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

SEPTEMBER 17, 2024

Our solution uses an FSx for ONTAP file system as the source of unstructured data and continuously populates an Amazon OpenSearch Serverless vector database with the user’s existing files and folders and associated metadata. Prerequisites Complete the following prerequisite steps: Make sure you have model access in Amazon Bedrock.

Generative AI 91

Generative AI Metadata Chatbots Auto-complete 91

The MLOps Blog

JANUARY 23, 2025

How do multimodal LLMs work? A typical multimodal LLM has three primary modules: The input module comprises specialized neural networks for each specific data type that output intermediate embeddings. Basic structure of a multimodal LLM. The fusion module converts the intermediate embeddings into a joint representation.

Large Language Models 59

Large Language Models Auto-classification LLM Robotics 59

The MLOps Blog

JUNE 27, 2023

When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support. Flexibility, speed, and accessibility : can you customize the metadata structure? Can you see the complete model lineage with data/models/experiments used downstream?

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

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. This represents about a full page of text.

Generative AI 99

Generative AI Auto-complete LLM Natural Language Processing 99

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Training job resiliency with the job auto resume functionality – In this section, we demonstrate how scientists can submit and manage their distributed training jobs using either the native Kubernetes CLI (kubectl) or optionally the new HyperPod CLI (hyperpod) with automatic job recovery enabled.

Auto-complete 82

Auto-complete ML Machine Learning Automation 82

AWS Machine Learning Blog

MAY 22, 2024

BLIP-2 consists of three models: a CLIP-like image encoder, a Querying Transformer (Q-Former) and a large language model (LLM). We use a version of BLIP-2, that contains Flan-T5-XL as the LLM. jpg and the complete metadata from styles/38642.json. From here, we can fetch the image for this product from images/38642.jpg

Machine Learning 133

Machine Learning Generative AI Natural Language Processing Large Language Models 133

AWS Machine Learning Blog

JUNE 20, 2024

It allows LLMs to reference authoritative knowledge bases or internal repositories before generating responses, producing output tailored to specific domains or contexts while providing relevance, accuracy, and efficiency. Generation is the process of generating the final response from the LLM.

Auto-classification 133

Auto-classification LLM Prompt Engineer Prompt Engineering 133

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

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 99

Large Language Models LLM Machine Learning ML 99

ODSC - Open Data Science

AUGUST 24, 2023

In this blog post, our objective is to illuminate the constantly evolving research around the LLMs space, while also addressing key ethical considerations and trying to provide practical guidance to AI practitioners and clients with examples of our internal use cases, facilitating the responsible development of LLM applications.

Prompt Engineering 52

Prompt Engineering Prompt Engineer Large Language Models Responsible AI 52

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. This adaptation is facilitated through the use of LLM prompts. For Secret type , choose Other type of secret.

Data Scientist 116

Data Scientist Generative AI Machine Learning ML 116

The MLOps Blog

MARCH 12, 2024

TL;DR LLMOps involves managing the entire lifecycle of Large Language Models (LLMs), including data and prompt management, model fine-tuning and evaluation, pipeline orchestration, and LLM deployment. Prompt-response management: Refining LLM-backed applications through continuous prompt-response optimization and quality control.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models LLM 52

Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. Others, toward language completion and further downstream tasks. Hope you can all hear me well.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. Others, toward language completion and further downstream tasks. Hope you can all hear me well.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

AWS Machine Learning Blog

JULY 16, 2024

The NVIDIA NeMo Framework provides a comprehensive set of tools, scripts, and recipes to support each stage of the LLM journey, from data preparation to training and deployment. Training Now that our data preparation is complete, we’re ready to train our model with the created dataset.

Generative AI 126

Generative AI Auto-complete Auto-classification Deep Learning 126

Flipboard

NOVEMBER 27, 2024

The application needs to search through the catalog and show the metadata information related to all of the data assets that are relevant to the search context. The following diagram illustrates the end-to-end architecture, consisting of the metadata API layer, ingestion pipeline, embedding generation workflow, and frontend UI.

Metadata 146

Metadata Auto-complete Data Discovery ML Engineer 146

AWS Machine Learning Blog

FEBRUARY 3, 2025

Not only are large language models (LLMs) capable of answering a users question based on the transcript of the file, they are also capable of identifying the timestamp (or timestamps) of the transcript during which the answer was discussed. Each citation can point to a different video, or to different timestamps within the same video.

UX Design 96

UX Design Auto-complete LLM Prompt Engineer 96

AWS Machine Learning Blog

DECEMBER 11, 2024

Next, you need to index this data to make it available for a Retrieval Augmented Generation (RAG) approach, where relevant passages are delivered with high accuracy to a large language model (LLM). Complete the following steps to create your application: On the Amazon Q Business console, choose Applications in the navigation pane.

Auto-complete 103

Auto-complete IDP Generative AI Metadata 103

AWS Machine Learning Blog

JANUARY 9, 2025

This process is like assembling a jigsaw puzzle to form a complete picture of the malwares capabilities and intentions, with pieces constantly changing shape. DIANNA is a groundbreaking malware analysis tool powered by generative AI to tackle real-world issues, using Amazon Bedrock as its large language model (LLM) infrastructure.

Deep Learning 111

Deep Learning Neural Network Explainability AI 111

AWS Machine Learning Blog

NOVEMBER 22, 2024

Amazon Q Business is a conversational assistant powered by generative AI that enhances workforce productivity by answering questions and completing tasks based on information in your enterprise systems, which each user is authorized to access. On the Settings tab, note the Metadata URI. The sample script simple_aq.py

IDP 89

IDP Auto-complete Python Generative AI 89