, 2023

It also serves as a powerful lever for refining the abilities of LLMs. Famous models like BERT and others, begin their journey with initial training on massive datasets encompassing vast swaths of internet text. So as you can see above in the picture the taxonomy can be broadly categorized into: 1.

Large Language Models 98

Large Language Models BERT Categorization LLM 98

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

Viso.ai

JULY 18, 2024

If a computer program is trained on enough data such that it can analyze, understand, and generate responses in natural language and other forms of content, it is called a Large Language Model (LLM). An easy way to describe LLM is an AI algorithm capable of understanding and generating human language.

Large Language Models 52

Large Language Models Neural Network Natural Language Processing BERT 52

John Snow Labs

OCTOBER 19, 2023

How to use the LangTest library to evaluate LLM for bias using CrowS-Pairs dataset? report() Output of the.report() In this snippet, we defined the task as crows-pairs , the model as bert-base-uncased from huggingface , and the data as CrowS-Pairs. We can check the detailed results using .generated_results()

BERT 52

BERT NLP Natural Language Processing Python 52

Topbots

JULY 6, 2023

Like other large language models, including BERT and GPT-3, LaMDA is trained on terabytes of text data to learn how words relate to one another and then predict what words are likely to come next. The second pre-training stage performs vision-to-language generative learning by connecting the output of the Q-Former to a frozen LLM.

LLM 52

LLM Large Language Models Natural Language Processing NLP 52

Topbots

OCTOBER 4, 2023

Here are a few examples across various domains: Natural Language Processing (NLP) : Predictive NLP models can categorize text into predefined classes (e.g., For example, large language models (LLMs) are trained by randomly replacing some of the tokens in training data with a special token, such as [MASK].

Generative AI 119

Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 119

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. For businesses to get the greatest value out of an LLM, they need to customize it with their proprietary data—something Snorkel can help with.

Large Language Models 52

Large Language Models Natural Language Processing LLM AI 52

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. For businesses to get the greatest value out of an LLM, they need to customize it with their proprietary data—something Snorkel can help with.

Large Language Models 52

Large Language Models Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. For businesses to get the greatest value out of an LLM, they need to customize it with their proprietary data—something Snorkel can help with.

Large Language Models 52

Large Language Models Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. For businesses to get the greatest value out of an LLM, they need to customize it with their proprietary data—something Snorkel can help with.

Large Language Models 52

Large Language Models Natural Language Processing Artificial Intelligence Artificial Intelligence 52

John Snow Labs

APRIL 18, 2024

Specifically, our aim is to facilitate standardized categorization for enhanced medical data analysis and interpretation. Spark NLP & LLM The Healthcare Library is a powerful component of John Snow Labs’ Spark NLP platform, designed to facilitate NLP tasks within the healthcare domain. In the latest release, v5.3.0,

NLP 40

NLP BERT Categorization Automation 40

John Snow Labs

APRIL 22, 2024

Spark NLP & LLM The Healthcare Library is a powerful component of John Snow Labs’ Spark NLP platform, designed to facilitate NLP tasks within the healthcare domain. When applied to new unlabeled files, the models can categorize them at high accuracy. setInputCol("text").setOutputCol("document")

NLP 64

NLP Categorization Natural Language Processing BERT 64

Bugra Akyildiz

MARCH 24, 2024

RWKV (pronounced as RWaKuV) is an RNN with GPT-level LLM performance, which can also be directly trained like a GPT transformer (parallelizable). Despite extensive research on traditional machine learning models, there has been limited work studying MIA on the pre-training data of large language models (LLMs). Reference-based ( ref ).

Machine Learning 52

Machine Learning Algorithm Data Scientist LLM 52

Dlabs.ai

NOVEMBER 2, 2023

Case study: Creating an LLM-based application using LLM-based tools To best illustrate how LLM-based tools can be used, let me use a real-life example. We tried Vectara, an LLM-based platform for search. BERT), GPT is a generative model. Step 5: LLM customization 5.1. But why settle on GPT?

ChatGPT 52

ChatGPT LLM Artificial Intelligence Artificial Intelligence 52