
Dental Anatomy Helper by Athina
测试你对牙科解剖学的知识,包括珐琅质、牙列和牙齿编号。
@athina586610681 · X
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测试你对牙科解剖学的知识,包括珐琅质、牙列和牙齿编号。
@athina586610681 · X
Check out what I just built with Lovable!

Optimiza tu clínica dental con Dent CMS. Agenda citas, administra pacientes, controla pagos y accede a historiales clínicos desde cualquier dispositivo. Prueba gratis durante 30 dí
@kinbloomuupk · X
I created a dental clinic management system (CMS) for dental clinics in Latin America, but I'm still looking for clinics through direct contact because I don't have money for advertising.

24个口腔和颌面疾病的交互式临床图谱,包含放射学和组织病理学内容。
@dentistbangla · X
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连接 GitHub,自动将提交和部署转化为可分享的内容。
@plaqueboywest · X
I’m building Super Dent X. Connect GitHub once, and it remembers your build journey for you. Curious what you think: Would love your feedback !

Snap a photo of any confusing paper — medical, legal, school or bank — and get it explained in plain language, in your language.
@AToluwain · X
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用AI快速转录视频和音频,配有40多个工具生成字幕、摘要、翻译和图像放大。
@indrapurnomos · X
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将你的笔迹转化为可安装的OTF字体
@alpsariyer · X
Building Penform, a browser-based tool that turns handwriting into a real installable font with supporting alternates.

语音控制牙科粘接计时器,中文语音命令操作,椅旁免手操作。
@TianhouZ46664 · X
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AI form builder that turns voice, photos, and messy notes into clean structured data. 200+ templates, analytics, and integrations. 14-day Pro trial, no card.
@faizydroid · X

A public leaderboard of YouTube videos, ranked by money. Your crown lasts exactly as long as nobody pays more. Somebody always pays more.
@ascndnt_alchmy · X

从视频生成个性化教科书,无需重复观看。
@mdTouseef_ · X
Never re-watch any video.

具有30个语音和16种语言的轻量级神经文本转语音系统,可在微控制器上运行。
u/Affectionate_Hat_585 · Reddit
Building smallest neural Text to speech system that runs on microcontroller cheaper than cup of coffee : 30 voices, 16 languages Most TTS is a cloud API call or a multi-gigabyte model. I wanted the opposite — the smallest, most honest neural TTS I could make, small enough to run somewhere with no server at all: a microcontroller, a browser tab, whatever you've already got. What it turned into: sanoTTS, 30 trained voices across 16 languages, ranging from 294,642 parameters (337