Unite.AI

MAY 29, 2024

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Image and Document Processing Multimodal LLMs have completely replaced OCR.

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Marktechpost

NOVEMBER 24, 2024

Transformer architectures have revolutionized Natural Language Processing (NLP), enabling significant language understanding and generation progress. One promising solution is Speculative Decoding (SD), a method designed to accelerate LLM inference without compromising generated output quality.

LLM 88

LLM AI Research AI Researcher Auto-complete 88

NVIDIA

MARCH 18, 2024

These technologies together enable NVIDIA Avatar Cloud Engine , or ACE, and multimodal language models to work together with the NVIDIA DRIVE platform to let automotive manufacturers develop their own intelligent in-car assistants. Li Auto unveiled its multimodal cognitive model, Mind GPT, in June.

Generative AI 121

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Flipboard

NOVEMBER 20, 2023

Retrieval Augmented Generation (RAG) allows you to provide a large language model (LLM) with access to data from external knowledge sources such as repositories, databases, and APIs without the need to fine-tune it. There are two models in this implementation: the embeddings model and the LLM that generates the final response.

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Marktechpost

JUNE 4, 2023

Augmented LLMs are the ones that are added with external tools and skills in order to increase their performance so that they perform beyond their inherent capabilities. Applications like Auto-GPT for autonomous task execution have been made possible by Augmented Language Models (ALMs) only.

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Auto-complete Large Language Models Natural Language Processing LLM 119

AssemblyAI

SEPTEMBER 18, 2023

Below, we'll give you the basic know-how you need to understand LLMs, how they work, and the best models in 2023. What Is a Large Language Model? A large language model (often abbreviated as LLM) is a machine-learning model designed to understand, generate, and interact with human language.

Large Language Models 130

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AWS Machine Learning Blog

MARCH 28, 2024

This technique provides targeted yet broad-ranging search capabilities, furnishing the LLM with a wider perspective. It tackles the issue of information overload and irrelevant data processing head-on, leading to improved response quality, more cost-effective LLM operations, and a smoother overall retrieval process.

LLM 138

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AWS Machine Learning Blog

OCTOBER 11, 2023

The LMI container has a powerful serving stack called DJL serving that is agnostic to the underlying LLM. It provides system-level configuration parameters that can be tuned for extracting the best performance of the hosting infrastructure for a given LLM. These cached key and value tensors are often referred to as the KV cache.

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AWS Machine Learning Blog

JULY 24, 2024

Einstein has a list of over 60 features, unlocked at different price points and segmented into four main categories: machine learning (ML), natural language processing (NLP), computer vision, and automatic speech recognition. LMI containers are a set of high-performance Docker Containers purpose built for LLM inference.

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AWS Machine Learning Blog

JULY 1, 2024

The user prompt is augmented along with the results returned from the knowledge base as an additional context and sent to the LLM to generate a response. Create a knowledge base To create a new knowledge base in Amazon Bedrock, complete the following steps. You should see a Successfully built message when the build is complete.

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AWS Machine Learning Blog

SEPTEMBER 5, 2023

These models have revolutionized various computer vision (CV) and natural language processing (NLP) tasks, including image generation, translation, and question answering. To make sure that our endpoint can scale down to zero, we need to configure auto scaling on the asynchronous endpoint using Application Auto Scaling.

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AWS Machine Learning Blog

SEPTEMBER 25, 2023

Large language models (LLMs) used to generate text sequences need immense amounts of computing power and have difficulty accessing the available high bandwidth memory (HBM) and compute capacity. The parameters can be loaded one time and used to process multiple input sequences.

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AWS Machine Learning Blog

MAY 22, 2024

Using machine learning (ML) and natural language processing (NLP) to automate product description generation has the potential to save manual effort and transform the way ecommerce platforms operate. BLIP-2 consists of three models: a CLIP-like image encoder, a Querying Transformer (Q-Former) and a large language model (LLM).

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AWS Machine Learning Blog

JUNE 13, 2023

Last week, Technology Innovation Institute (TII) launched TII Falcon LLM , an open-source foundational large language model (LLM). The result of this effort is TII Falcon LLM. SageMaker large model inference DLCs simplify LLM hosting Hosting LLMs such as Falcon-40B and Falcon-7B can be challenging.

