AI

Cool but dangerous: New Claude AI model can control your computer
23 Oct

Cool but dangerous: New Claude AI model can control your computer

stp2y0 CommentsAI
Just a heads up, if you buy something through our links, we may get a small share of the sale. It’s one of the ways we keep the lights on here. Click here for more. Anthropic has rolled out the Claude 3.5 Sonnet AI model with a feature in the public beta that can operate a computer simply by looking at what’s on the screen. The API also includes a new feature called “computer use,” which allows developers to command Claude to work on a computer like a human would. It is the first major AI model to take the…
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Using Artificial Intelligence Is Easier Than You Think
23 Oct

Using Artificial Intelligence Is Easier Than You Think

stp2y0 CommentsAI, , ,
Ever since I watched the Disney Channel original movie Smart House as a kid, I’ve been fascinated by futuristic visions of technology in our daily lives. While writing about artificial intelligence tools and providing advice for using them at WIRED over the past two years, it’s become so clear to me that the software is nothing like it’s depicted in these sci-fi movies or what the hype-focused marketing materials from AI companies would have you believe.Even with this in mind, I do still consider the current crop of generative AI tools to be sometimes useful, sometimes entertaining, and almost always…
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Crafting ethical AI: Addressing bias and challenges
23 Oct

Crafting ethical AI: Addressing bias and challenges

stp2y0 CommentsAI
Did you know that 27.1% of AI practitioners and 32.5% of AI tools’ end users don’t specifically address artificial intelligence's biases and challenges? The technology is helping to improve industries like healthcare, where diagnoses can be improved through rapidly evolving technology. However, this raises ethical concerns about the potential for AI systems to be biased, threaten human rights, contribute to climate change, and more. In our Generative AI 2024 report, we set out to understand how businesses address these ethical AI issues by surveying practitioners and end users.With the global AI market size forecast to be US$1.8tn by 2030 and AI…
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Implement Amazon SageMaker domain cross-Region disaster recovery using custom Amazon EFS instances | Amazon Web Services
22 Oct

Implement Amazon SageMaker domain cross-Region disaster recovery using custom Amazon EFS instances | Amazon Web Services

stp2y0 CommentsAI
Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. Extensively used by data scientists and ML engineers across various industries, this robust tool provides high availability and uninterrupted access for its users. When working with SageMaker, your environment resides within a SageMaker domain, which encompasses critical components like Amazon Elastic File System (Amazon EFS) for storage, user profiles, and a diverse array of security configurations. This comprehensive setup enables collaborative efforts by allowing users to store, share, and access notebooks, Python…
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Automate fine-tuning of Llama 3.x models with the new visual designer for Amazon SageMaker Pipelines | Amazon Web Services
22 Oct

Automate fine-tuning of Llama 3.x models with the new visual designer for Amazon SageMaker Pipelines | Amazon Web Services

stp2y0 CommentsAI
You can now create an end-to-end workflow to train, fine tune, evaluate, register, and deploy generative AI models with the visual designer for Amazon SageMaker Pipelines. SageMaker Pipelines is a serverless workflow orchestration service purpose-built for foundation model operations (FMOps). It accelerates your generative AI journey from prototype to production because you don’t need to learn about specialized workflow frameworks to automate model development or notebook execution at scale. Data scientists and machine learning (ML) engineers use pipelines for tasks such as continuous fine-tuning of large language models (LLMs) and scheduled notebook job workflows. Pipelines can scale up to run…
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Long Context Compression with Activation Beacon
22 Oct

Long Context Compression with Activation Beacon

stp2y0 CommentsAI
How do we make LLMs handle long contexts without breaking the bank on computational costs? This is a pressing issue because tasks like document understanding and long-form text generation require processing more information than ever. The quadratic complexity of attention mechanisms in transformers means that, as we extend the context, the computation and memory requirements skyrocket. In this post, we will explore how "Activation Beacon," a new method for long context compression (trending on AImodels.fyi!), attempts to solve this problem. We’ll dig into what makes this approach effective, how it works, and the benefits it brings. And I’ll also highlight…
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Generative AI foundation model training on Amazon SageMaker | Amazon Web Services
22 Oct

Generative AI foundation model training on Amazon SageMaker | Amazon Web Services

stp2y0 CommentsAI
To stay competitive, businesses across industries use foundation models (FMs) to transform their applications. Although FMs offer impressive out-of-the-box capabilities, achieving a true competitive edge often requires deep model customization through pre-training or fine-tuning. However, these approaches demand advanced AI expertise, high performance compute, fast storage access and can be prohibitively expensive for many organizations. In this post, we explore how organizations can address these challenges and cost-effectively customize and adapt FMs using AWS managed services such as Amazon SageMaker training jobs and Amazon SageMaker HyperPod. We discuss how these powerful tools enable organizations to optimize compute resources and reduce the complexity…
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