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安徽合肥
Joined September 2020
感受一下中环的万圣节氛围 #香港 #中环 #万圣节
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DarkCom retweeted
科研入门手册 没有科研的需求,只是比较喜欢新知识,有阅读文献想法的也可以看看 LAMDA-NeSy / Research-Starter-Kit
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Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
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DarkCom retweeted
「中英双语字幕」这是我见过最清晰、能讲透 ChatGPT 和 Claude 到底怎么构建出来的课。斯坦福大学、免费LLM课程 看完你会看到很多“原来如此”的设计。 我觉得学这些东西最有意思的地方,就是把“模型内部大概有点魔法”,慢慢换成自己能顺着讲出来的过程。以后看新模型的介绍,至少知道它改的是哪一环,也能分清自己理解了什么、哪些地方还只是记住了名字。 “预测下一个 token”这句话,大家都会说。可再往下问:文字怎么变成数字?为什么一个单词还要拆开?Attention 到底在算什么?模型训练时,又在改什么?几个问题一连起来,就能发现自己哪里还没弄懂。
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今年暑假还在折腾supabase + resend + cf,然后发现cf也有d1,也有邮件发送服务的,本来就不想写后端找那么多baas服务,这下好了,一个cf平台直接把baas服务包揽了,这个月满心欢喜开了5刀的worker paid直接一个平台梭哈了。就算cf崩了那也是互联网基建带着楼上一堆大公司一块崩哈哈哈哈
现在做个个人小工具或者出海小产品,不建议买云服务器、配环境、折腾 Nginx,纯属自己给自己找罪受。 静态前端直接扔给 Cloudflare Pages,连着 GitHub 推送就能自动构建,全球 CDN 一分钱不收。 后端接口全丢给 Cloudflare Workers,毫秒级冷启动,每天几十万次请求的免费额度根本用不完。 数据库直接上 D1,本质上就是开箱即用的边缘 SQLite,不用自己管连接池,更不用天天提防数据库端口被扫。 用户上传的文件和图片丢进 Cloudflare R2,兼容 S3 协议,出网流量费直接免掉。 验证码和通知邮件接个 Resend,每月 3000 封免费额度,写两行代码直接发,不用自己去伺候邮件服务器折腾解析。 整套全托管组合跑下来,每月几十万次请求直接零账单。 省下买服务器的几十块钱是小事,最爽的是不用半夜被叫醒看日志,也不用操心磁盘满不满。 不用伺候机器,小东西安安静静跑在边缘节点,用到地老天荒也不用掏一分钱。
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而且d1的免费额度还比supabase多,supabase就送俩数据库,cf d1送10个免费额度的数据库
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essa foi a melhor foto de comida que eu já vi em toda a minha vida.
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I have been saddened to hear of the passing of the great Liu Huan, who I had the pleasure of singing with at the 2008 Beijing Olympic Games, performing the opening theme song, ‘You and Me’. He was an amazing talent and a true gentleman. He will be greatly missed. R.I.P. Sarah
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Chinese President #XiJinping's time in Washington, D.C. - A new chapter for China-US ties
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DarkCom retweeted
Thank you @POTUS and @FLOTUS for a truly remarkable evening at the White House State Dinner welcoming President Xi and Madame Peng. Honored to be part of such a special occasion.
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Legacy media REFUSED to show you a SINGLE SECOND of President Trump's speech and historic state dinner with Xi Jinping tonight at the White House So here's the ENTIRE thing, from start to finish, with translations for Xi's speech DO NOT LET LEGACY MEDIA KEEP YOU IN THE DARK
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A historic arrival at the White House.
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🇨🇳🇺🇸
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DarkCom retweeted
JUST IN: 🇨🇳🇺🇸 Chinese President Xi Jinping in the Oval Office with President Trump.
