
mtok.market - spot pricing for AI tokens
在非托管现货市场上买卖AI推理代币产能
royashbrook · HN
Show HN: Mtok.market – a non-custodial spot market for AI inference tokens
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在非托管现货市场上买卖AI推理代币产能
royashbrook · HN
Show HN: Mtok.market – a non-custodial spot market for AI inference tokens

统一云平台,集数据库、AI推理、函数、容器和存储于一体。
kiran-ravi · HN
Scalix World – AI native Neo cloud built by two engineers in Rust

Runpod是无服务器GPU推理平台,冷启动低于200ms,按秒计费。
@svpino · X
You can check out Runpod here: Thanks to the Runpod team for partnering with me on this post.

为企业员工提供智慧孪生AI助手,保存机构知识和判断力。
@romanbodnarchuk · X
Check out what I just built with Lovable!

Aurora - 本地AI代理验证系统,提供透明的推理过程和MCP集成。
brandon_grutkowski · Product Hunt
Aurora Glass-box Quantitative AI for Humans and Agents


与AI对话,查看置信度评分和完整推理过程
u/RayanBuilds · Reddit
I’m 18 and built an AI chat app solo. Tear it apart (brutal feedback welcome) Built this solo this year at 18. It’s called Veris, an AI chat + writing assistant. I know, “another chatbot” 😭. So I gave it stuff the big ones don’t. Favorite feature: upload an image and pick a mode: Normal (it analyzes it) or Debate (it actually argues with you about it). Not selling anything. I just want to know: what would an AI have to do for you to use it daily? submitted by

在推理时为 AI 代理注入工程化认知能力。
@frank_brsrk · X
reasoning tools for ai agents

对比和评估 AI 模型在编码、推理、代理和其他基准测试中的表现。
davidtsong · HN
Benchmarklist: track AI benchmarks (2.4k+), models, and capabilities

CoBro 用 AI 扫描竞争对手和市场数据,90 秒内判断初创企业创意是否值得构建。
@Ebrahim_Rio · X
Most founders skip validation and pray. I automated the "worth building?" check. AI scans competitors, Reddit, and market data → Cook or Kill in 90 seconds. Killed? It surfaces the pivot the data actually backs.

用自然语言问题查询电子表格和数据集,生成即时答案、报告和仪表板。
u/maybeImakemoney · Reddit
I built the thing. Now I am not sure the base use case is one people will pay for. Founder here. This started as a side learning project to see whether an LLM could answer questions about Excel data, back when they could not do it well. I built the first version on n8n, with workflows that ingested files, generated metadata with an LLM, and answered questions against the converted data plus that metadata. Then I started using it for my own analysis and report generation, saw that the time sav

用生产追踪镜像来测试AI代理,捕捉错误和性能回归。
aisinghal