Chris Wu (@amourow) header
Chris Wu (@amourow) profile picture

Taiwanese 🇹🇼 #Drupaller. OSS Contributor. Speaker @drupalcampTaipei, @coscup and @WebConfTaiwan. Love to travel around the world. (he/him/his)

Joined March 2012
Photo by Chris Wu (@amourow)Photo by Chris Wu (@amourow)Photo by Chris Wu (@amourow)Photo by Chris Wu (@amourow)Photo by Chris Wu (@amourow)Photo by Chris Wu (@amourow)Photo by Chris Wu (@amourow)Photo by Chris Wu (@amourow)Photo by Chris Wu (@amourow)Photo by Chris Wu (@amourow)
Lin Yu-Ting has won the Olympic gold medal against all odds! Her triumph in the ring is not just a testament to her unparalleled skill and dedication as a boxer, but also a powerful vindication of her character. Despite the unjust and baseless accusations questioning her gender eligibility, she has risen above the slander with grace and strength. We celebrate not just her win, but the unwavering spirit she embodies. #BoxingQueenLinYuTing
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Join @bikepackingscot @reizkulrur and endurance cyclist Jenny Graham as they traverse the picturesque @morayspeyside on the Orox. Watch the full video here: youtube.com/watch?v=xiRw6oIW…
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I think AI agentic machine translation has huge potential for improving over traditional neural machine translation, and am releasing as open-source a demonstration I'd been playing with as a fun weekend project. Using an agentic workflow, this demonstration (i) Prompts an LLM to translate from one language to another, (ii) Reflects on the translation to come up with constructive suggestions, (iii) Uses the suggestions to refine the translation. In our limited testing, this is sometimes competitive with, and sometimes worse than, leading commercial providers. But it gives a highly steerable translation system where by simply changing the prompt, you can specify the tone (formal/informal), regional variation (do you want Spanish as spoken in Spain or as spoken in Latin America?), and ensure consistent translation of terms (by providing a glossary). This is not mature software. But I hope the open-source community can make agentic translation work much better. Given how a simple reflection workflow already gives decent results, I think there's significant headroom to make agentic translation much better. Releasing an early software prototype like this is something new I decided to try to see if it is helpful to the developer community. I'd love any feedback on this. Thanks to Joaquin Dominguez, @nedteneva, @JohnSanterre for help with this. github.com/andrewyng/transla…
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Chris Wu retweeted
Here's the first release of my consistent-character model on Replicate. It uses InstantID, IPAdapter, Controlnet and FaceDetailer, with SDXL Lightning. Prompt clothes and hairstyle for best consistency It's open source but non-commercial, all links below 👇
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🎉DrupalCon Asia is back in Singapore! Join us on 9-11 December 2024 at PARKROYAL COLLECTION Marina Bay for a jam-packed event filled with keynotes, workshops and endless networking. events.drupal.org/singapore2… #DrupalAsia #Singapore #DigitalInnovation #OpenSource #DrupalCommunity
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很令人震撼的一篇關於中國女性靠假結婚去台灣從事色情業的故事。 我記得前些年看過東北下崗潮之後,為了養家,中國女性去法國,美國從事色情業的報導。 沒想到也有如此大規模的福建女性去台灣,甚至現在,去台灣從事色情業,對她們仍然如此有吸引力。 這篇文章中也能看到馬英九政府大規模放縱假結婚的情形,觸目驚心。 是在蔡英文政府時代,司法似乎才開始發揮作用。 chinadigitaltimes.net/chines…
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Chris Wu retweeted
the mission continues
We remain committed to our partnership with OpenAI and have confidence in our product roadmap, our ability to continue to innovate with everything we announced at Microsoft Ignite, and in continuing to support our customers and partners. We look forward to getting to know Emmett Shear and OAI's new leadership team and working with them. And we’re extremely excited to share the news that Sam Altman and Greg Brockman, together with colleagues, will be joining Microsoft to lead a new advanced AI research team. We look forward to moving quickly to provide them with the resources needed for their success.
