与「Analytics」相关的搜索结果

Big news: Qwen3.8-Max by @Alibaba_Qwen just landed at #4# on the Frontend Code Arena leaderboard with a score of 1,668! With 1,668 points, Qwen3.8-Max is trailing only Claude Opus 5 (Max) with 1,705 pts and Kimi K3 (Max) with 1,676 pts, on par with Claude Opus 5 (High) with 1669 pts. It also ranks high across all domains: #2# in Consumer Product #3# in Brand & Marketing, Reference-based design, Gaming, and Content Creation Tools #4# in Data & Analytics #5# Simulations Dig into the thread for more details and to see how it also performs on real-world tasks in the Text Arena. Congrats to @Alibaba_Qwen on this huge release!

DeepSeek-V4-Flash-High by @deepseek_ai is #7# overall in the Frontend Code Arena with 1,586 pts! It’s #3# among open. In categories it’s #4# in Consumer Product, #6# in Reference-based Design, Data & Analytics, Gaming, and #7# in Brand & Marketing. This is an impressive improvement from DeepSeek-V4-Flash-High-Preview, a +154 pt jump. Even more impressive is the jump from DeepSeek-V4-Pro-Preview, a +121 point improvement.

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Despite recent tech stock selloffs, are hedge funds still fundamentally bullish on AI? Vincent Lin, co-head of Prime Insights and Analytics in Global Banking & Markets, discusses his observations of the hedge fund industry:

⚪️ New App: Slate — a voice journal built on one rule: nothing leaves your phone. 100% Apple, top to bottom. Transcription by SpeechAnalyzer on device. Reflection by the 3 billion parameter Apple Intelligence model on the Neural Engine. Storage in SwiftData. Swift 6, SwiftUI, Liquid Glass. Zero third-party code in the binary. There's no account. No analytics. No tracking. No third party SDKs. No network calls. The app is private because there is nothing to collect. Turn on airplane mode and everything still works. There's no server. You speak your mind and slate writes it down. It notices patterns and reads your week back to you in a summary every Sunday. The local model is an observer. It never replies or advises or comforts. When it has nothing real to say, it says nothing.

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America just had its AI Sputnik moment. Kimi K3 dropped a bombshell: 2.8 trillion parameters, the largest open-weight model ever built headed. straight to number one. Possible built on chips two generations behind NVIDIA's best, under US export controls designed to make exactly this impossible -- K3 is #1# in front-end code and six other domains: marketing, design, data analytics, consumer products, simulations, and content creation. -- The model designed its own chip for its next generation and wrote its own inference kernels. Recursive -- 70% of elite AI researchers are not US citizens. The founder of Moonshot AI earned his PhD at Carnegie Mellon and started a Chinese AI startup one year into his US program. -- Bonsai 27B: a GPT-5 class model now runs entirely on a smartphone at 6 gigabytes.

Big news: Kimi-K3 by @Kimi_Moonshot is now #1# in the Frontend Code Arena with 1679 pts, surpassing Claude Fable 5. This is a 17-place jump from Kimi-k2.6 (#18# -> #1#). In Frontend, Kimi-K3 ranked #1# in 6 of 7 domains: Brand & Marketing, Reference-Based Design, Data & Analytics, Consumer Product, Simulations, and Content Creation Tools, landing #2# only in Gaming behind Fable 5. The full model weights will be released by July 27. Congrats to the @Kimi_Moonshot team on this major milestone!

Even the fastest AI agents need fresh data. VeloDB helps enterprises unify analytics, search, and AI retrieval, giving agents better context to act on. Learn how IMDA Accreditation supports firms like VeloDB:

30天赚了快1万美金 这还只是一个平台的 他做的是长视频每天条视频20分钟以上 2天更新一条 我仔细看了一下 他是AI+实拍视频(这就要去网上找一些纪录片的素材了) 1、用YouTube搜索建议 + vidIQ/Google Trends找高搜索量、 evergreen 的神秘历史话题。确认有足够素材支持20分钟左右视频，优先有视觉冲击力的题材。 2、脚本创作（1-2小时） 用Claude（或多模型组合）根据选题生成初稿。 提示词强调：强钩子、清晰叙事结构（问题-探索-高潮-总结）、事实准确、故事化表达。 关键改进：人工认真审核、修改、添加独特洞见或分析，让内容有个人视角。目标是高留存+可信。 3、分镜与视觉生成（2-4小时） 把脚本拆成详细场景提示。（Seedance 2.5或其他顶级模型）生成片段。 重点prompt：统一电影级风格、历史细节准确、动态镜头、神秘氛围。必要时混合少量真实素材或手动微调，确保连贯性和准确性。 4、配音与音频（30-60分钟） 用ElevenLabs生成自然、带情感的旁白，根据脚本调整语气和节奏。叠加高质量背景音乐和音效，增强沉浸感。 5、视频编辑与合成（1-2小时） 用CapCut（高级功能）或DaVinci Resolve等工具剪辑片段、加转场、字幕、文字动画、章节标记。严格控制节奏，每几分钟设置高潮点。最终人工完整检查流畅度和质量。 6、标题、缩略图、描述优化（30-60分钟） AI生成多个标题选项（用疑问、数字、神秘词），选最有点击潜力的。缩略图用AI工具生成高对比、神秘视觉 + 大胆文字，再用Canva精修。描述包含关键词、时间戳、吸引人的卖点。 7、上传与发布 填写优化后的描述、标签、播放列表，设置端屏和卡片。使用分析工具监控表现。 8、发布后迭代 查看YouTube Analytics（平均观看时长、流量来源等），总结什么有效，快速调整下一条。保持稳定产出频率。 需要注意的是现在油管严打批量生产的低质内容 （就是说纯AI，没有人工） 很容易被没收收益 YouTube现在强调AI内容必须有显著 人类原创的输入和真实价值