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Train custom computer vision defect detection model using Amazon SageMaker Artificial Intelligence

Train custom computer vision defect detection model using Amazon SageMaker Artificial Intelligence

Train custom computer vision defect detection model using Amazon SageMakerArtificial Intelligence In this post, we demonstrate how to migrate computer vision workloads from Amazon Lookout for Vision to Amazon SageMaker AI by training custom defect detection models using pre-trained models available on AWS Marketplace. We provide step-by-step guidance on labeling datasets with SageMaker Ground Truth, training models with flexible hyperparameter configurations, and deploying them for real-time or batch inference—giving you greater control and flexibility for automated quality inspection use cases.

 In this post, we demonstrate how to migrate computer vision workloads from Amazon Lookout for Vision to Amazon SageMaker AI by training custom defect detection models using pre-trained models available on AWS Marketplace. We provide step-by-step guidance on labeling datasets with SageMaker Ground Truth, training models with flexible hyperparameter configurations, and deploying them for real-time or batch inference—giving you greater control and flexibility for automated quality inspection use cases. Read More  

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MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases MIT News – Machine learning

MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases MIT News – Machine learning

MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseasesMIT News – Machine learning BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it.

 BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it. Read More  

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Practical implementation considerations to close the AI value gap Artificial Intelligence

Practical implementation considerations to close the AI value gap Artificial Intelligence

Practical implementation considerations to close the AI value gapArtificial Intelligence The AWS Customer Success Center of Excellence (CS COE) helps customers get tangible value from their AWS investments. We’ve seen a pattern: customers who build AI strategies that address people, process, and technology together succeed more often. In this post, we share practical considerations that can help close the AI value gap.

 The AWS Customer Success Center of Excellence (CS COE) helps customers get tangible value from their AWS investments. We’ve seen a pattern: customers who build AI strategies that address people, process, and technology together succeed more often. In this post, we share practical considerations that can help close the AI value gap. Read More  

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Why CrewAI’s Manager-Worker Architecture Fails — and How to Fix It Towards Data Science

Why CrewAI’s Manager-Worker Architecture Fails — and How to Fix ItTowards Data Science A real-world analysis of why CrewAI’s hierarchical orchestration misfires—and a practical fix you can implement today.
The post Why CrewAI’s Manager-Worker Architecture Fails — and How to Fix It appeared first on Towards Data Science.

 A real-world analysis of why CrewAI’s hierarchical orchestration misfires—and a practical fix you can implement today.
The post Why CrewAI’s Manager-Worker Architecture Fails — and How to Fix It appeared first on Towards Data Science. Read More  

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Warner Bros. Discovery achieves 60% cost savings and faster ML inference with AWS Graviton Artificial Intelligence

Warner Bros. Discovery achieves 60% cost savings and faster ML inference with AWS Graviton Artificial Intelligence

Warner Bros. Discovery achieves 60% cost savings and faster ML inference with AWS GravitonArtificial Intelligence Warner Bros. Discovery (WBD) is a leading global media and entertainment company that creates and distributes the world’s most differentiated and complete portfolio of content and brands across television, film and streaming. In this post, we describe the scale of our offerings, artificial intelligence (AI)/machine learning (ML) inference infrastructure requirements for our real time recommender systems, and how we used AWS Graviton-based Amazon SageMaker AI instances for our ML inference workloads and achieved 60% cost savings and 7% to 60% latency improvements across different models.