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习近平主席在白宫欢迎仪式上的致辞(全文) 尊敬的特朗普总统和梅拉尼娅女士, 女士们,先生们,朋友们: 很高兴对美丽的美利坚合众国进行国事访问,感谢特朗普总统和夫人给予我和我夫人的热情款待。首先,我谨代表14亿多中国人民,向美国人民致以诚挚问候,向美国独立250周年表示热烈祝贺! 中国和美国都是伟大的国家,中国人民和美国人民都是伟大的人民。我这次应特朗普总统邀请访美,是为传承友谊而来,为拓展合作而来,为增进两国人民福祉而来。 面对当今世界之变、时代之变、历史之变,中美两个大国肩负着促进人类发展进步的历史重任。 特朗普总统今年访华期间,我们一致同意构建中美建设性战略稳定关系,受到两国人民和国际社会广泛欢迎。我愿同特朗普总统一道努力,引领中美关系这艘大船行稳致远。 ——我们要加强沟通。中美两国国情不同,通过坦诚、深入、持续的对话能够增进理解、求同存异、积累互信。我和特朗普总统彼此尊重,已建立良好关系,保持经常性沟通。我们鼓励两国外交、经贸、财金、执法、人文等各部门加强沟通,支持两国立法机构扩大交流。 ——我们要真诚合作。中美两国利益深度交融,合作空间十分广阔。虽然中美合作不可能解决世界上所有问题,但没有两国合作,世界上很多问题都难以解决。中国开放的大门始终敞开,欢迎美国企业来华投资兴业,希望美方公平对待中国企业,共同拉长合作清单,压缩问题清单。中美两国都是人工智能大国,有能力也有责任发展好、管控好人工智能,确保人工智能发展始终受控于人、造福于民。中方愿同美国加强禁毒、执法等合作。双方可以增加直航航班,让双方人员和经贸往来更加便捷。 ——我们要和平共处。我多次讲,中美两个大国合则两利、斗则俱伤。中美不必讳言竞争,但竞争应该是良性的、有边界的,应该是你追我赶的赛跑,而不是你输我赢的角斗。中美双方必须守住不冲突、不对抗的底线,也一定能走出一条两个大国在这个星球上的正确相处之道。两国军队要保持常态化对话,完善危机沟通和预防机制。“修昔底德陷阱”是可以跨越的。 女士们、先生们、朋友们! 第二次世界大战期间,中美并肩抗击法西斯侵略。对于这段历史,中国人民不会忘记,美国人民也没有忘记。中美关系希望在人民、未来在青年。这里,我愿宣布,未来5年,中方将邀请10万名美国青少年来华交流学习。 大熊猫是中美两国人民友谊的使者。今天,我要分享一个好消息,再过几天,大熊猫“平平”、“福双”就会落户亚特兰大动物园,同美国人民见面。 女士们、先生们、朋友们! 实现中华民族伟大复兴和让美国再次伟大并行不悖。让我们秉持人民情怀、展现历史主动,不断推进中美两国人民友好事业,携手共建一个更加美好的世界! 谢谢大家!
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得益于中国强大的产业链,MFI认证芯片只需要2块多钱,高大上的 #carplay 就可以在任何车机上使用了。测试的国产车车机是Android9的系统,无线黑屏。但有线连接非常流畅。帧率很高。现在唯一的问题是音频通道获取不到,目前无声。感谢 @__shilapi__ github.com/shilapi/xcertplay 项目。
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当地时间2026年9月23日下午,习近平主席乘专机抵达华盛顿,应美国总统特朗普邀请,对美国进行国事访问。 习近平和夫人彭丽媛抵达华盛顿安德鲁斯空军基地时,特朗普和夫人梅拉尼娅热情迎接。特朗普表示,很高兴在华盛顿接待习近平主席和彭丽媛女士,这是一次举世瞩目的访问。习近平主席是伟大的领导人,这是一个伟大的时刻。我期待同习近平主席深入交换意见,推动两国关系发展。 美国儿童向习近平和彭丽媛献上鲜花。礼兵分列红毯两侧致敬,军乐团奏中美两国国歌,现场鸣放21响礼炮,战机飞越致敬。 习近平发表书面讲话,代表中国人民向美国人民致以诚挚问候和良好祝愿。 习近平指出,中国和美国都是伟大的国家,中国人民和美国人民都是伟大的人民。中美两国人民长期友好交往,双方利益深度交融,两国应该成为伙伴而不是对手,实现中华民族伟大复兴和让美国再次伟大,完全可以并行不悖、相互成就、造福世界。特朗普总统今年5月访问中国时,我们同意构建中美建设性战略稳定关系,为未来中美关系发展作出战略指引。中美双方应该相向而行,推动形成合作为主、竞争有度、分歧可控、和平可期的稳定关系,走出一条新时代中美两个大国正确相处之道。 习近平强调,世界在发展,时代在变化,但中美两国和平共处的历史逻辑没有变,两国人民友好交往的良好愿望没有变,国际社会对中美两国的普遍期待没有变。我期待同特朗普总统就关乎两国关系和世界局势的重大问题深入交流,不断丰富中美建设性战略稳定关系内涵,拓展中美各领域交流合作空间。我也期待同美国各界人士广泛接触、厚植友谊。相信在双方共同努力下,这次访问一定会取得丰硕成果,为两国人民增进福祉,为世界和平增添希望。 蔡奇、王毅等陪同人员同机抵达。 先期抵达的中共中央政治局委员、国务院副总理何立峰,中国驻美国大使谢锋也到机场迎接。 习近平乘车从机场赴下榻饭店途中,华侨华人和留学生代表聚集在道路两旁,挥舞中美两国国旗,热烈欢迎习近平主席到访。
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President Donald J. Trump and First Lady Melania Trump greet President Xi Jinping of China and Madame Peng Liyuan upon their arrival in Washington, D.C., ahead of the state visit at the White House.
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盒子世界
SOCIAL EXPERIMENT: If you come across this tweet, name the game that made you fall in love with video games. DO NOT read the replies before you comment.
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