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Topbots

AUGUST 22, 2023

Unlike traditional machine learning where outcomes are often binary, LLM outputs dwell in a spectrum of correctness. Therefore, a holistic approach to evaluating LLMs must utilize a variety of approaches, such as using LLMs to evaluate LLMs (i.e., auto-evaluation) and using human-LLM hybrid approaches.

LLM 52

LLM Auto-complete Large Language Models Machine Learning 52

AWS Machine Learning Blog

MAY 31, 2024

It’s a next generation model in the Falcon family—a more efficient and accessible large language model (LLM) that is trained on a 5.5 It’s built on causal decoder-only architecture, making it powerful for auto-regressive tasks. After deployment is complete, you will see that an endpoint is created.

Python 128

Python Auto-classification Machine Learning Natural Language Processing 128

AWS Machine Learning Blog

AUGUST 5, 2024

In recent years, we have seen a big increase in the size of large language models (LLMs) used to solve natural language processing (NLP) tasks such as question answering and text summarization. This technique improves LLM inference throughput and output token latency (TPOT). compared to 76.4).

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Auto-complete Large Language Models ML Natural Language Processing 121

AWS Machine Learning Blog

DECEMBER 5, 2023

Customers can create the custom metadata using Amazon Comprehend , a natural-language processing (NLP) service managed by AWS to extract insights about the content of documents, and ingest it into Amazon Kendra along with their data into the index. For example, metadata can be used for filtering and searching. append(e["Text"].upper())

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Metadata Auto-classification Auto-complete Content Enrichment 131

AWS Machine Learning Blog

MAY 12, 2023

To get started, complete the following steps: On the File menu, choose New and Terminal. Use CodeWhisperer in Studio After we complete the installation steps, we can use CodeWhisperer by opening a new notebook or Python file. To get started, complete the following steps: On the File menu, choose New and Terminal.

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AWS Machine Learning Blog

MAY 1, 2024

Llama2 by Meta is an example of an LLM offered by AWS. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture and is intended for commercial and research use in English. This results in faster restarts and workload completion.

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AWS Machine Learning Blog

DECEMBER 11, 2024

Two open-source libraries, Ragas (a library for RAG evaluation) and Auto-Instruct, used Amazon Bedrock to power a framework that evaluates and improves upon RAG. Generating improved instructions for each question-and-answer pair using an automatic prompt engineering technique based on the Auto-Instruct Repository.

Generative AI 70

Generative AI Chatbots Prompt Engineer Prompt Engineering 70

Mlearning.ai

FEBRUARY 19, 2023

You don’t need to have a PhD to understand the billion parameter language model GPT is a general-purpose natural language processing model that revolutionized the landscape of AI. GPT-3 is a autoregressive language model created by OpenAI, released in 2020 . What is GPT-3?

Auto-classification 52

Auto-classification Auto-complete Natural Language Processing NLP 52

AWS Machine Learning Blog

MARCH 6, 2023

LLMs’ generative abilities make them popular for text synthesis, summarization, machine translation, and more. The size of an LLM and its training data is a double-edged sword: it brings modeling quality, but entails infrastructure challenges. In the past few years, numerous customers have been using the AWS Cloud for LLM training.

Large Language Models 111

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The MLOps Blog

JANUARY 19, 2024

Imagine you’re facing the following challenge: you want to develop a Large Language Model (LLM) that can proficiently respond to inquiries in Portuguese. We will fine-tune different foundation LLM models on a dataset, evaluate them, and select the best model. You have a valuable dataset and can choose from various base models.

LLM 52

LLM Auto-complete Large Language Models Natural Language Processing 52

Marktechpost

AUGUST 18, 2024

In the field of Natural Language Processing (NLP), Retrieval Augmented Generation, or RAG, has attracted much attention lately. To make sure the knowledge base is as precise and complete as feasible, duplicates should also be removed. For this process, choosing the optimal embedding and reranked models is essential.

