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GraphStorm 0.3: Scalable, multi-task learning on graphs with user-friendly APIs

AWS Machine Learning

adds new APIs to customize GraphStorm pipelines: you now only need 12 lines of code to implement a custom node classification training loop. To help you get started with the new API, we have published two Jupyter notebook examples: one for node classification, and one for a link prediction task. Specifically, GraphStorm 0.3

APIs 115
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From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 2

AWS Machine Learning

For a qualitative question like “What caused inflation in 2023?”, However, for a quantitative question such as “What was the average inflation in 2023?”, For instance, instead of saying “What caused inflation in 2023?”, the user could disambiguate by asking “What caused inflation in 2023 according to analysts?”,

APIs 117
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Product News – May 2023

Lumoa

Lumoa Product News for May 2023 Hey everyone! New API AppStore integration Those of you who are pulling data from the AppStore are going to love this, and if you aren’t pulling AppStore data, there has never been a better time to start! The post Product News – May 2023 appeared first on Lumoa. Let’s get started!

APIs 15
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Fine-tune LLMs with synthetic data for context-based Q&A using Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that makes FMs from leading AI startups and Amazon available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case. Solution overview The solution comprises two main steps: Generate synthetic data using the Amazon Bedrock InvokeModel API.

APIs 74
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Get started with Amazon Titan Text Embeddings V2: A new state-of-the-art embeddings model on Amazon Bedrock

AWS Machine Learning

In September of 2023, we announced the launch of Amazon Titan Text Embeddings V1, a multilingual text embeddings model that converts text inputs like single words, phrases, or large documents into high-dimensional numerical vector representations. In this benchmark, 33 different text embedding models were evaluated on the MTEB tasks.

Benchmark 126
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Intelligent healthcare forms analysis with Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI startups and Amazon available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case. Lastly, the Lambda function stores the question list in Amazon S3.

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Generate training data and cost-effectively train categorical models with Amazon Bedrock

AWS Machine Learning

These include metrics such as ROUGE or cosine similarity for text similarity, and specific benchmarks for assessing toxicity (Detoxify), prompt stereotyping (cross-entropy loss), or factual knowledge (HELM, LAMA). Refer to Getting started with the API to set up your environment to make Amazon Bedrock requests through the AWS API.