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10月22日周四
  1. IT之家·人工智能66

    讯飞星火 X2.6 端云一体大模型发布,首次基于全国产算力实现代码和智能体能力突破

    科大讯飞在全球 1024 开发者节发布讯飞星火 X2.6 端云一体大模型,宣称首次基于全国产算力实现代码和智能体能力突破。模型采用 293B-A30B 参数的 MoE 架构,上下文长度拓展至 1M,输入限时 0.9 元/百万 tokens,输出限时 3.6 元/百万 tokens;同时开源星火 X2.6-4B 端侧模型,新增三档推理模式,推理定价限时免费。

  2. meng shao66

    Recursive 发布首个模型 Flint,由其自动化研究系统 Eureka Machine 参与完成,从零训练用时不到 4 个月。

    引用Richard Socher@RichardSocher

    Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine. • Best-in-class fast local coding • Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark • Built from scratch in under 4 months Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.

  3. Dongxi 东锡 NLP44

    Base Labs 发布 release mammoth-1 和 elephant-1,超越 Jev,继续向前推动 decision model 最重要的: 开放权重和 technical report!

    引用Base Labs@baselabs

    Today we release mammoth-1 and elephant-1! We post-trained mammoth-1, the #1 ranked best decision model in the world, and elephant-1, which is the best model under 15B (and beats Jev). We're open-sourcing all model weights and provide a technical report detailing all our training and data methods.

  4. 🚨 AI News | TestingCatalog57

    Recursive 发布首个开源权重编码模型 Flint,采用 Apache 2.0 协议。Flint 是 40B 参数的 MoE 本地编码模型,号称比同类模型快 2 倍,在 64GB RTX Spark 上超过 220 tokens/秒,在 MacBook Pro 上达 125+ tokens/秒。其 Eureka Machine 自动研究系统通过编写自定义 GPU 代码,在不改权重的情况下将 Flint 在 RTX Spark 上提速 55%,权重已在 Hugging Face 开放。

    引用Richard Socher@RichardSocher

    Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine. • Best-in-class fast local coding • Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark • Built from scratch in under 4 months Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.

  5. Rohan Paul64

    Recursive 发布首个模型 Flint,一个 40B MoE 本地编码模型,由其自动化研究系统 Eureka Machine 构建,从零开始用时不到 4 个月,权重以 Apache 2.0 开放。

    引用Richard Socher@RichardSocher

    Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine. • Best-in-class fast local coding • Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark • Built from scratch in under 4 months Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.

10月21日周三
  1. 🚨 AI News | TestingCatalog52

    Coco Labs 发布其首个设计模型 Vyb,能根据品牌网站生成分层、可编辑的营销图形。Vyb 将每个元素放在独立图层,可只修改标题而无需重新生成整个设计;它能从公司网站识别 logo 和精确的十六进制色值,产品照片可以以全分辨率嵌入而不被重新生成,成品设计可导出至 Figma 并保留全部图层。

    引用Anusha Ramesh@anurahk

    I launched the first image and video generation models at Google, and kept asking why all AI designs look the same. AI has brought us the WORST era of design. It made content creation effortless, but it also made 90% of it look painfully generic. My co-founder and I spent 2 years building in stealth to change that. Meet Vyb, the first AI design model that understands your taste like a designer would. RT + comment your website URL and we’ll make your first design.

  2. Rohan Paul54

    Coco Labs 的 AI 设计模型 Vyb 按图层逐个元素构建设计,文字保持可编辑文本、图形保持矢量、照片保持像素,并从网站自动提取 logo、字体和配色。在 145 款 Google 字体上按像素重叠 IoU 打分,Vyb 达到 90.3%,对比中 最强图像模型为 76.0%,该测试的测量上限为 94.4%。由于每层保留原生格式,导出 Figma 时结构完整保留。

    引用Anusha Ramesh@anurahk

    I launched the first image and video generation models at Google, and kept asking why all AI designs look the same. AI has brought us the WORST era of design. It made content creation effortless, but it also made 90% of it look painfully generic. My co-founder and I spent 2 years building in stealth to change that. Meet Vyb, the first AI design model that understands your taste like a designer would. RT + comment your website URL and we’ll make your first design.

  3. Rohan Paul54

    SoMark 团队发布开源文档解析模型 OXR(1.3B 参数),将 PDF 和文档图像转为含布局坐标的 Markdown 或 JSON 的 Agent-Friendly 数据。

    引用SoMark@somarkai

    Beyond OCR. Meet OXR. Only 1.3B. Open source. #1 on olmOCR-Bench, OmniDocBench & DocParsingBench🏆 #1 in parsing speed among open-source models⚡ RSI-powered. A first in document parsing. Turn documents into Agent-Friendly data. If OXR helps, give us a star on GitHub! 🌟