@leslieloser_: Had the privilege of meeting @Zhm20220917, the best at AI transformation in Jiangsu, Zhejiang, and Shanghai, for a few hours. Became even more certain about the following --In the AI era, those closer to production who understand the industry will reap huge startup dividends; understanding AI and boundaries is 20%, understanding production and industry is 80% --Small teams refuse inno…
Summary
The article shares insights on entrepreneurial dividends in the AI era, emphasizing that understanding industry and production is more critical than mastering AI technology. Companies prioritize actual problem-solving capabilities over the models themselves.
Similar Articles
@LuoSays: Actually, this argument works the other way too: right now is exactly the best entrepreneurial opportunity for ordinary people. Here's why: 1. AI has completely demolished the technical barriers of any product. If you want to make something, you can do it with AI. You can easily clone any product you want, something that was very difficult in the past. 2. With the rise of v…
The author believes that AI has broken down technical barriers and lowered the entrepreneurial threshold, making now the best entrepreneurial opportunity for ordinary people. They can quickly realize product ideas and occupy niche markets through AI.
@dongxi_nlp: A very valuable article, the last 6 takeaways are worth pondering. Among them, the last two: 5. The data industry is far from developed. Anthropic and OpenAI spend over $10 million on a single environment, while Chinese AI labs have a 'build rather than buy' mentality. 6. Countless...
The article summarizes the current state of the AI data industry, pointing out that the data industry is not yet mature. Anthropic and OpenAI spend over $10 million on a single environment, while Chinese AI labs tend to build rather than buy. In addition, many labs have access to Huawei chips but still crave more Nvidia chips.
@interjc: Can you actually get rich doing AI in Shenzhen?
A brief social-media question asking whether building AI in Shenzhen can really make you rich.
The smartest way to learn AI: grab coffee with Gen-Z founders like @beefnoode—suddenly it clicks. They’re masters of East-West arbitrage: turn China’s agent-based software into an “AI-OS” and sell it to high-paying, low-tech European firms. Started as a relay service, still printing money, successfully exporting domestic tokens.
A tweet highlights how Gen-Z entrepreneurs profit by repackaging Chinese AI-agent systems for high-paying, low-tech European clients.
@hongming731: Alibaba's article on organizational R&D in the AI Native era is well worth reading. It addresses a critical foundational issue: for the past two millennia, organizational structures have been built around human limitations. Humans forget, get tired, misunderstand, and have emotions. The number of people one can stably collaborate with and manage is limited, and information inevitably degrades as it passes between hierarchies...
Alibaba released insights on organizational R&D in the AI Native era, pointing out that traditional organizational structures need to shift from accommodating human limitations to adapting to the efficient execution of AI Agents. The article emphasizes that the core bottleneck of AI transformation lies in outdated information formats; implicit experience must be transformed into AI-understandable infrastructure, while preserving the human role in innovation and cultural building.