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今年のDrupal Advent Calendar! @snize さん作成ありがとうございます Drupal Advent Calendar 2023 qiita.com/advent-calendar/20…
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I’ve resigned from my role leading the Audio team at Stability AI, because I don’t agree with the company’s opinion that training generative AI models on copyrighted works is ‘fair use’. First off, I want to say that there are lots of people at Stability who are deeply thoughtful about these issues. I’m proud that we were able to launch a state-of-the-art AI music generation product trained on licensed training data, sharing the revenue from the model with rights-holders. I’m grateful to my many colleagues who worked on this with me and who supported our team, and particularly to Emad for giving us the opportunity to build and ship it. I’m thankful for my time at Stability, and in many ways I think they take a more nuanced view on this topic than some of their competitors. But, despite this, I wasn’t able to change the prevailing opinion on fair use at the company. This was made clear when the US Copyright Office recently invited public comments on generative AI and copyright, and Stability was one of many AI companies to respond. Stability’s 23-page submission included this on its opening page: “We believe that Al development is an acceptable, transformative, and socially-beneficial use of existing content that is protected by fair use”. For those unfamiliar with ‘fair use’, this claims that training an AI model on copyrighted works doesn’t infringe the copyright in those works, so it can be done without permission, and without payment. This is a position that is fairly standard across many of the large generative AI companies, and other big tech companies building these models — it’s far from a view that is unique to Stability. But it’s a position I disagree with. I disagree because one of the factors affecting whether the act of copying is fair use, according to Congress, is “the effect of the use upon the potential market for or value of the copyrighted work”. Today’s generative AI models can clearly be used to create works that compete with the copyrighted works they are trained on. So I don’t see how using copyrighted works to train generative AI models of this nature can be considered fair use. But setting aside the fair use argument for a moment — since ‘fair use’ wasn’t designed with generative AI in mind — training generative AI models in this way is, to me, wrong. Companies worth billions of dollars are, without permission, training generative AI models on creators’ works, which are then being used to create new content that in many cases can compete with the original works. I don’t see how this can be acceptable in a society that has set up the economics of the creative arts such that creators rely on copyright. To be clear, I’m a supporter of generative AI. It will have many benefits — that’s why I’ve worked on it for 13 years. But I can only support generative AI that doesn’t exploit creators by training models — which may replace them — on their work without permission. I’m sure I’m not the only person inside these generative AI companies who doesn’t think the claim of ‘fair use’ is fair to creators. I hope others will speak up, either internally or in public, so that companies realise that exploiting creators can’t be the long-term solution in generative AI.
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🦜🤖OpenGPTs OpenAI just announced "GPTs" - chatbots augmented with custom tools and custom instructions that anyone can create We're excited to announce OpenGPTs - a open source GitHub repo enabling similar functionality. This will allow: 🛠️Easier tool definition 🧠Usage of other LLMs like Anthropic, Azure, and OSS models (of course, compatibility with OpenAI models as well) 💻Full control of the platform (deploy wherever, use APIs however) GitHub repo: github.com/langchain-ai/open… Check out an example of a hosted version here: opengpts-example-vz4y4ooboq-… Fork it, clone it, add your custom tools! We're working on a hosted version
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Announcing Grok! Grok is an AI modeled after the Hitchhiker’s Guide to the Galaxy, so intended to answer almost anything and, far harder, even suggest what questions to ask! Grok is designed to answer questions with a bit of wit and has a rebellious streak, so please don’t use it if you hate humor! A unique and fundamental advantage of Grok is that it has real-time knowledge of the world via the 𝕏 platform. It will also answer spicy questions that are rejected by most other AI systems. Grok is still a very early beta product – the best we could do with 2 months of training – so expect it to improve rapidly with each passing week with your help. Thank you, the xAI Team x.ai
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Preview of the New ChatGPT Prototype - Gizmo V8 Featuring "Magic Maker" (GPT-4 Magic Create?) and Customizable "GPTs" The new ChatGPT prototype looks like the ChatGPT iOS App, but introduces a new model selector, customizable GPTs, and "Magic Maker" (presumably utilizing GPT-4 Magic Create) alongside an "Advanced" mode for creating your own GPTs. The "My GPTs" dashboard displays all your GPTs and provides the option to "Create a GPT - Customize and share a powerful AI assistant". Find all the details and screenshots in the thread below 👇
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🌟 It's time to kick off #DrupalConLille! ✨ Join us, including the Organizing Secretariat, Advisory Board members, and Drupal Association staff, for the Opening Ceremony today at 12:00 CEST in the Auditorium. The Women in Drupal Award ceremony is up next at 12:45 CEST.
