Eric Zhao

234 posts

Eric Zhao

Eric Zhao

@zhaopenghui

iOS App, Android App & Django Backend Developer, Former Windows Client Developer, C/C++/Golang/Java/Objective C/Python.

Singapore Katılım Mart 2009
481 Takip Edilen113 Takipçiler
Eric Zhao
Eric Zhao@zhaopenghui·
Fable 5 is a fantastic model👍
Jason Zook@jasondoesstuff

I've been using Fable 5 and GPT-5.6 Sol A LOT the past few days. Both on effort level high. Three different projects with vastly different codebases. Some thoughts from real-world use... 1. Fable 5 **never** makes mistakes. Not once. I've given it complex features and it never randomly messes up. It's actually blown my mind a bit. 2. GPT-5.6 Sol gets it right 50% of the time. It hasn't deleted any production code, which is great, but it also makes stupid mistakes and just forgets to do part of a feature entirely. I find myself having to go back and forth with GPT-5.6 just as much as I did with GPT-5.5. 3. I built a Captions feature into our video editing app (SceneRoll) in two separate workspaces, one with Fable 5 and one with GPT-5.6 Sol (same starting prompt). Fable 5's was nearly perfect out of the gate (a couple small UI tweaks). GPT-5.6 Sol didn't even have the captions playable on video 😂. I spent an additional hour and then finally just gave up on GPT. 4. Fable 5 thinks about a lot more edge cases. It's going 4-5 steps further without telling it to even do that. 5. GPT-5.6 Sol does not think very far ahead. Yes, it's better than 5.5, but I wouldn't say noticeably. 6. Fable 5 is a more creative thinker. I asked it build a gamification trial onboarding flow for our content creation app (Solo Content Studio). It was REALLY good. It thought through little animations, details, and even small alerts to give to the user. 7. GPT-5.6 Sol can work within a brand system well, but it does deviate randomly. It LOVES trying to shove a dark mode moment and random shapes into a page. Fable 5 never does this. It just follows the brand system and never invents any random design treatments. 8. I am NOT A DEVELOPER, so take this with a grain of salt: GPT-5.6 Sol writes more code than Fable 5. It seems to just try to do more or write more, when it really doesn't have to. On a feature that's 1,000 lines of code, Fable 5 usually removes 15% of what GPT-5.6 Sol wrote. 9. GPT-5.6 Sol wins by a mile on actual usage. Think of it like a Toyota Prius. It's going to give you 80 MPG and you're never going to need to worry about your usage. Fable 5 is like a (token) gas-guzzling SUV. You feel how much usage it tears through. 10. I used "Ultra" mode on both. I'm not entirely sure I see the point, unless you just want to YOLO your usage and have it work on something big overnight. I would only trust Fable 5 to work overnight in Ultracode. It would nuke usage, so I'd rather just babysit it during the day and get a lot more done with the usage. 11. I have a 13-year old codebase (Teachery) that I've tried to use GPT-5.6 Sol on multiple times, and multiple times it cannot do the simplest of tasks correctly. I don't know if it's just getting lost in the old spaghetti code or what, but it fails to do simple things like take a list of 140 users, only show 15, paginate the rest. Fable 5 accomplished this in 1 sentence and 1 attempt. GPT failed 3 times on this task. 12. Unrelated to code, I feel like Fable 5 and GPT-5.6 Sol are on the same playing field when it comes to brainstorming, analysis of data, and big picture thinking. Neither feels better than the other. 13. Oh, when you give GPT-5.6 Sol a complex task, it will spawn ONE MILLION AGENTS 😅. It's actually kind of insane. I don't care that it does this, but I find that Fable 5 feels more conservative with its agents. It uses them, but it doesn't just whack 20 of them onto tasks. FINAL THOUGHTS... The takeaways above, were based on singular use with each model. My typical building flow is Fable 5 as planner/reviewer, GPT-5.6 as code writer, Fable 5 deploys Opus/Sonnet as agents to verify and test. This is the best way to squeeze the most juice out of both models (and really, just save as much Fable usage as possible). Like many other people, I'm going to be sad to see Fable 5 goes to usage credits only. My hope is that Opus 5 ends up with all the same reasoning abilities, and can orchestrate and manage big tasks like Fable 5 does. But, being totally honest, if I have to pay $200-$500 in Fable 5 usage credits a month to continue to use it with sky-high confidence and accuracy, I’ll do it in a heartbeat.

