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Perplexity’s agents are running ads better than ad agencies for business owners.
Computer managed $30k in Meta ad spend for Get Maine Lobster, outperforming their agency. Compared to their usual ads, Computer delivered 3.5x revenue with 63% higher ROAS. It automated creative analysis, ad production, and media buying. Read more: https://pplx.ai/gml
View quoted postIf you are working on tools and agents to do security agents, I would love to talk to you. We have something very cool cooking. Pls dm.
It is now table stakes to be running a 24/7 process of scanning for vulnerabilities and attempting to self-pwn your software/infra. This will be a compliance requirement for any business doing business with others.
🚨 Node.js warns of HIGH-severity security vulnerabilities. Security fixes are coming November 11 for Node.js 26.x, 24.x, and 22.x. All three release lines are affected. Production users should take note. Details: https://nodejs.org/en/blog/vulnerability/november-2026-security-releases
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Computer rebuilt Elon Musk's 2013 SpaceX 3D visualizer app. From the YouTube video alone, Computer built a 7,677-segment Three.js wireframe of SpaceX's Merlin 1D engine, and you turn it with bare hands through a webcam. Try it: https://merlin-hand-control.pplx.app How Computer made it:
View quoted postKimi-K3.1-Pro by Moonshot AI: interesting facts It's huge, and sparse • It has 2.8T total parameters, but only 104B are active per token. • Along with Kimi-K3, it's the largest real model release on the Hub. The next biggest are Qwen3.8-2.4T and DeepSeek-V4-Pro (1.6T). • It has 896 experts and sends each token to 16 of them. (DeepSeek-V4-Pro has 2 times less and Mistral-Large-4 has 7 times less) Clever attention for a 1M-token context • Most of its 93 layers use linear attention (KDA). Every 4th layer uses DeepSeek-style sparse attention, which only looks at the top 2048 tokens. • This is how it handles a 1M-token context (the same as the other frontier open models) • It uses a custom activation called SiTU-GLU and has a 401M-parameter vision encoder (MoonViT-V2), so it takes both text and images. Small on disk for its size • It was trained to run in 4-bit (MXFP4), so the whole repo is only ~1.56 TB. • Stored in regular BF16 it would be about 5.6 TB(!) Benchmarks (from the model card) • It goes back and forth with Claude Opus 5.5 and GPT-6 Astra. It's top of the card's table on BrowseComp (92.1), HLE with tools (70.0) and SWE Marathon (51.7). • It's weaker on pure reasoning without tools and on cyber security. • Moonshot ran most of their own coding evals using the Claude Code harness. License (a modified MIT) • It's free to use, modify and redistribute. • API businesses making over $20M a year need a deal with Moonshot. • Products with over 100M monthly users or over $20M monthly revenue must display "Kimi K3.1-Pro". On the Hub • It went public about 1.5 hours ago and already has 214 likes, about 9× Kimi-K3's first hour. It's #19 on the trending list. • It isn't gated, but loading it in transformers requires "trust_remote_code"
Kimi-K3.1-Pro is now open-weights https://huggingface.co/moonshotai/Kimi-K3.1-Pro
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anyone who says YC has fallen off or doesn’t attract and produce strong founders is completely out of touch, bitter, and/or threatened
View quoted postyour daily dose of open source robotic cuteness
国庆前,我跟部分群友提议,我们错峰出行,大家出门时,我们待在家里上站。 国庆期间,我自己也没出门,带着大家一起上站,同时每天同步最新信息和经验到社群里。 于是社群里国庆期间出单的越来越多了,10 月 6 日,我做了一个决定,#哥飞国庆大撒币 https://x.com/gefei55/status/2107455361389334827 只要在 9 月 28 日至 10 月 8 日期间上站出了单的群友,按照订单数量,每一单我奖励 100 元,每个人封顶 2000 元。 今天,结果出来了,总共有 45 位群友,拿到了我的 4.86 万元奖金。 其中拿到了 2000 元的居然有 15 位。 前 24 名拿到了 1000 元以上奖励。 鼓励大家多多上站赚美金,哥飞是真的很认真在做的。 从2023 年 10 月开始(有可能更早),我们就搞了每个月一次的新词新站比赛,也是为了鼓励大家根据所学习到的知识,多多实践,多多上站。 后来社群里成长起来的一批大手子,早期都积极参与了多次新词新站比赛。 SEO 是一门特别注重实践的手艺活,我相信,多多上站,多多练习,多多复盘,多多总结,是可以让大家真正练出来的。 这里查看完整奖励名单 https://new.web.cafe/ask/bounty/x83dttsuu7
#哥飞大撒币了 在这期间,你的新站每出 1 单,哥飞就奖励给你 100 元,如果出了 2 单,就奖励 200 元,,如果出了 10 单,就奖励 1000 元,单人最多奖励 2000 元,也就是如果你出了大于等于 20 单,都只会奖励 2000 元每人。 #哥飞的朋友们国庆上站征文比赛开始了最高奖金2000元一篇
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