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Chris Wu retweeted
《一个简单的Prompt大幅提升ChatGPT翻译质量,告别“机翻感”》 无论是Google翻译、DeepL翻译还是ChatGPT,翻译大段英文的时候,“机翻感”(机器翻译的感觉)都很强,一看就是机器翻译的,很生硬,但是自己手动润色又太费时间。 我以前花了很多努力让ChatGPT去“意译”而不是“直译”,让它模仿特定写作风格,效果能做到比谷歌翻译和DeepL强,但还是能感觉有“机翻”痕迹。 基于我前面的研究成果,我发现对于普通的翻译,如果让ChatGPT翻译两次,先直译一次,然后再基于第一次结果意译,整体翻译质量会上一个大台阶,而且经过第二次翻译后,“机翻”的痕迹已经不明显了,很难看出来这是机器翻译的结果。 当然你还可以让ChatGPT继续重写润色,但经过我的实验,对于 GPT-4 来说两次翻译已经是性价比很好的方式,既不用增加很多Token和时间成本,同时得到没有什么“机翻”痕迹的结果。 可以对比看翻译的效果。 图一是只翻译一次的效果 完整会话历史:chat.openai.com/share/de0483… 摘取最后一句话:“就像扎克伯格一样,盖茨曾从哈佛退学,以建立一个历史性的科技公司。就像扎克伯格一样,他是他领域的神童型人物。就像扎克伯格一样,他在一路奋进的过程中,创造了粉丝,树敌,也引发了反垄断的担忧。” 图二是让它翻译两次的效果,第一次翻译的结果差不多,但是第二次翻译的结果明显有很大改善。 完整会话历史:chat.openai.com/share/22a908… 同样摘录最后一句话:“与扎克伯格相似,盖茨也曾离开哈佛,去创建一家有着重要历史意义的科技公司;他们都曾是各自领域的奇迹之子;而且他们都在强势冲刺的过程中,赢得了粉丝,也树立了敌人,并产生了反垄断的担忧。” 虽然图一翻译的也不错,但是图二第二次翻译的效果明显要更好一些。 建议你也可以试试。
之前我分享过,每次翻译字幕时,在精翻阶段,通常我会让ChatGPT给我提供3-5个不同风格的翻译选项,然后我从中挑选好的,大部分时候都不需要修改,只要逐句选择最好的翻译就好了。 虽然已经简单很多了,但是还是有点筛选工作,于是我想,是不是可以优化一下这个过程? 但怎么能让AI帮我挑选最好的呢?并且是真的符合我的标准的好的结果。 我联想到CoT(Chain of Thought),通过分步可以让LLM得到更好的结果。 联想到没有ChatGPT的时候我翻译的步骤:先用Google翻译,得到一个差不多的粗糙结果,然后一个个去校对,最后忘记英文,只用中文润色。 也许我们可以借助CoT来一步步优化翻译结果。 于是我先将翻译拆成两步,打印每一步的结果: 第一步:就是直译,就像我们用Google翻译那样,好处是可以忠于原意 第二步:基于第一步直译的结果,结合上下文,重新意译 我发现这样调整后,第一步的翻译结果和以前差不多,但是第二步的结果明显好于以前直接让 ChatGPT 意译的效果,说明 CoT 是有效果的。 然后我再将它扩展成四步: 第三步:基于第一步和第二步,提供一种创意翻译结果(这一步其实可以根据自己需要调整),主要是作为第二步意译的一个补充,为第四步提供足够的素材 第四步:现在已经有了三步的迭代,我们已经有了三个不错的翻译版本,这时候可以让ChatGPT不需要看英文了,当做一个中文老师,擅长修改,有三个学生的提供了中文句子,基于他们的句子做出批改,最终形成一个最好的中文版本。 实际效果来看挺不错的,大多数时候我只要选择第四步的结果,偶尔需要参照第二步和第三步的结果,几乎不需要第一步的结果。 不知道是不是可以水一篇论文:《如何借助CoT得到高质量的翻译结果》👨‍🎓🤪 Prompt参考:chat.openai.com/share/1feb6e…
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🚲 #TernHSD 📍 #Tokaido, #Japan 📸 @YokohamaRides (Twitter) 🎨 Unkown Artist Oh hey, it's #MuralMonday! We love seeing where your Tern takes you to explore your city and the art you find along the way. Tag us in photos of your Tern in front of a local mural!!
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I’ve been investing for 19 years. Here are the 9 best FREE investing resources I’ve ever found:
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Chris Wu retweeted
BREAKING: Google opens its Generative AI Platform to all. Imagine unlocking the power of machine learning for everyone Businesses can now integrate Google's Vertex AI into their applications. Here's what you need to know:
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生成AI画像は類似性が認められれば「著作権侵害」。文化庁 pc.watch.impress.co.jp/docs/…
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Chris Wu retweeted
AI is how we describe software that we don’t quite know how to build yet, particularly software we are either very excited about or very nervous about
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