Unite.AI

JANUARY 11, 2024

Text embeddings are vector representations of words, sentences, paragraphs or documents that capture their semantic meaning. vector embedding Recent advances in large language models (LLMs) like GPT-3 have shown impressive capabilities in few-shot learning and natural language generation.

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Large Language Models Prompt Engineering Prompt Engineer BERT 147

Marktechpost

JULY 9, 2024

Some approaches focus on aligning retrievers with LLM needs, while others explore multi-step retrieval processes or context-filtering methods. Instruction-tuning techniques have been developed to enhance both search capabilities and the RAG performance of LLMs. The 8B parameter version consistently outperforms ChatQA-1.5

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LLM Large Language Models Natural Language Processing BERT 130

Marktechpost

NOVEMBER 19, 2024

LLMs, like GPT-4 and Llama 3, have shown promise in handling such tasks due to their advanced language comprehension. Current LLM-based methods for anomaly detection include prompt engineering, which uses LLMs in zero/few-shot setups, and fine-tuning, which adapts models to specific datasets.

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Large Language Models BERT Prompt Engineer Prompt Engineering 74

Unite.AI

MAY 29, 2024

Source: A pipeline on Generative AI This figure of a generative AI pipeline illustrates the applicability of models such as BERT, GPT, and OPT in data extraction. These LLMs can perform various NLP operations, including data extraction. LLMs like GPT, BERT, and OPT have harnessed transformers technology.

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Data Extraction Neural Network Large Language Models NLP 273

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 training examples are needed in LLM Development but it’s needed in Traditional Development.

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Large Language Models LLM Natural Language Processing Deep Learning 85

Marktechpost

APRIL 25, 2024

In this article, we delve into 25 essential terms to enhance your technical vocabulary and provide insights into the mechanisms that make LLMs so transformative. Heatmap representing the relative importance of terms in the context of LLMs Source: marktechpost.com 1.

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Large Language Models LLM Neural Network Natural Language Processing 131

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?

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LLM Auto-complete Prompt Engineer Prompt Engineering 72

John Snow Labs

AUGUST 22, 2023

The new release delivers material speedups for calculating text embeddings, a critical step in populating vector databases for RAG LLM and Semantic Search applications. These cover the most widely used transformer architectures such as BERT, RoBERTa, DeBERTa, ALBERT, DistilBERT, XLM-RoBERTa, and CamamBERT.

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NLP LLM BERT Chatbots 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. Inspect Rich Documents with Gemini Multimodality and Multimodal RAG This course covers using multimodal prompts to extract information from text and visual data and generate video descriptions with Gemini.

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Artificial Intelligence Artificial Intelligence BERT Computer Vision 132

Unite.AI

JANUARY 23, 2024

Large language models (LLMs) have exploded in popularity over the last few years, revolutionizing natural language processing and AI. From chatbots to search engines to creative writing aids, LLMs are powering cutting-edge applications across industries. LLMs utilize embeddings to understand word context.

Large Language Models 130

Large Language Models Prompt Engineering Prompt Engineer LLM 130

John Snow Labs

JUNE 27, 2023

Instead of navigating complex menus or waiting on hold, they can engage in a conversation with a chatbot powered by an LLM. The LLM analyzes the customer’s query, processes the natural language input, and generates a contextual response in real-time.

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Large Language Models BERT Natural Language Processing NLP 52

Snorkel AI

FEBRUARY 13, 2024

Large language model distillation isolates LLM performance on a specific task and mirrors its functionality in a smaller format. LLM distillation basics Multi-billion parameter language models pre-trained on millions of documents have changed the world. LLMs’ flexibility dazzles, but most AI problems don’t require flexibility.

LLM 52

LLM Data Scientist Neural Network Data Science 52

Snorkel AI

FEBRUARY 13, 2024

Large language model distillation isolates LLM performance on a specific task and mirrors its functionality in a smaller format. LLM distillation basics Multi-billion parameter language models pre-trained on millions of documents have changed the world. LLMs’ flexibility dazzles, but most AI problems don’t require flexibility.

LLM 52

LLM Data Scientist Neural Network Data Science 52

Towards AI

NOVEMBER 6, 2024

With the advent of generative models (LLMs), the importance of effective retrieval has only grown. Our only knowledge source is high-quality documentation of SimTalk, consisting of approximately 10,000 pages, covering detailed explanations of language syntax, functions, use cases, and best practices, along with some code snippets.

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Metadata LLM BERT OpenAI 100

AWS Machine Learning Blog

JUNE 18, 2024

Manually identifying all mentions of specific types of information in documents is extremely time-consuming and labor-intensive. This process must be repeated for every new document and entity type, making it impractical for processing large volumes of documents at scale.

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Large Language Models Natural Language Processing LLM Computer Vision 126

Marktechpost

SEPTEMBER 9, 2024

Natural language inference (NLI) has emerged as a versatile classification framework, offering an alternative to generative Large Language Models (LLMs) for text analysis tasks. In NLI, a “premise” document is paired with a “hypothesis” statement, and the model determines if the hypothesis is true based on the premise.