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ODSC - Open Data Science

AUGUST 24, 2023

Be sure to check out their talk, “Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI Practices,” there! At the core of efficient LLM utilization lies the art of prompt engineering which involves crafting prompts that guide LLMs effectively, paving the way for reliable responses.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models Responsible AI 52

AWS Machine Learning Blog

DECEMBER 14, 2023

Complete the following steps to edit an existing space: On the space details page, choose Stop space. It serves as an essential tool for both beginner and seasoned coders, providing insights into best practices, accelerating the development process, and improving the overall quality of code. Choose Create JupyterLab space.

Generative AI 132

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AWS Machine Learning Blog

NOVEMBER 15, 2024

In the metadata.jsonl file, each example is a dictionary that contains three keys named file_name , prompt , and completion. prompt defines the text input prompt and completion defines the text completion corresponding to the input prompt. jpg", "prompt": "what is the contact person name mentioned in letter?", "completion": "P.

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AWS Machine Learning Blog

AUGUST 14, 2023

An application using the RAG approach retrieves information most relevant to the user’s request from the enterprise knowledge base or content, bundles it as context along with the user’s request as a prompt, and then sends it to the LLM to get a response. The LLM returns with a response that is based on the retrieved documents.

Generative AI 91

Generative AI LLM NLP Large Language Models 91

AWS Machine Learning Blog

APRIL 16, 2024

To store information in Secrets Manager, complete the following steps: On the Secrets Manager console, choose Store a new secret. Complete the following steps: On the Secrets Manager console, choose Store a new secret. However, it is essential to acknowledge the inherent differences between human language and SQL.

Data Scientist 126

Data Scientist Generative AI Machine Learning Auto-complete 126

AWS Machine Learning Blog

MAY 4, 2023

For ultra-large models that don’t fit into a single accelerator, data flows directly between accelerators with NeuronLink, bypassing the CPU completely. These endpoints are fully managed and support auto scaling. When the tracing is complete, the model is partitioned across the NeuronCores based on the tensor parallel degree.

Generative AI 102

Generative AI Deep Learning Machine Learning Python 102

John Snow Labs

JUNE 27, 2023

Are you curious about the groundbreaking advancements in Natural Language Processing (NLP)? Prepare to be amazed as we delve into the world of Large Language Models (LLMs) – the driving force behind NLP’s remarkable progress. and GPT-4, marked a significant advancement in the field of large language models.

Large Language Models 52

Large Language Models BERT Natural Language Processing NLP 52

The MLOps Blog

JUNE 27, 2023

For example, if your team works on recommender systems or natural language processing applications, you may want an MLOps tool that has built-in algorithms or templates for these use cases. Is it accessible from your language/framework/infrastructure, framework, or infrastructure? Can you render audio/video?

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

John Snow Labs

AUGUST 15, 2023

The realm of Natural Language Processing has been growing exponentially, bringing about a host of advancements that are pushing the boundaries of technology and its application. Enabling this option ensures that the pre-annotation process only includes sections present in the latest completion of the current user.

NLP 52

NLP Auto-complete Natural Language Processing Data Extraction 52

AWS Machine Learning Blog

SEPTEMBER 24, 2024

It also enables operational capabilities including automated testing, conversation analytics, monitoring and observability, and LLM hallucination prevention and detection. “We An optional CloudFormation stack to enable an asynchronous LLM hallucination detection feature. seconds or less. The stack will take about 10 minutes to deploy.

Generative AI 104

Generative AI Auto-complete LLM Automation 104

AWS Machine Learning Blog

NOVEMBER 1, 2023

Visual language processing (VLP) is at the forefront of generative AI, driving advancements in multimodal learning that encompasses language intelligence, vision understanding, and processing. Central to the architecture are the fine-tuned VLM and LLM, both instrumental in decoding visual and textual data streams.

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Unite.AI

APRIL 18, 2024

SWE agent LLM LLM Agents: Orchestrating Task Automation LLM agents are sophisticated software entities designed to automate the execution of complex tasks. The operation of an LLM agent can be visualized as a dynamic sequence of steps, meticulously orchestrated to fulfill the given task.

Software Engineer 261

Software Engineer Software Development LLM Auto-complete 261