本文摘选自刘嘉教授新书《通用人工智能》 大模型的成功并非偶然——从早期符号主义AI的失败，到深度学习的崛起，再到Transformer的成功，每 一次进化都是从无数被淘汰的算法、模型中艰难诞生。在这艰难曲折的探索中，人类智慧的金块无疑是 AI头上的一盏明灯。反过来，大模型的进化经验，能否成为我们人类认知进化的营养？由此，我们破茧 成蝶，与AI时代同频共振，开启认知与智慧的跃迁。 为人生定义目标函数 所有的机器学习，在开始训练前，都必须明确一个目标函数 （又 称损失函数或 成本函数） 。这个函数定 义了模型希望达到的理想状态，而训练的全部意义就在于不断优化参数，让模型越来越接近这个目标。 正所谓学习未动，目标先行。 作为机器学习的一个分支，人工神经网络从一开始就是另类，因为它的目标函数太宏大、太有野心，以 至于当辛顿请求其所在的多伦多大学校长再招收一名人工神经网络的研究者时，该校长是如此回答 的："一个疯子就足够了。"的确，人工神经网络的开创者都有一个在外人眼里近似疯狂的目标函数： 1943年麦卡洛克和皮茨提出的"简陋"神经元是要模拟"神经活动内在观念的逻辑演算"，1958年罗森布拉 刘嘉 清华大学基础科学讲席 ...

Core Insights - The article discusses the concept of "path dependence" and how reliance on past experiences can hinder innovation and adaptation in business environments [1][3][5] - It highlights the dangers of "success dependence," where companies fail to evolve due to over-reliance on previous successful strategies [3][11] - The need for entrepreneurs to break free from these mental constraints to unlock new growth opportunities is emphasized [11][12] Group 1: Path Dependence - Path dependence can lead to a rigid adherence to familiar strategies, which may become a liability in changing environments [2][5] - Examples of companies like Nokia and Kodak illustrate how over-reliance on past successes can result in missed opportunities and decline [3][10] - The concept of "local optimum" is introduced, where businesses may settle for satisfactory solutions without exploring potentially better alternatives [7][8] Group 2: Cognitive Biases - Cognitive biases, such as the tendency to stick with familiar methods, can limit the ability to adapt to new challenges [6][9] - The article explains how the brain's predictive coding can reinforce existing beliefs and hinder the acceptance of new information [6][9] - Entrepreneurs often attribute success to specific methods without recognizing the importance of context and adaptability [6][9] Group 3: Overfitting in Business - The analogy of "overfitting" from machine learning is used to describe how businesses can become too specialized in their past methods, failing to generalize to new situations [4][11] - This overfitting can lead to a lack of responsiveness when faced with new data or market changes [4][11] Group 4: Strategies for Overcoming Constraints - To break free from path dependence, companies should actively seek new experiences and challenges [12][14] - Developing transferable skills is crucial for adapting to changing environments and avoiding the pitfalls of being locked into a single path [14][15] - Regularly reassessing goals and strategies can help identify when a company is stuck in a local optimum and needs to pivot [13][15]

Core Viewpoint - The article discusses the dangers of "path dependence" and "success dependence" in entrepreneurship, emphasizing that reliance on past experiences can hinder innovation and adaptation to new market conditions [4][6][15]. Group 1: Path Dependence - Path dependence can lead to a reliance on outdated strategies, making it difficult for companies to adapt to new technologies and market demands [4][6]. - Examples include Nokia and Kodak, which failed to transition to smartphones and digital photography due to their reliance on past successes [4][6]. - The concept of path dependence is rooted in increasing returns and transfer costs, which discourage companies from changing established practices [6][7]. Group 2: Success Dependence - Success dependence refers to the tendency to attribute past successes solely to specific methods, ignoring the context that made those methods effective [7][8]. - This cognitive bias can lead to a failure to question the relevance of established practices when market conditions change [7][8]. Group 3: Local Optima - The article highlights the issue of "local optima," where individuals or companies settle for satisfactory solutions without exploring potentially better options [10][11]. - This phenomenon can hinder personal growth and innovation, as sticking to familiar paths may prevent the discovery of superior alternatives [11][12]. Group 4: Breaking Free from Constraints - To overcome these limitations, companies should actively seek new experiences and challenge existing habits [16][18]. - Developing transferable skills can help entrepreneurs adapt to changing environments and avoid being trapped by outdated practices [18][19]. - The article advocates for a mindset shift from relying on past experiences to actively shaping future paths through continuous learning and adaptation [19].