LEADERS: LEARN FROM AI TO OVERCOME YOUR LOCAL MAXIMUM

Leader to Leader Pub Date : 2025-02-16 DOI:10.1002/ltl.20875
Judah Taub
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Abstract

The author is founder and managing partner of Hetz Ventures, one of Israel’s leading early-stage venture capital firms; and has previously served in elite commando and intelligence military units. He discusses the concept of a “local maximum,” which he describes as “a point on a field that is not the highest or the best, but it is a point from which we can only go down in order to continue further.” He outlines “three techniques and approaches used by AI – and which can be used by all of us to overcome local maximums.” Within point one, “agility can be both a function of an organization’s mindset and DNA, and the hard quantifiable metrics such as the level of CapEx (capital expenditures) versus OpEx (operating expenses).” Within point two, “we will always be limited by time. However, learning to utilize time as a variable, trading it sometimes as a buyer and sometimes as a seller, increases our potential outcome to reach a higher maximum.” And he concludes that, “as artificial intelligence continues to improve, we may find that the lessons it teaches us are more impactful than the tasks it performs.”

领导者:向人工智能学习,克服你的局部最大值
本文作者是以色列领先的早期风险投资公司Hetz Ventures的创始人和管理合伙人;他之前曾在精锐突击队和情报部队服役。他讨论了“局部最大值”的概念,他将其描述为“领域中的一个点,它不是最高或最好的,但为了继续前进,我们只能从这个点开始下降。”他概述了“人工智能使用的三种技术和方法——我们所有人都可以使用它们来克服局部最大值。”在第一点中,“敏捷性既可以是组织思维模式和DNA的功能,也可以是硬性量化指标,例如CapEx(资本支出)与OpEx(运营支出)的水平。”在第二点中,“我们总是受到时间的限制。然而,学会利用时间作为一个变量,有时作为买方,有时作为卖方进行交易,可以增加我们的潜在结果,达到更高的最大值。”他的结论是,“随着人工智能的不断进步,我们可能会发现,它教给我们的教训比它执行的任务更有影响力。”
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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