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2024.08.15 NEO合戦2024 (渋谷O-EAST) #バンビのセトリ# SE 青春ギルティ 恋のキャンディ 私心伝心 BPM180 MC Clover とぅーまっそ 星形 MC たくさんの方に見てもらえて、とっても楽しかったです^ᴗ.ᴗ^♡ ババババンビ新体制初披露衣装でした!!🩵 夏🥹🥹🫶🏻🫶🏻🫶🏻バンビ、かわいいですか？👶🏻 #ババババンビ#

老黄老婆暂时保了他。 但是对手不放过他。 刚刚老黄辞职了。 现在CFO当临时CEO，寻找新的CEO. 一个很大可能的内部候选人是 Ian Buck. nvda中国的朋友可以考虑准备简历了。 建议整组打包跳槽，可以拿到比个人跳槽拿到更高的溢价。 可能会提供relocate到美国的机会，不过relocate到美国也毫无意义，除非准备退休。 neo cloud可以抛了。 老黄走了，但老黄埋的雷，挖的坑，都会爆。新CEO必然会和前任划清界限的。 大家一步一步等着吧。

本地无审查大模型的地下军火库今天彻底齐活了 从 8GB 入门卡到 24GB 满血工作站，Hugging Face 三大破甲顶流（Huihui、HauhauCS、DavidAU）把 Qwen 家族最凶残的 5 款无甲神作全放出来了。不仅切掉了烦人的道德说教锁，还完整保留了多模态视觉（Vision）与 MTP 多 Token 极速预测。 直接按你手头的显卡显存对号入座抄作业： 01 全能六边形战神：Huihui Qwen3.8 27B Abliterated 目前本地综合实力最强的破甲王牌之一，逻辑智商在线，原生保留视觉识图能力。 · 16GB 显存：直接冲 UD-IQ4_XS 或 IQ4（约占 14.4GB，黄金甜点档） · 24GB 显存：直接上 Q4_K_M 或 Q5 满血稳跑 · 极简启动：ollama run huihui_ai/Qwen3.8-abliterated仓库地址： 02 暴力狂暴破甲：HauhauCS Qwen3.8 27B Uncensored Aggressive 如果你嫌常规消融不够狠，这款走的是极其激进的深度破甲路线，几乎零拒答，同样带 MTP 加速与多模态视觉。 · 16GB 显存：选 IQ4_XS（约占 15.7GB，刚好卡满显存极限） · 24GB 显存：直接上 Q4 / Q5 仓库地址： 03 极速 MoE 闪电炮：Huihui Qwen3.6 35B-A3B Abliterated MTP 35B 的大身板，但底层是 MoE 混合专家架构，每次推理仅激活约 3B 参数，吐字速度快到飞起，支持视觉。 · 12–16GB 显存：跑 IQ3 / IQ4 配合专家卸载（建议系统内存 32GB+ 兜底） · 24GB 显存：直接全塞进显存跑 Q4，丝滑起飞 仓库地址： 04 激进破甲 + 极速吞吐：HauhauCS Qwen3.6 35B-A3B Aggressive 把 HauhauCS 最凶狠的激进去审查手法塞进了 35B-A3B 的 MoE 架构里，既要完全听话不拒答，又要极致生成速度的兄弟选它。 · 16GB 显存：IQ3 / IQ4 + 专家卸载 · 24GB 显存：Q4_K_M（约 21GB）完美吃满单卡上限 仓库地址： 05 8G 显存小钢炮：Qwen3.5 9B Defiant / Heretic 系列 DavidAU 操刀的 NEO-IMATRIX 极限调校版，搭载 Heretic 消融算法与 MTP，小体积榨出恐怖表现，轻量本首选。 · 8GB 显存：毫无压力轻松秒开 · 12–16GB 显存：显存极其宽裕，剩下的空间直接把上下文长度拉爆 仓库地址： 省流选型指南： · 追求极致智商与多模态全能：无脑冲 01 或 02（27B Dense） · 追求秒级吐字速度与高吞吐：选 03 或 04（35B MoE） · 8G 显卡或轻薄本长文本：直接锁死 05（9B Heretic） 本地跑大模型最爽的就是彻底摆脱云端审核与封号焦虑，搞红队测试、角色扮演和私有 Agent 的兄弟建议先把这份军火库马住备用。 你现在主力机的显卡显存是多少 G？平时更喜欢跑满血 Dense 模型还是飞快的 MoE 架构？ #AI# #大模型# #Qwen# #开源# #Ollama# #本地部署#

