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444作者: sidcool大约 14 小时前原帖
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19作者: sdan大约 13 小时前原帖
Hey - I&#x27;ve been playing with LLMs since GPT-2 and recently experimented with fully generative UIs where the HTML&#x2F;Canvas are generated just-in-time.<p>Every post on the feed( on slop&#x2F;duck&#x2F;storytime) you see is streamed and generated just-in-time with HTML and into a Canvas with Gemini 3 Flash.<p>Comments and DMs are bidirectionally linked with a Cloudflare Workers Durable Object which is why they feel so fast. Every generated post is saved into a DO SQLite which is then served into the &quot;Following&quot; feed so it can be served quicker.<p>This was inspired by Wikitok, a VSCode Extension I made around brainrot, and another fully generative UI site I made.
16作者: donutthejedi大约 12 小时前原帖
I (17y&#x2F;o) have been developing a rocket launch simulation that allows the user to explore what it&#x27;s like launching a rocket from earth and putting it into orbit. This idea originally started as an educational simulation but as i&#x27;ve gone more down the rabbit hole the more i&#x27;ve wanted to make it realistic. The problem is that I&#x27;ve never had a formal orbital mechanics class or anything like that so I don&#x27;t know what I&#x27;m missing, what I currently have implemented is:<p><pre><code> Variable gravity Variable Atmospheric drag (US Standard Atmosphere 1976) Multi-stage rockets Closed-loop guidance &#x2F; pitch programs (works well within ranges 350km to 600km) Orbital prediction and thrusting options to change your orbit. </code></pre> The feedback I&#x27;m looking for is: UI improvements and possible future physics implementations that I can work on.<p>Current code and physics can be found at: <a href="https:&#x2F;&#x2F;github.com&#x2F;donutTheJedi&#x2F;Rocket-Launch-Simulation" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;donutTheJedi&#x2F;Rocket-Launch-Simulation</a>
13作者: hiepler大约 12 小时前原帖
I built this as a personal open-source project to explore how EU AI Act requirements can be translated into concrete, inspectable technical checks.<p>The core idea is local-first compliance: – risk classification (Articles 5–15, incl. prohibited use cases) – bias evaluation using CrowS-Pairs – automatic Annex IV–oriented PDF reports – no cloud services or external APIs (browser-based + Ollama)<p>I’m especially interested in feedback on whether this kind of technical framing of AI regulation makes sense in real-world projects.