{
  "version": "https://jsonfeed.org/version/1.1",
  "title": "AI News: Amazon Science",
  "home_page_url": "https://ai-news.ypetit.net/sources/amazon-science/",
  "feed_url": "https://ai-news.ypetit.net/feed/source/amazon-science.json",
  "description": "Latest publications from Amazon Science, aggregated by AI News from the official source.",
  "language": "en",
  "items": [
    {
      "id": "https://www.amazon.science/blog/better-speech-synthesis-for-audiobooks",
      "url": "https://www.amazon.science/blog/better-speech-synthesis-for-audiobooks",
      "title": "Amazon Science: Better speech synthesis for audiobooks",
      "summary": "“Controllable text to speech” makes speech more expressive, character voices more distinct and consistent.",
      "date_published": "2026-10-23T15:20:02.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    },
    {
      "id": "https://www.amazon.science/blog/the-science-behind-torchneuron-amazons-new-pytorch-backend-for-aws-trainium-chips",
      "url": "https://www.amazon.science/blog/the-science-behind-torchneuron-amazons-new-pytorch-backend-for-aws-trainium-chips",
      "title": "Amazon Science: The science behind TorchNeuron, Amazon’s new PyTorch backend for AWS Trainium chips",
      "summary": "Runtime optimizations and a thorough evaluation process driven by agentic AI help ensure that models written in PyTorch will execute efficiently and reliably on Trainium systems.",
      "date_published": "2026-10-22T19:36:42.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    },
    {
      "id": "https://www.amazon.science/blog/strengthening-ai-safety-evaluation-through-independent-third-party-review",
      "url": "https://www.amazon.science/blog/strengthening-ai-safety-evaluation-through-independent-third-party-review",
      "title": "Amazon Science: Strengthening AI safety evaluation through independent third-party review",
      "summary": "How Amazon partnered with AVERI to independently assess — and improve — our internal safety testing of Amazon models.",
      "date_published": "2026-10-20T17:57:55.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    },
    {
      "id": "https://www.amazon.science/blog/can-we-change-an-ai-models-architecture-without-retraining-it-from-scratch",
      "url": "https://www.amazon.science/blog/can-we-change-an-ai-models-architecture-without-retraining-it-from-scratch",
      "title": "Amazon Science: Can we change an AI model’s architecture without retraining it from scratch?",
      "summary": "“Priming” reuses pretrained Transformer weights to build models with more efficient architectures at less than 1% of the original training cost and with throughputs up to twice as high.",
      "date_published": "2026-10-12T17:36:18.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    },
    {
      "id": "https://www.amazon.science/blog/graph-centric-agentic-intelligence",
      "url": "https://www.amazon.science/blog/graph-centric-agentic-intelligence",
      "title": "Amazon Science: Graph-centric agentic intelligence",
      "summary": "Augmenting a network graph with agentic AI produces a “digital twin” that can help isolate network failures.",
      "date_published": "2026-10-01T12:54:31.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    },
    {
      "id": "https://www.amazon.science/blog/a-kernel-centric-path-to-real-time-video-generation-on-trainium",
      "url": "https://www.amazon.science/blog/a-kernel-centric-path-to-real-time-video-generation-on-trainium",
      "title": "Amazon Science: A kernel-centric path to real-time video generation on Trainium",
      "summary": "Using the Neuron Kernel Interface, a Reactor–AWS collaboration tackled the dynamic shapes, memory access patterns, and cache management that make real-time autoregressive diffusion hard—building techniques that generalize across models.",
      "date_published": "2026-09-25T14:55:00.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    },
    {
      "id": "https://www.amazon.science/news/amazon-launches-research-initiative-with-stanford-university-to-advance-ai-and-science",
      "url": "https://www.amazon.science/news/amazon-launches-research-initiative-with-stanford-university-to-advance-ai-and-science",
      "title": "Amazon Science: Amazon launches research initiative with Stanford University to advance AI and science",
      "summary": "The collaboration aims to advance research while broadening participation and translating discovery into real-world solutions.",
      "date_published": "2026-09-21T19:31:59.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    },
    {
      "id": "https://www.amazon.science/blog/advancing-ai-for-biology-teaching-models-to-design-and-characterize-antibodies",
      "url": "https://www.amazon.science/blog/advancing-ai-for-biology-teaching-models-to-design-and-characterize-antibodies",
      "title": "Amazon Science: Advancing AI for biology: Teaching models to design and characterize antibodies",
      "summary": "Three new papers from Amazon Bio Discovery address bottlenecks in AI-driven antibody engineering, from benchmarking binding predictors to experimentally validating de novo design.",
      "date_published": "2026-09-21T17:51:00.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    },
    {
      "id": "https://www.amazon.science/blog/why-dont-machine-learning-research-agents-overfit",
      "url": "https://www.amazon.science/blog/why-dont-machine-learning-research-agents-overfit",
      "title": "Amazon Science: Why don’t machine learning research agents overfit?",
      "summary": "New research indicates that AI agents learn compressible models of data, which don’t have enough space to enable memorization.",
      "date_published": "2026-09-10T15:03:39.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    },
    {
      "id": "https://www.amazon.science/blog/developing-provably-correct-rust-code-with-verus",
      "url": "https://www.amazon.science/blog/developing-provably-correct-rust-code-with-verus",
      "title": "Amazon Science: Developing provably correct Rust code with Verus",
      "summary": "How the Verus \"program verifier\", which automatically checks code against a mathematical specification of its functionality, helps increase security assurance in software projects.",
      "date_published": "2026-08-31T15:35:33.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    },
    {
      "id": "https://www.amazon.science/blog/when-llm-judges-agree-should-we-believe-them",
      "url": "https://www.amazon.science/blog/when-llm-judges-agree-should-we-believe-them",
      "title": "Amazon Science: When LLM judges agree, should we believe them?",
      "summary": "Discounting the opinions of LLM judges with highly correlated outputs ensures that panels of judges reflect a true diversity of perspectives.",
      "date_published": "2026-08-26T17:10:40.000Z",
      "tags": [
        "research",
        "Amazon Science"
      ],
      "authors": [
        {
          "name": "Amazon Science"
        }
      ]
    }
  ]
}