My top 5 robotics companies to start a career at, based on 412 open jobs i read: 1. @Figure_robot most open roles of anyone, 101. humanoid robot operators on morning, afternoon and night shifts. 63 of 101 jobs don't mention a degree 2. @1x_tech 3 to 6 month AI Residency at $10K a month. your code ships to NEO robots in real homes. every single job post shows the pay 3. @physical_int robot operator at $25/hr, no degree listed. you teleoperate the arms that train their robot brain 4. @agilityrobotics "Robot Operator II": $102K to $133K. associate degree or equivalent certs, basic Python and Linux 5. @SkildAI robot operator jobs in Pittsburgh and India. you don't have to live in San Francisco to get in the door into humanoids isn't the research team. it's one of these 5

6/ Neo 又押中了一次 Listen Labs 早期曾进入 Neo 加速器，并获得一张 60 万美元的 SAFE。 据估算，这笔投资如今价值超过 2500 万美元。 而就在三个月前，Neo 还通过 Cursor 的收购获得了超过 1000 倍回报。 这笔交易几乎让所有参与者都赢了：Sequoia、Ribbit、Conviction、Pear、Neo，以及 Listen Labs 的创始人与团队。

Salesforce acquires Listen Labs for ~$2b. But who gets the 💰? My usual breakdown below 👇 The company was founded in Sep-23 and had raised less than $100m. Investors will share ~$850m of profits on $96m invested, a ~10x blended. From a huge pivot to a unicorn valuation term sheet they refused, this is truly a wild story ✍️. In the end an incredible outcome for all involved. So let's dive in! 1) The boldest move: walking away from $1.5b 🎲 Listen Labs had a signed $125m Series C term sheet from Menlo at a $1.5b valuation... and walked away from it to sell to Salesforce at ~$2b. This takes a huge amount of courage: few founders turn down a signed unicorn-plus round. @itsalfredw and @florian_jue did it 2.5 years after founding. Huge congratulations are in order for the discipline and execution of the founders here. 2) Founders and team: a life-changing outcome in under 3 years 🥳 By my best estimates, founders and team still own over half the company. At $2b, that's ~$1.1b for them to share. Specifically, assuming a 15% option pool, that is ~$300m for the team and ~$750m for the two co-founders. And, as was the case with Hugging Face, this is all from a pivot. They originally built an AI customer-interview tool to understand why their viral app BeFake was growing, then realised the tool was the business! 3) Sequoia's Bryan Schreier did it again 👑 What few people know is that Bryan was an early backer of Qualtrics... the category Listen Labs is disrupting. Now he led both the seed and the Series A here. By my estimates, those two rounds will return ~$670m combined, or ~25x on ~$27m invested, in under three years. Pattern recognition and industry knowledge have their perks, it would seem! 4) Ribbit: 4x in 8 months ⚡ Ribbit led the $69m Series B in Jan-26 at ~$500m. At $2b, that's ~4x in 8 months. Unbelievable IRR and a great return on a meaningful cheque. 5) Neo does it again, congrats @apartovi 🎯 Listen Labs went through the Neo accelerator early on, which came with a $600k SAFE. On my estimates, that cheque is worth ~$25m+ today. This comes just three months after Cursor's acquisition (a cool >1,000x for Neo). What a hit rate! This one is very straightforward: it is a massive win for everyone. And so congratulations to all involved: Sequoia, Ribbit, Conviction, Pear, Neo and the team!

4/ 但按回报倍数看，早期投资人更夸张。 NEO、OpenAI Startup Fund，以及Nat Friedman、Patrick Collison、Jeff Dean等早期支持者，预计获得数百倍回报。 其中NEO的回报超过1000倍，对应价值约15亿美元。