I’m learning game development.
One day, I’ll create a giant robot.
AI software dev | GenAI | GPU |
OpenClaw skills research
Data Viz | Game Dev | AI SaaS
Building apps has never been easier.
With Sites, Codex can turn your work, ideas, and plans into an interactive website or app your team can explore, use, and share with a URL.
Rolling out to Business and Enterprise plans, before expanding more broadly.
AI video editors can't edit what isn't indexed. Learn how a developer used Gemma 4 31B locally on a 5-year-old laptop to process and index a year of raw, unlabeled video, making it fully searchable. A great look at building local-first tools.
You can now train 120B+ parameter models locally on a laptop! 🔥
We collabed with NVIDIA and Microsoft to bring LLM training on the 128GB unified memory RTX Spark laptop!
Y Combinator 執行長 Garry Tan 公開指出:現在的模型已經夠聰明了,真正的瓶頸是「公司專屬知識」——那些鎖在資深員工腦袋裡的經驗、判斷與脈絡。
他認為,誰能把這些隱性知識有效提取並結構化,讓 AI Agent 能即時取用,誰就掌握了下一階段的關鍵優勢。
這代表 AI 競爭已從「模型智力」轉向「組織記憶力」。未來贏家不會只是有最好模型的公司,而是那些能把「我們公司到底怎麼做事的」這件事,成功轉化成 Agent 可以穩定呼叫的知識層。
AI連人脈經驗跟裸照都要整碗拿走嗎
This is the actual bottleneck. The models are smart enough already. What is missing is the company-specific context locked in senior people heads. Whoever cracks knowledge extraction at the company level unlocks the rest.
As you work on this, please consider using GBrain as your OSS retrieval layer
https://t.co/0F5uDQzPHu
當一位工程師搭配 AI 能創造出 9 兆美元 的生產力時,公司為什麼要少聘人?反而會因為產出太驚人而想聘更多人。
這正是「Jevons Paradox」(傑文斯悖論)在 AI 時代的體現——當「寫程式」的成本大幅下降時,公司不會減少需求,而是會去做更多原本做不起來的專案。
真正被取代的不是工程師,而是「只會寫 boilerplate、無法駕馭 AI」的工程師。未來贏家,是那些把 AI 當超能力使用的工程師🚀
Nvidia CEO Jensen Huang just called the idea of AI replacing software engineers "complete nonsense"
"The number of software engineers is actually increasing... if you can hire a software engineer and generate $9 trillion worth of productive work, why wouldn't you want to hire more?
If that line were flat, then obviously people would hire fewer software engineers. But because the output is so incredible, people want to hire more
This is going to show up in our economy somehow, soon. Useful AI has arrived"
.@Adobe Photoshop and Premiere — rebuilt from the ground up for NVIDIA RTX Spark.
Up to 2x faster across AI, editing, coloring and effects. Full GPU acceleration. AI-native pipeline.
Coming soon.
.@Adobe Photoshop and Premiere — rebuilt from the ground up for NVIDIA RTX Spark.
Up to 2x faster across AI, editing, coloring and effects. Full GPU acceleration. AI-native pipeline.
Coming soon.
NVIDIA 執行長 Jensen Huang 公開表示,AI PC 的變革規模將媲美智慧型手機革命**!
他指出,過去三年 NVIDIA 與 Microsoft 共同重新定義 PC,讓 AI 模型可以直接在裝置上本地運行,而非完全依賴雲端。下一代 PC 將內建能與使用者並肩工作的 AI Agent。
核心硬體就是剛發表的 RTX Spark,被稱為「全球最強桌上型 AI 超級電腦」,專為下一代本地 AI Agent 工作負載設計。
這代表運算架構從「雲端集中式」走向「邊緣分散式」,未來 Agent 不只聊天,還能即時在你本機執行複雜任務、處理隱私敏感資料。這波「Agentic AI PC」浪潮,才剛剛開始🚀
Jensen Huang says the AI PC reinvention is as big as the smartphone shift by calling it “a new line” and “a new beginning.”
$NVDA and $MSFT unveiled RTX Spark which will be the world’s most powerful deskside AI supercomputer built to run next-gen AI agent workloads locally.
雖然 Apple M 系列從 2020 年就用統一記憶體 + 高效能做到類似的事,但 NVIDIA 把 CUDA 生態帶進 Windows 輕薄筆電,代表「AI Agent 24 小時常駐本機、不依賴雲端」這件事,終於要從概念走向主流。
接下來 AMD、Intel 很可能跟進,這波「Agentic AI PC」戰爭才剛開始🚀
The laptop hasn't changed in 30 years. NVIDIA just changed it
RTX Spark is their first PC chip ever.
- RTX 5070 level GPU
- 128GB unified memory
- 1 petaflop of local AI
- thin, light, barely throttles unplugged
Your AI agent lives on the machine. 24/7. No cloud.
This is step one of the agentic AI PC, and everyone else is about to copy it.