
Echo by Tracer
Echo – Fable-level results at 1/3 the cost using open-weight models
adam_rida · HN
Echo – Fable-level results at 1/3 the cost using open-weight models
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Echo – Fable-level results at 1/3 the cost using open-weight models
adam_rida · HN
Echo – Fable-level results at 1/3 the cost using open-weight models

Analyze cryptocurrency markets with Chan Theory patterns, K-line charts, and anomaly detection.
@onehopeA9 · X
用 DAPPOS @dappOS_com 做了一个加密货币缠论分析网站,也是我一直想做没时间做的! 来看看缠论三买的威力: 不是不会写代码。 我自己是程序员,真要硬写当然能写。 但问题是:没时间。🤡 做交易的人都懂,真正消耗人的不是“看一根 K 线”,而是把一堆信息拼起来: K 线结构。 缠论笔、中枢。 一买二买三买。 一卖二卖三卖。 资金费率。 持仓量变化。 成交量异动。 市场舆情。 这些模块涉及太多方面,写得出来,但太费时间。 所以我一直想做一个自己的交易雷达: 接币安历史数据。 用 TradingView 展示 K 线。 自动画缠论结构。 标注买卖点。 再把资金费率、持仓量、成交量和币安广场热度放进去。 想法很清楚。 但一直躺在 TODO 里。 最近用 xbubble 的 Coding 功能试了一下,直接把需求丢进去: “做一个加密货币缠论分析网站,接入币安一年历史数据,用 TradingView 展示 K 线,自动画笔、中枢、一买二买三买、一卖二卖三卖,增加异动分析和币安广场舆情热度。” 它真给我生成了一个能跑的原型。 这次最戳我的不是“AI 会写代码”。 而是 xBubble 把最消耗时间的工程杂活压短了。 以前我自己做: ❌ 搭项目结构 ❌ 爬数据源和图表库 ❌ 写 K 线处理 ❌ 写缠论结构识别 ❌ 做前端交互 ❌ 部署、改样式、修细节 一圈下来,核心想法还没验证,人先累了。 现在变成: ✅ 先描述业务目标 ✅ 让 xBubble 生成可运行原型 ✅ 我再校验规则、调整逻辑、优化体验 ✅ 把时间花在交易理解和产品迭代上 这对程序员其实很有价值。 因为程序员最缺的不是能力,而是时间和注意力。 我这个原型现在大概有几块: 第一,TradingView K 线主图。 用币安数据展示行情,再叠加缠论结构。 第二,笔和中枢。 把原本需要手动盯的结构,先自动画出来。 第三,买卖点雷达。 一买、二买、三买,一卖、二卖、三卖,先帮我筛可能的位置。 第四,异动面板。 资金费率、持仓量、成交量变化,和 K 线结构一起看。 第五,舆情热度。 把币安广场讨论热度也拉进来,看看市场情绪是不是和盘面互相印证。 你可以理解成: 我不是让 AI 替我交易。 我是让 AI 帮我做一个交易前的信息雷达。 我觉得 xBubble 和普通 AI

Compare AI subscription prices across reseller channels to find the lowest rates.
bytedoger · GitHub
awesome-OpenPrice 一个开源的收录全网卡网渠道各种AI订阅价格的项目。打破信息茧房,一站式获取各个渠道的 Claude、GPT、gemini 、cursor产品的最新价格

Upload vendor proposals to get AI-powered side-by-side comparison with red flags and citations.
@nbOlveira · X
A vendor comparison software

Institutional trading journal to track and analyze forex, crypto, and indices using price action and smart money concepts.
@sidhit12 · X
Check out what I just built with Lovable!

Search and compare AI tools by price, features, security, and compliance.
u/CyberMAL · Reddit
There are so many cool AI tools coming out that I couldn't keep up so, I built a site to compare them properly. I don't know about you, but I hit a point where there was a new AI tool every single week and I genuinely couldn't tell which ones were worth my time. I wanted to actually use this stuff, write, make images, build things, get organised, but figuring out the right tool for each job was a mess. So I'd do what everyone does. Search "best AI writing tool," "best AI voice generator,"

Generate AI images from text or images and compare outputs across multiple models.
Seedream 5.0 Pro — 多模型 AI 图片工作台,支持文字生图、图片生图、复杂布局与多语言文字编辑

Real-time market analysis and digit predictions for Deriv volatility index trading.
@CollohBrax · X
Check out what I just built with Lovable!

AI platform for macroeconomic research with daily analysis, central bank monitoring, and trading tools.
@ChrizBogota · X
A great demo of why in Financial Markets you have to use Grok, it's not affected by "training cut-off date" like the other models. is 100% run on Grok, (but mostly built with Claude).

A public ranking platform where projects compete for top spots through bidding.
@wahedsikder · X

View and compare public opinions and benchmark ratings for leading AI models.
u/TasteMysterious5285 · Reddit
I built AI Census, a live field bulletin for how people are actually talking about AI models I’ve been building AI Census, a public “field bulletin” for how people are talking about current AI models. I kept running into the same problem: benchmark tables tell me how a model performs on a test, but not whether people are actually finding it useful, frustrating, reliable, etc. So I built a rolling view from public technical conversations across Reddit, Hacker News, Bluesky, GitHub, and Huggi

Directory comparing relay services with exchange rates, initial credits, available groups, and performance data.
@mutou1852 · X
做了一个中转站点收录网站,展示倍率、初始额度、可用分组和实测性能数据。 希望帮大家更快找到适合自己的站点。