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BERT Large Language Models LLM Categorization 105

Mlearning.ai

JUNE 7, 2023

Optimized to deploy increasingly complex models, such as large language models (LLM) and vision transformers, at scale. Goal In this end-to-end post, we will learn how to speed up BERT inference for text classification with Hugging Face Transformers, Amazon SageMaker, and AWS Inferentia2. item()], "score": item.max().item()}

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BERT Deep Learning Large Language Models Generative AI 52

Marktechpost

DECEMBER 18, 2023

From drug discovery to transcribing medical documents and even assisting in surgeries, it is transforming medical professionals’ lives and even helps reduce errors and improve their efficiency. Bioformer Bioformer is a compact version of BERT that can be used for biomedical text mining.

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Artificial Intelligence Artificial Intelligence BERT Deep Learning 124

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.

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Auto-complete Large Language Models Prompt Engineering Prompt Engineer 103

Towards AI

OCTOBER 31, 2024

As we wrap up October, we’ve compiled a bunch of diverse resources for you — from the latest developments in generative AI to tips for fine-tuning your LLM workflows, from building your own NotebookLM clone to instruction tuning. We have long supported RAG as one of the most practical ways to make LLMs more reliable and customizable.

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LLM NLP BERT Large Language Models 104

Mlearning.ai

APRIL 21, 2023

" } In general cases, we always have data in the form of paragraphs and documents. Even though traditional datasets are always in the form of a series of documents of either text files or word files, The problem with it is we can not feed it directly to LLM models as it requires data in a specific format.

LLM 52

LLM Large Language Models Natural Language Processing BERT 52

Unite.AI

FEBRUARY 12, 2024

Architectural Transparency and Customizability Access to open source LLM internals unlocks customization opportunities simply not possible with closed source alternatives. This customizability allows open source LLMs to better serve specialized domains like biomedical research, code generation, and education.

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LLM Large Language Models OpenAI Natural Language Processing 130

John Snow Labs

MAY 29, 2023

Question / Answering in Legal NLP using Flan-T5 LLM demos A new demo has been released showcasing how to use Flan-T5 models, finetuned on legal texts to carry out summarization , text generation and question answering. Let’s take a look at each of them! Demo available here.

NLP 52

NLP LLM BERT 52

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 189

Generative AI BERT Data Scientist Machine Learning 189

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. He has a Ph.D.

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Large Language Models LLM BERT Deep Learning 130

Unite.AI

NOVEMBER 20, 2023

Applications & Impact Meta's Llama is compared to other prominent LLMs, such as BERT and GPT-3. Privacy Control: Llama's adaptability and flexibility make it potentially disruptive to the current leaders in LLM, such as OpenAI and Google. However, Llama 2 is considered somewhat closed off compared to other open-source LLMs.

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Large Language Models BERT Chatbots LLM 173

Marktechpost

JANUARY 20, 2024

Pseudo-labels from advanced cross-encoder models like BERT are one of the methods for generating synthetic data for domain adaptation of dense passage retrievers. The second phase utilizes synthetic queries generated by an LLM based on randomly sampled documents from the corpus.

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BERT Large Language Models LLM AI 132

Marktechpost

MAY 17, 2024

Named Entity Recognition (NER) is vital in natural language processing, with applications spanning medical coding, financial analysis, and legal document parsing. NuMind team introduces an approach that suggests utilizing LLMs to minimize human annotations for custom model creation.

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Natural Language Processing BERT Large Language Models LLM 95

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. Biomedical Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. Well, that’s what CaseHOLD does.

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Large Language Models LLM NLP BERT 98

Flipboard

JUNE 20, 2023

For reference, GPT-3, an earlier generation LLM has 175 billion parameters and requires months of non-stop training on a cluster of thousands of accelerated processors. Specifically, we select LayoutLM , a pre-trained transformer model used for document image processing and information extraction. times higher inference throughput.

Machine Learning 123

Machine Learning BERT Deep Learning ML Engineer 123

IBM Journey to AI blog

NOVEMBER 24, 2023

Modernization teams perform their code analysis and go through several documents (mostly dated); this is where their reliance on code analysis tools becomes important. The accelerator generated UI for desired channel that could be integrated to the APIs, unit test cases and test data and design documentation.

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Generative AI Auto-complete DevOps Automation 305

John Snow Labs

AUGUST 29, 2023

It’s a well-established principle: any LLM, whether open-source or proprietary, isn’t dependable without a RAG. Anticipate swifter inferences, seamless optimizations, and quantization for exporting LLM models. MPNet, a cherished sentence-embedding LLM boasting 140+ ready-to-use models! This holds true in our 5.1

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NLP OpenAI BERT LLM 98

Analytics Vidhya

APRIL 15, 2024

RAG is what is necessary for the Large Language Models (LLMs) to provide or generate accurate and factual answers.

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Large Language Models LLM BERT OpenAI 324

Towards AI

JUNE 20, 2024

You could use LLM models like ChatGPT to create horoscopes (which it does quite successfully), or for something more practical (like work). However, there is a problem: companies typically have a multitude of documents, rules, regulations, etc., This part is usually done using an LLM like OpenAI. Of course, an LLM.

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LLM BERT OpenAI ChatGPT 62

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. Product requirements documentation (PRD) generation Monterey is working on a “co-pilot for product development” that might include LLMs.

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Large Language Models BERT Natural Language Processing Categorization 103

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.

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Prompt Engineer Prompt Engineering LLM ChatGPT 59

Marktechpost

JULY 27, 2024

However, a significant challenge with LLMs is their tendency to produce hallucinations—statements that sound plausible but are not grounded in factual information. This issue affects the reliability of AI-generated content, especially in domains requiring high accuracy, such as medical and legal documents.

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Large Language Models Natural Language Processing BERT AI 116