Artificial Intelligence

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Automate video insights for contextual advertising using Amazon Bedrock Data Automation

Amazon Bedrock, Artificial Intelligence, Data Science & Analytics for Media, Marketing & Advertising, Media & Entertainment /

Contextual advertising, a strategy that matches ads with relevant digital content, has transformed digital marketing by delivering personalized experiences to viewers. However, implementing this approach for streaming video-on-demand (VOD) content poses significant challenges, particularly in ad placement and relevance. Traditional methods rely heavily on manual content analysis. For example, a content analyst might spend hours […]

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How Salesforce achieves high-performance model deployment with Amazon SageMaker AI

Amazon SageMaker, Amazon SageMaker AI, Artificial Intelligence, Best Practices, Customer Solutions, Experience-Based Acceleration /

This post is a joint collaboration between Salesforce and AWS and is being cross-published on both the Salesforce Engineering Blog and the AWS Machine Learning Blog. The Salesforce AI Model Serving team is working to push the boundaries of natural language processing and AI capabilities for enterprise applications. Their key focus areas include optimizing large

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Host concurrent LLMs with LoRAX

Amazon EC2, Artificial Intelligence, Generative AI, Technical How-to /

Businesses are increasingly seeking domain-adapted and specialized foundation models (FMs) to meet specific needs in areas such as document summarization, industry-specific adaptations, and technical code generation and advisory. The increased usage of generative AI models has offered tailored experiences with minimal technical expertise, and organizations are increasingly using these powerful models to drive innovation and

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Build multi-agent systems with LangGraph and Amazon Bedrock

Advanced (300), AI/ML, Amazon Bedrock, Artificial Intelligence, Generative AI, Technical How-to /

Large language models (LLMs) have raised the bar for human-computer interaction where the expectation from users is that they can communicate with their applications through natural language. Beyond simple language understanding, real-world applications require managing complex workflows, connecting to external data, and coordinating multiple AI capabilities. Imagine scheduling a doctor’s appointment where an AI agent

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Racing beyond DeepRacer: Debut of the AWS LLM League

Artificial Intelligence, AWS DeepRacer, Foundational (100) /

The AWS DeepRacer League is the world’s first autonomous racing league, open to anyone. Announced at re:Invent 2018, it puts machine learning in the hands of every developer through the fun and excitement of developing and racing self-driving remote control cars. Through the past 7 years, over 560 thousand developers of all skill levels have

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How TransPerfect Improved Translation Quality and Efficiency Using Amazon Bedrock

Amazon Bedrock, Amazon Bedrock Guardrails, Artificial Intelligence, Customer Solutions /

This post is co-written with Keith Brazil, Julien Didier, and Bryan Rand from TransPerfect. TransPerfect, a global leader in language and technology solutions, serves a diverse array of industries. Founded in 1992, TransPerfect has grown into an enterprise with over 10,000 employees in more than 140 cities on six continents. The company offers a broad

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Reduce ML training costs with Amazon SageMaker HyperPod

Amazon Machine Learning, Amazon SageMaker, Amazon SageMaker AI, Artificial Intelligence, Foundation models, Generative AI /

Training a frontier model is highly compute-intensive, requiring a distributed system of hundreds, or thousands, of accelerated instances running for several weeks or months to complete a single job. For example, pre-training the Llama 3 70B model with 15 trillion training tokens took 6.5 million H100 GPU hours. On 256 Amazon EC2 P5 instances (p5.48xlarge,

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Generate user-personalized communication with Amazon Personalize and Amazon Bedrock

Amazon Bedrock, Amazon Personalize, Artificial Intelligence, Intermediate (200), Technical How-to /

Today, businesses are using AI and generative models to improve productivity in their teams and provide better experiences to their customers. Personalized outbound communication can be a powerful tool to increase user engagement and conversion. For instance, as a marketing manager for a video-on-demand company, you might want to send personalized email messages tailored to

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Build an ecommerce product recommendation chatbot with Amazon Bedrock Agents

AI/ML, Amazon Bedrock, Artificial Intelligence, Generative AI, Industries, Intermediate (200), Retail, Technical How-to /

Many ecommerce applications want to provide their users with a human-like chatbot that guides them to choose the best product as a gift for their loved ones or friends. To enhance the customer experience, the chatbot need to engage in a natural, conversational manner to understand the user’s preferences and requirements, such as the recipient’s

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Transform customer engagement with no-code LLM fine-tuning using Amazon SageMaker Canvas and SageMaker JumpStart

Advanced (300), Amazon SageMaker, Amazon SageMaker Canvas, Amazon SageMaker JumpStart, Artificial Intelligence /

Fine-tuning large language models (LLMs) creates tailored customer experiences that align with a brand’s unique voice. Amazon SageMaker Canvas and Amazon SageMaker JumpStart democratize this process, offering no-code solutions and pre-trained models that enable businesses to fine-tune LLMs without deep technical expertise, helping organizations move faster with fewer technical resources. SageMaker Canvas provides an intuitive

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