Amazon Science @AmazonScience
The latest news and research from Amazon's science community. #AmazonScience amazon.science Global Joined December 2019-
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Amazon's Sebastian Hoefer (@hoeferse) discusses his team's work on visual defect detection at @CVPR — including the Kaputt dataset and #CVPR2026 challenge. Learn more about the novel dataset: amzn.to/4oe4nHy
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It's been an incredible week at #CVPR2026! If you haven't stopped by our booth yet, come say hi to our team at booth 349.
Our scientists are presenting at poster sessions throughout @CVPR, covering computer vision, multimodal AI, and image retrieval. Find us on the #CVPR2026 floor and explore our research: amzn.to/43knFBn
Meet Yelin Kim – she leads computer vision for Amazon's Last Mile team, relocating AI from the cloud to wearables and enabling hands-free delivery with multimodal sensing. Hear more about her work and check out her paper that was selected as a #CVPR2026 highlight: amzn.to/3PJOax5
Don't miss what's happening at our #CVPR2026 booth the rest of the week. Live demos, technical deep dives, and conversations with our researchers – here's the full schedule:
Amazon is advancing AI, computer vision, and machine learning to solve real-world challenges for customers. Explore career opportunities: amzn.to/4uhJj4i At #CVPR2026? Visit booth 349 to learn about joining our team.
Amazon researchers have accepted papers at @CVPR spanning visual reasoning, agentic AI, multimodal LLMs, reinforcement learning, and image generation. #CVPR2026 amazon.science/conferences-an…
We're excited to be back with the computer vision community at #CVPR2026. Here's the lineup at our booth ⬇️
Amazon Science retweeted
Amazon Science retweeted
📌☁️ @Pinterest just committed $4B for @awscloud services through 2031, the largest infrastructure commitment in the company's history. Learn how AWS is powering personalized discovery for Pinterest’s 600M+ users with Trainium, Graviton, & Amazon EKS: go.aws/4uJkTSe
Amazon researchers are participating in workshops across #CVPR2026 — among them, embodied AI, personalization in generative AI, and medical reasoning with VLMs. Catch them throughout the day.amazon.science/conferences-an…
Attending #CVPR2026 in Denver? We'll be at booth 349 showcasing our latest research with live demos throughout the conference. Stop by to meet our scientists and see their work in action. Check out the full booth schedule:
Next stop: Denver. 🏔️ Amazon will be at @CVPR with workshops, live demos, and new computer vision research. Come find us at booth 349. #CVPR2026 amazon.science/conferences-an…
A passive optical device called a ShuffleBox and a routing protocol called Spraypoint just made flat datacenter networks as practical as fat trees, with 69% fewer routers and up to 33% better throughput. amzn.to/4uIdylW
Announcing the #AmazonResearchAwards fall 2025 recipients: 🔍 68 researchers 🏫 49 universities 🌏 11 countries Each gains access to 800+ Amazon public datasets and AWS AI/ML tools. Meet the cohort: amzn.to/4uaFNZC
Current LLMs overallocate to MLP layers. A new scaling law presented at #ICLR2026 identifies architectures with up to 47% higher throughput and equivalent accuracy. amazon.science/blog/making-ll…
Amazon Science retweeted
If a model is 50% reliable, it's 0% useful. Michael Giannangeli, Head of Agentic AI at Amazon Nova, breaks down one of the hardest problems in agentic AI: reliability. Models need to match or beat human performance, or they won't get adopted. To close the gap, teams are building an ecosystem of reinforcement learning "gyms" where AI agents can hone their skills. Think of it like a virtual training ground where agents practice tasks through trial and error, building reliability one rep at a time. 💪
The next generation of AI researchers is using Amazon's Trainium chip to build the next AI breakthrough. Teams at @UCBerkeley, @MIT, @CarnegieMellon, and @UCLA are seeing results across ML, healthcare, and quantum computing. aboutamazon.com/news/aws/amazo…
Promptimus, a new automated prompt-engineering framework from Amazon, improves already good LLM prompts by focusing on specific failure points. It achieves the best result on 16 of 20 benchmarks. amazon.science/blog/promptimu…
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