@dddanielwang

ICT Sales/GTM 关心实用的 AI:产品、效率与工程 更多⬇️

Joined July 2024
Jev 类的 Decisions model 就挺适合这种定时任务的 每次轮询用 Decision model 和上下文来给出一个是否调用 LLM 来通知用户的 Yes or No 的决定
众所周知,微信公众号的送达率太低了,即使你关注了某一个博主,比如苍老师,你也是没法第一时间接收到,现在爽了,直接交给grok bot,有更新就给我消息,相当于rss订阅了。我拿卡神的公众号试了试,可行
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未来一年都在北京工作了 这过渡酒店真不赖啊
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从来没像现在这样如此认可去中心化 最自然、最理性的想法,就是把 personal agent 运行在自己能控制的主机上面 如果大模型不能运行在自己的主机(GP)U 上,那至少 personal agent 以及数据要在自己的主机(CPU) 上 现在这些 muse、 grok bot 如此中心化集中一个人生活各个方面隐私的 personal agent 的模式,不会让人感到不安吗... 模型能力的提升以月为单位,而产品的迭代更是以日为单位,同时还想长期“养”一个越来越懂自己的 personal agent,唯一的途径就是把 agent 和数据都保存在自己可控的主机上啊
there’s something quite awkward about all the personal agents in the current hype cycle muse, grok bot, instinct, dots, and whatever google, anthropic will come up with none of them is “mine” i’d be trusting a vendor for some of the most sensitive data about me and bet on them handling it with extreme responsibility. what if they have a data leakage incident? what if they hired a wrong employee? what if they simply break bad? i’d also be betting on their model. right now i’ve set up a lot of my stuff in grok bot, but what if their model falls behind? what if another model becomes 10x better on pure intelligence? then i’ll either miss out on a better assistant, or have to bite the bullet and do a full migration i’d also have to bet on their product. they may not build the features i want. they may not allow me to customize enough. and one day my assistant may show me ads that feels like way too much betting than what i’d be comfortable with, if i truly want literally everything in my life to go through and be taken care of by an assistant with all that considered, i’m more bullish on open source personal agents that run on people’s own computers. but i think these open source projects have to break out of the assumption that their users are developers and they can just throw a repo at them and ask them to launch a terminal a well polished, fool proof, community maintained, vendor agnostic, free personal agent that everyone can run by themselves without locking into a SaaS - that’s what i think many people will need
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Runpod 真是贵嘟嘟的,几乎是vast的两倍
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可爱捏,6.1 Sol还能做出这么细致的示意图
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反正今天reset了,还有一个banked reset 4号过期今天要用,why not github.com/DanielDaniel2201/…
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ChatGPT Work 没有提供主机的规格吧? 不知道它能胜任多高强度的开发工作,连接了Github,帮我改一改个人网站目前看起来还行
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Fireworks 的销售没听说过 KV Cache 除非有什么过人之处,不然美国就业市场这么宽松吗? 国内类似有卖 Token 的 startup 吗,我也可以做销售😂😂
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马斯克大礼包套餐,要是真的就好啦...
One plan for X, Grok, Cursor and Grok Bot. It's called Xpass. Premium $8 • Grok Lite + X Premium • Shared quota • Cursor included, Grok API Plus $30 • SuperGrok + X Premium+ • 4x Premium • Grok Bot, Cursor cloud agents, Bugbot Super $100 • SuperGrok Plus + X Premium+ • 15x Premium • 1080p, faster replies, priority access Ultra $200 • SuperGrok Heavy + X Premium+ • 50x Premium • Fastest replies, earliest access A launch promo is in there too: 50% off the first month, dated Oct 9. 4x / 15x / 50x usage is still unconfirmed.
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真是太酷了😢,上次研究HBM的时候也想做一个类似的 3D 导览,看来可以继续研究一下做出来!!! 当时只简单做了一下实在太草台了:
Most of us don't have access to multi-million dollar NVIDIA gpu sleds (if you do, hit me up). But I wanted to learn how they work, so i build a 3d guide! Unified GPU / CPU systems like this are what's powering all these mega-ai DCs. Incredible what educational tools you can build with llms.
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吞金兽小子,把我每次system prompt都改一遍! 梁叔叔的cache在天上(因为失效了)失望的看着 5.6 Sol 怎么会写出破坏prompt caching的引用逻辑呢?!悲!!!我们模型的基本素养都没了!
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气的半死,这个逻辑我都测试两天了才改,白花多少钱呜呜呜
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当我发现 每月公积金=社保+税 顿时感觉也还行
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开了网络,同时跑 Agent,感觉4 岁的笔记本好烧啊,只跑一个任务的并发都会非常非常烫 该怎么办呢 换新笔记本,物理降温(吹风扇)还是用云电脑呢
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人云亦云,外文抄中文的帖子/账号,一律 mute... 本来 timeline 上面一次就显示两到三个帖子,我还要看一个刚刚看过一模一样的
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6.1 sol 的 TPS马上就会被提高接近两倍 但问题是,昨天看到推友 TPS 只有十几二十几,就算翻了两倍,也还是很慢啊 而且 OpenAI 你们不是总说有非常多的 compute 吗,在很多用户被 Opus 5.5 吸引过去了之后,还是满足不了需求吗
GPT-6.1 Sol is our most demanded model pretty much ever both across both the API and subscriptions. Within ChatGPT & Codex, we were under heavy load, but have brough more capacity online and the speed should get much better in the coming hours, reaching almost twice the speed compared to what we served yesterday.
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我一直想追求言出法随的 AI 体验,但就算是200 TPS 的 Deepseek Flash 在我的use case里也无法做到(当然,也许跟他的雷霆大思考有关) 我用到的任务就是引用里面的,给 Xcalidraw 画布里只有一层 Hidden Layer 的 MLP,再加上一层 Hidden Layer,就耗时了将近 1 分钟,太久了,但是在 UI 层面还是可以优化的,比如体现一步一步改动的工作量,而非从初始状态直接变成最终状态 Inference 工程还有很多进步空间,因为但凡涉及到 Reasoning 和工具调用,那个延迟真的是无法让人保持专注,必须抽空干点别的 让 ChatGPT 搜罗了最快 TPS 模型厂商,最快的就是 600 左右,也难怪 OpenAI 在 fast ultra fast 方面一直有更新,时间就是体验,时间就是金钱!!
为了让 Deepseek Flash 用好 excalidraw MCP,我变成prompt小子的第一天 不得不说,留存 llm/agent trajectory 真的太重要了,简直是debug的金杯
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为了让 Deepseek Flash 用好 excalidraw MCP,我变成prompt小子的第一天 不得不说,留存 llm/agent trajectory 真的太重要了,简直是debug的金杯
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开发者们真是太累太辛苦了,感觉不得不fork了
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鉴定为 Token 太多烧的
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