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Jerry
Jerry@jerry_230925·
@0xVeryBigOrange 市中心的住宅本地人不喜欢 因为没生活气息 没学校。bukit timah , river valley 就卖的很好。新加坡本地人不可能去买condo,你对本地人富人是不是有什么误解。
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很大很大的橙子
很大很大的橙子@0xVeryBigOrange·
新加坡房产市场因为对国外人60%税,高端住宅几乎无人问津,新加坡本地人不可能去买condo,去年几个比较好的楼盘,开盘至今一路降价,很少人买。
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Michael McNair
Michael McNair@michaeljmcnair·
Arguing that Elon Musk’s success is due to “narrative control”, luck, or riding others coattails is such an implausible claim that it functions as a useful litmus test for a persons analytical judgment. This isnt about whether you like Elon Musk. I don’t know him, and I am largely agnostic about him as a person. But I do know his record as a CEO, and studying management and business strategy has been a major part of my job for the past 20yrs. From that perspective I can tell you that Musk isn’t just a good CEO. He is one of the most effective CEOs of our generation. When I hear people write off Elon’s achievements bc someone else started these companies, it is a clear tell that they don’t understand business. Ideas are a dime a dozen. They are not what makes a great CEO. Execution is. And part of execution is recognizing a good idea when you see one and understanding how to build something around it that actually works. Tesla was months from bankruptcy when Musk took control. It’s now the company that forced every major automaker on earth to retool their entire product strategy. SpaceX was a startup that serious people in the aerospace industry dismissed as a fantasy. It now conducts more orbital launches than the rest of the world combined and has driven launch costs down by an order of magnitude. Starlink is on track to become one of the most consequential communications infrastructure projects in history. These aren’t narrative achievements. Theyre tangible businesses that work, at scale, in industries where failure is the default condition. And there’s a consistent pattern where Elon has repeatedly looked crazy, and then been right. The people who called reusable rockets a dream watched a booster fly back and land itself. The people who said a mainstream consumer EV company was impossible watched Tesla restructure the global auto industry. This is a person who has repeatedly seen something others cant see yet, absorbs the ridicule, and then builds toward it anyway. The PayPal criticism this author pushes is another perfect ex. Do you know how he became CEO? Elon identified the importance of network effects in the late 90s and realized he could take advantage of cheap capital during the internet bubble to pay users to join his network. He was labeled a lunatic. Losing money upfront to lock customers into your network is well understood now but it wasn’t back then. Confinity was forced to merge bc they couldn’t compete with it…and that’s based on Peter Thiel’s own account in Zero to One. Elon was considered reckless at the time. But he was right. And now we have people criticizing Musk’s Mars goal. But as Ben Thompson explained, Mars is the strategic North Star that forces you to radically confront the cost structure required to achieve it. Which leads you down the only path that actually scales, without settling for easier short-term solutions. If you’re serious about putting a city on Mars, full reusability is non-negotiable. And that engineering logic turns out to be what dramatically lowers launch costs. Which unlocks Starlink at scale. And Starlink creates the revenue flywheel that funds everything else. An Arianespace executive called reusability a dream in 2013 and said it was impossible. But the dream isnt the destination. It’s the constraint that forces you down the only engineering path that actually works. And it’s why SpaceX is a trillion company today. You can write off one company as luck. You can write off two as fortunate timing. But at some point the sheer weight of success across different industries and challenges stops looking like coincidence and starts looking like a big flashing signal. When someone executes repeatedly in industries where lack of execution destroys almost everyone else, the correct analytical move is to update your model. If you can’t see that Elon is a great CEO, then you’re just revealing the limits of your own analytical process.
CommonSenseSkeptic@C_S_Skeptic

