Remove 2012 Remove AI Remove Python
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You can now download the source code that sparked the AI boom

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On Thursday, Google and the Computer History Museum (CHM) jointly released the source code for AlexNet , the convolutional neural network (CNN) that many credit with transforming the AI field in 2012 by proving that "deep learning" could achieve things conventional AI techniques could not.

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Combine keyword and semantic search for text and images using Amazon Bedrock and Amazon OpenSearch Service

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OpenSearch Service can help you deploy and operate your search infrastructure with native vector database capabilities delivering as low as single-digit millisecond latencies for searches across billions of vectors, making it ideal for real-time AI applications. Familiarity with Python programming language.

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Uphold ethical standards in fashion using multimodal toxicity detection with Amazon Bedrock Guardrails

AWS Machine Learning Blog

In the fashion industry, teams are frequently innovating quickly, often utilizing AI. Implementing guardrails while utilizing AI to innovate faster within this industry can provide long lasting benefits. As technology evolves, the need for effective reputation management strategies should include using AI in responsible ways.

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Agents as escalators: Real-time AI video monitoring with Amazon Bedrock Agents and video streams

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Amazon Bedrock is a fully managed service that provides access to high-performing foundation models (FMs) from leading AI companies through a single API. Using Amazon Bedrock, you can build secure, responsible generative AI applications. The core of the video processing is a modular pipeline implemented in Python.

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Evaluating generative AI models with Amazon Nova LLM-as-a-Judge on Amazon SageMaker AI

AWS Machine Learning Blog

For most real-world generative AI scenarios, it’s crucial to understand whether a model is producing better outputs than a baseline or an earlier iteration. Amazon Nova LLM-as-a-Judge is designed to deliver robust, unbiased assessments of generative AI outputs across model families. Meta J1 8B – 0.42 – 0.60 – Nova Micro (8B) 0.56

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Use Amazon Bedrock tooling with Amazon SageMaker JumpStart models

AWS Machine Learning Blog

SageMaker JumpStart helps you get started with machine learning (ML) by providing fully customizable solutions and one-click deployment and fine-tuning of more than 400 popular open-weight and proprietary generative AI models. It also offers a broad set of capabilities to build generative AI applications.

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Fine-tune multimodal models for vision and text use cases on Amazon SageMaker JumpStart

AWS Machine Learning Blog

In the rapidly evolving landscape of AI, generative models have emerged as a transformative technology, empowering users to explore new frontiers of creativity and problem-solving. By fine-tuning a generative AI model like Meta Llama 3.2 For a detailed walkthrough on fine-tuning the Meta Llama 3.2 Meta Llama 3.2 All Meta Llama 3.2

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