 Warner Bros. Discovery (WBD) is a leading global media and entertainment company that creates and distributes the world’s most differentiated and complete portfolio of content and brands across television, film and streaming. In this post, we describe the scale of our offerings, artificial intelligence (AI)/machine learning (ML) inference infrastructure requirements for our real time recommender systems, and how we used AWS Graviton-based Amazon SageMaker AI instances for our ML inference workloads and achieved 60% cost savings and 7% to 60% latency improvements across different models. Read More  

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Physical AI in practice: Technical foundations that fuel human-machine interactions Artificial Intelligence

Physical AI in practice: Technical foundations that fuel human-machine interactions Artificial Intelligence

Physical AI in practice: Technical foundations that fuel human-machine interactionsArtificial Intelligence In this post, we explore the complete development lifecycle of physical AI—from data collection and model training to edge deployment—and examine how these intelligent systems learn to understand, reason, and interact with the physical world through continuous feedback loops. We illustrate this workflow through Diligent Robotics’ Moxi, a mobile manipulation robot that has completed over 1.2 million deliveries in hospitals, saving nearly 600,000 hours for clinical staff while transforming healthcare logistics and returning valuable time to patient care.

 In this post, we explore the complete development lifecycle of physical AI—from data collection and model training to edge deployment—and examine how these intelligent systems learn to understand, reason, and interact with the physical world through continuous feedback loops. We illustrate this workflow through Diligent Robotics’ Moxi, a mobile manipulation robot that has completed over 1.2 million deliveries in hospitals, saving nearly 600,000 hours for clinical staff while transforming healthcare logistics and returning valuable time to patient care. Read More  

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HyperPod now supports Multi-Instance GPU to maximize GPU utilization for generative AI tasks Artificial Intelligence

HyperPod now supports Multi-Instance GPU to maximize GPU utilization for generative AI tasks Artificial Intelligence

HyperPod now supports Multi-Instance GPU to maximize GPU utilization for generative AI tasksArtificial Intelligence In this post, we explore how Amazon SageMaker HyperPod now supports NVIDIA Multi-Instance GPU (MIG) technology, enabling you to partition powerful GPUs into multiple isolated instances for running concurrent workloads like inference, research, and interactive development. By maximizing GPU utilization and reducing wasted resources, MIG helps organizations optimize costs while maintaining performance isolation and predictable quality of service across diverse machine learning tasks.

 In this post, we explore how Amazon SageMaker HyperPod now supports NVIDIA Multi-Instance GPU (MIG) technology, enabling you to partition powerful GPUs into multiple isolated instances for running concurrent workloads like inference, research, and interactive development. By maximizing GPU utilization and reducing wasted resources, MIG helps organizations optimize costs while maintaining performance isolation and predictable quality of service across diverse machine learning tasks. Read More  

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Deploy an AI Analyst in Minutes: Connect Any LLM to Any Data Source with Bag of Words KDnuggets

Deploy an AI Analyst in Minutes: Connect Any LLM to Any Data Source with Bag of Words KDnuggets

Deploy an AI Analyst in Minutes: Connect Any LLM to Any Data Source with Bag of WordsKDnuggets Deploy an AI analyst fast by connecting any LLM to your SQL database with Bag of Words, allowing immediate, trustworthy data insights via natural language queries.

 Deploy an AI analyst fast by connecting any LLM to your SQL database with Bag of Words, allowing immediate, trustworthy data insights via natural language queries. Read More  

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Adversarial learning breakthrough enables real-time AI security AI News

Adversarial learning breakthrough enables real-time AI security AI News

Adversarial learning breakthrough enables real-time AI securityAI News The ability to execute adversarial learning for real-time AI security offers a decisive advantage over static defence mechanisms. The emergence of AI-driven attacks – utilising reinforcement learning (RL) and Large Language Model (LLM) capabilities – has created a class of “vibe hacking” and adaptive threats that mutate faster than human teams can respond. This represents
The post Adversarial learning breakthrough enables real-time AI security appeared first on AI News.

 The ability to execute adversarial learning for real-time AI security offers a decisive advantage over static defence mechanisms. The emergence of AI-driven attacks – utilising reinforcement learning (RL) and Large Language Model (LLM) capabilities – has created a class of “vibe hacking” and adaptive threats that mutate faster than human teams can respond. This represents
The post Adversarial learning breakthrough enables real-time AI security appeared first on AI News. Read More