x.com/i/article/2031…

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BBC News 中文
BBC News 中文@bbcchinese·
【最新消息】伊朗官方电视台确认该国最高领袖阿亚图拉·阿里·哈梅内伊已经身亡。
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棋局
棋局@qiju2030·
王阳明的龙场悟道,其实就是教人怎么自救。 大多数人讲王阳明,总爱说他龙场悟道,好像某天夜里灵光一闪,宇宙真理“啪”地一下砸到脑门上,从此心学诞生,圣人就位。 这个说法顶多当个传奇故事听,但对理解这段经历几乎没什么帮助。你真把他当圣人看,这个故事跟你有啥关系? 可如果你把时间往前拨一点,把王阳明先从神坛上请下来,还原成一个活生生的人,这事儿就完全不一样了。 王阳明去龙场之前,是遭逢人生巨变的失败者。三十多岁,科举出身,真心信儒家那套修身齐家治国平天下。然后他在朝堂上硬刚权贵,结果被抓,下狱,廷杖。相当于清华北大毕业,刚被提升为处长,一腔理想还没施展出来,然后就被双开了。 接下来就是龙场。注意,龙场不只是偏远艰苦。在当时,那地方几乎等同于社会性死亡。瘴气、疾病、信息断绝,属于在文明世界之外。相当于今天,被发配去一个连信号都没有的地方。 去那里的官员,默认结局只有两个:病死,或者精神先垮掉。因为真正打击不在环境苦不苦,而在于原来那条人生奋斗路径失效了。 我们大多数人的痛苦,本质是还在赌一件事:再撑一下会不会有转机,再努力一点会不会被看见。可在龙场那里,几乎做什么都得不到反馈。还不是负反馈,是压根没反馈,连骂你的人都没有。 你读书给谁看,你修德谁来评判,你坚持到底是为了什么。没有观众,没有回报,没有上升通道,没人关心,这就让努力甚至是活着本身都失去了意义。 后人说龙场悟道,说得很玄,其实过程一点都不浪漫。对于王阳明来说,根本不是想通什么哲学问题,而是被逼着解决一个生存级问题:如果世界已经完全不按规则给你反馈,那你还怎么活? 王阳明给出的答案,后来被包装成一句很漂亮的话——心即理。但翻译成人话,其实很简单: 自我判断权,我不外包了。 以前他的默认模式,是外面有一套正确秩序,圣人榜样在那里,经典也在那里,我只要不断靠近,世界迟早会承认我——这是一个彻底外部判断并给出结算的系统。 可在龙场,这套系统彻底失灵。王阳明要想活下去,或者不疯掉,只能换算法。而新的算法就是: 行为本身,就是意义来源。 我这么做,不是因为将来有用,不是因为会成功,不是因为会被看见,而是因为这是我认可的。我不这样做,我精神会先死。 很多人讲知行合一,容易讲成道德要求。但如果一个人一直停在“我知道该怎么做,但我什么都改变不了”,人很快就会崩溃。 知行合一真正干的,是把评价闭环锁回自己身上: 我判断,我行动,我自己确认,不再等外部系统给反馈。 这一点非常重要。因为一旦你不再依赖外部结算,你就变得极难被摧毁。环境再烂,它最多限制你能得到什么,但无法再定义你是谁,这就是另一种意义上的“无欲则刚”。 这其实就是创伤后成长最真实的样子。不是熬过去变坚强了,而是原来的那套认知系统已经无法支撑你继续活下去,必须被迫重写一套。 等王阳明后来回到社会,他整个人已经完全不一样了。他不证明自己,不被评价牵着走,成败对他影响很小,但行动力极强。 所以龙场悟道,根本不是什么顿悟宇宙真理,而是一个人在彻底被世界抛弃之后,学会自己给行为结算意义。 这个故事放在今天更有意义。因为很多现代人的痛苦,和龙场有一个隐秘的相似点: 努力和反馈之间的关系,正在失效。 但很多人还在等一个可能永远不会再来的外部确认。 王阳明在龙场做的那件事,说到底只有一句话: 当世界不再给你正反馈和奖励时,你要学会自己给行为结算意义。 否则,你就会一直站在原地,等一个不回应你的世界,把你拖垮。
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Eric Zhao
Eric Zhao@zhaopenghui·
@tualatrix 如果宝宝闹的厉害,试试半水解或全水解的奶粉
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图拉鼎
图拉鼎@tualatrix·
有娃后才知道的事情:除了要喂奶以外,肠胀气也是家常便饭。
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Django
Django@djangoproject·
Some of the biggest companies in the world use Django, but the project's budget is comparable to a single bay-area engineer's salary. If your company uses Django, please ask them to donate! It's a great way to say thanks, and really helps keep the framework going.
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Kimi.ai
Kimi.ai@Kimi_Moonshot·
🚀 Hello, Kimi K2 Thinking! The Open-Source Thinking Agent Model is here. 🔹 SOTA on HLE (44.9%) and BrowseComp (60.2%) 🔹 Executes up to 200 – 300 sequential tool calls without human interference 🔹 Excels in reasoning, agentic search, and coding 🔹 256K context window Built as a thinking agent, K2 Thinking marks our latest efforts in test-time scaling — scaling both thinking tokens and tool-calling turns. K2 Thinking is now live on kimi.com in chat mode, with full agentic mode coming soon. It is also accessible via API. 🔌 API is live: platform.moonshot.ai 🔗 Tech blog: moonshotai.github.io/Kimi-K2/thinki… 🔗 Weights & code: huggingface.co/moonshotai
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BoraBora
BoraBora@BoraBoraBaye·
新的缅甸帮佣。新的工人姐姐是个大学生,主修历史,英文比之前的工人好太多。她说在缅甸很难找到工作。她之前在缅甸做过柜姐。来了差不多两个月,干什么都不需要太费口舌。我时常把阳台上种的花花草草剪几枝插在厨房里。不用交代,她会每天换水,还会把叶子擦得干净发亮。我付她的前6个月薪水都被中介收走作为工作介绍、机票等酬劳。这六个月总共$3000。总共。
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Eric Zhao
Eric Zhao@zhaopenghui·
@DavidHuSG1 @zzxwill 原来住低楼层会有,换到十楼以上以后就很少了,每次fogging 的时候偶尔有蚊子飞上来。
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DavidHu@SG
DavidHu@SG@DavidHuSG1·
@zzxwill 😰你住哪蚊子少啊,我下楼不浑身喷满驱蚊水根本不敢出门,甚至喷了驱蚊水一周也会被咬几次,多到炸裂好吗
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zzxwill
zzxwill@zzxwill·
我写了篇新加坡蚊子很少的文章,才发现新加坡不算国家、屁大一点、新加坡人饭都吃不饱;另外,发现我自己精神出了问题,因为不止一个人说🌚
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Dr.周
Dr.周@DrZhou_fengshui·
太用力的人生,走不远 #道德经 #随缘 #道家 #人生智慧
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@levelsio
@levelsio@levelsio·
Unfollow everyone trying to sell you their courses Follow everyone who actuallly builds stuff
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Eric Zhao
Eric Zhao@zhaopenghui·
👍
Andrej Karpathy@karpathy

