从混沌到决定论 – 转变叙事空间

2作者: pyeri大约 1 个月前原帖
今天早上我喝着茶时意识到,目前AI热潮的很大一部分其实只是关于“人工智能叙事”的炒作。大型语言模型(LLM)技术本身只是一种数字工具,和之前出现的许多工具一样,但关于“人工智能是未来”、“学习它否则就会被淘汰”、“机器很快会取代人类”等等的讨论,使得这一话题频频出现在新闻中,实际上是在无中生有。然而,人们却因此失去了精力和睡眠,这就成了一个问题。许多本无恶意的企业也被误导,认为这项技术能创造奇迹,这对那些推销这些“桥梁”的人来说是一种极大的失职。 对于我们这些厌倦这种无聊叙事的人来说,与其与之抗争,不如尝试将叙事转向决定论。几个世纪以来,我们被训练去避免甚至恐惧宿命论(决定论的一个负面方面),并希望未来能够更好、更繁荣。怀有希望并没有错,但在已知历史上第一次,“未来将会辉煌”的主题似乎并不那么光明,至少对于许多与基层紧密相连的人来说是如此。 为了反击这种叙事,我们需要将决定论转变为一种积极的力量,或者至少是一种比其他选择更可取的力量。即使在大型语言模型领域,大多数实用的事情发生在低端、开源和本地的LLM领域,这些领域在方法上更具决定性。我们能做些什么来重新唤起人们对常规决定性编程(如C、Java和Python)的兴趣呢?
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What I realized today while sipping my morning cup of chai is that a large part of the present AI hype cycle is just about the &#x27;narrative of AI&#x27;. The LLM technology itself is just a digital tool like many others that came before it but all this chatter about &#x27;AI is the future&#x27;, &#x27;learn it or perish&#x27;, &#x27;machines will replace humans soon&#x27;, etc. keeps it in the news and creates a burger out of nothing. But folks lose their energy and sleep over this which becomes a problem. And many a benign enterprises are falsely led to believe that this technology can do wonders, it&#x27;s a great disservice being done by those selling these bridges.<p>For folks like us who are fed up of this slop narrative - instead of fighting it, it&#x27;s better to try and shift the narrative towards determinism. For centuries and millennia, we have been trained to avoid and even fear fatalism (a negative aspect of determinism), and look towards future with hopes for betterment and prosperity. There is nothing wrong with having hope but for the first time in known history, the &#x27;future will be glorious&#x27; theme isn&#x27;t looking so bright, at least to a large number of folks connected to grassroots.<p>In order to push back against this narrative, we need to turn determinism into a force of good, or at least a force preferable to the alternative. Even in the LLM space, most of the utilitarian things are happening in the low-end, open source and local LLMs niches which are more deterministic in approach. What can we do to bring back people&#x27;s interest in regular deterministic programming with C, Java and Python?