New 3h31m video on YouTube: "Deep Dive into LLMs like ChatGPT" This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. It is covers the full training stack of how the models are developed, along with mental models of how to think about their "psychology", and how to get the best use them in practical applications. We cover all the major stages: 1. pretraining: data, tokenization, Transformer neural network I/O and internals, inference, GPT-2 training example, Llama 3.1 base inference examples 2. supervised finetuning: conversations data, "LLM Psychology": hallucinations, tool use, knowledge/working memory, knowledge of self, models need tokens to think, spelling, jagged intelligence 3. reinforcement learning: practice makes perfect, DeepSeek-R1, AlphaGo, RLHF. I designed this video for the "general audience" track of my videos, which I believe are accessible to most people, even without technical background. It should give you an intuitive understanding of the full training pipeline of LLMs like ChatGPT, with many examples along the way, and maybe some ways of thinking around current capabilities, where we are, and what's coming. (Also, I have one "Intro to LLMs" video already from ~year ago, but that is just a re-recording of a random talk, so I wanted to loop around and do a lot more comprehensive version of this topic. They can still be combined, as the talk goes a lot deeper into other topics, e.g. LLM OS and LLM Security) Hope it's fun & useful! youtube.com/watch?v=7xTGNN…

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财经真相
财经真相@Rumoreconomy·
造物主说,我不能一丝不挂的被一种叫人的猴子扒光
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Be Water
Be Water@Be_Waterman·
發現Claude 愈來愈好用了!
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小岛观察
小岛观察@thinkingcui·
人口问题并没有脱离2013 Population White Paper 设想的范畴,只不过出生率的问题比预想的更严重,现在看来2030年人口增长到670万人的目标一直都在坚定的执行中,考虑到有20万公民长期定居海外,生活在新加坡的人口定格在650万是个可能的KPI目标。2023年六月人口已到592万,接下来的六年里每年要引进八九万人才能完成KPI。PR的设定的人口上限是60万,公民是380万,2023年已经分别达到54万和361万,目前每年出生人口比死亡人口多一万人,留给移民的配额不足20万,接下来虽然会有更多的人口来的新加坡但是移民却更难了,之前数年每年批准55000左右的移民(3万多PR,2万新公民)的节奏可能需要缩减到每年3万出头的水平,40%的降幅,无论公民还是PR的申请接下来都会非常的卷,申请要求一定会水涨船高。
小岛观察@thinkingcui

不出所料,新加坡去年总和生育率跌破1了。

Central Region, Singapore 🇸🇬 中文
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