<\/p>\n\n\n\n
\u6211\u6700\u8fd1\u6ce8\u610f\u5230\u4e00\u4e2a\u5f88\u5c11\u88ab\u8ba4\u771f\u8ba8\u8bba\u7684\u95ee\u9898\uff0c\u5728\u4e2d\u6587\u8bed\u5883\u4e2d\uff0c\u4eba\u4eec\u8c08\u8bba\u201c\u901a\u7528\u4eba\u5de5\u667a\u80fd\u201d\u65f6\uff0c\u5f80\u5f80\u5e26\u7740\u4e00\u79cd\u7406\u6240\u5f53\u7136\u7684\u60f3\u8c61\uff0c\u597d\u50cf\u53ea\u8981\u628a\u73b0\u6709\u7684\u4eba\u5de5\u667a\u80fd\u505a\u5f97\u66f4\u5f3a\u3001\u66f4\u901a\u7528\u4e00\u4e9b\uff0c\u5b83\u81ea\u7136\u5c31\u4f1a\u6f14\u53d8\u6210\u6240\u8c13\u7684\u201c\u901a\u7528\u4eba\u5de5\u667a\u80fd\u201d\u3002\u8fd9\u79cd\u7406\u89e3\u542c\u8d77\u6765\u987a\u7406\u6210\u7ae0\uff0c\u4f46\u6211\u8d8a\u6765\u8d8a\u89c9\u5f97\uff0c\u5b83\u5728\u4e00\u5f00\u59cb\u5c31\u5df2\u7ecf\u504f\u79bb\u4e86\u95ee\u9898\u672c\u8eab\u3002<\/p>\n\n\n\n
\u95ee\u9898\u7684\u6839\u6e90\uff0c\u9996\u5148\u51fa\u73b0\u5728\u8bed\u8a00\u5c42\u9762\uff0c\u5c24\u5176\u662f\u7ffb\u8bd1\u3002\u82f1\u6587\u4e2d\u7684 Artificial General Intelligence\uff0c\u5982\u679c\u76f4\u8bd1\u6210\u4e2d\u6587\uff0c\u5176\u5b9e\u66f4\u63a5\u8fd1\u201c\u4eba\u5de5\u901a\u7528\u667a\u80fd\u201d\uff0c\u800c\u4e0d\u662f\u201c\u901a\u7528\u4eba\u5de5\u667a\u80fd\u201d\u3002\u8fd9\u4e24\u4e2a\u8868\u8ff0\u5728\u4e2d\u6587\u91cc\u770b\u4f3c\u53ea\u662f\u4e00\u70b9\u8bed\u5e8f\u5dee\u522b\uff0c\u4f46\u5f3a\u8c03\u91cd\u70b9\u5374\u5b8c\u5168\u4e0d\u540c\u3002\u4e2d\u6587\u201c\u901a\u7528\u4eba\u5de5\u667a\u80fd\u201d\u5f88\u5bb9\u6613\u8ba9\u4eba\u628a\u6ce8\u610f\u529b\u653e\u5728\u201c\u901a\u7528\u201d\u4e0a\uff0c\u4eff\u4f5b\u201c\u667a\u80fd\u201d\u672c\u8eab\u662f\u53ef\u4ee5\u88ab\u4e0d\u65ad\u6269\u5c55\u3001\u8986\u76d6\u66f4\u591a\u9886\u57df\u7684\u4e1c\u897f\uff1b\u800c\u82f1\u6587\u91cc\u7684 General Intelligence\uff0c\u5f3a\u8c03\u7684\u6070\u6070\u662f\u201c\u667a\u80fd\u7684\u7c7b\u578b\u201d\uff0c\u5b83\u4e0e Narrow Intelligence \u5e76\u5217\uff0c\u6307\u5411\u7684\u662f\u4e24\u79cd\u4e0d\u540c\u5f62\u6001\u3001\u4e0d\u540c\u5c42\u7ea7\u7684\u667a\u80fd\uff0c\u800c\u4e0d\u662f\u540c\u4e00\u79cd\u667a\u80fd\u7684\u4e0d\u540c\u4f7f\u7528\u8303\u56f4\u3002<\/p>\n\n\n\n
\u6b63\u662f\u8fd9\u79cd\u8bed\u8a00\u91cd\u5fc3\u7684\u9519\u4f4d\uff0c\u5236\u9020\u4e86\u4e00\u4e2a\u9519\u89c9\uff1a\u666e\u901a\u667a\u80fd\u53ea\u8981\u8db3\u591f\u901a\u7528\uff0c\u5c31\u80fd\u81ea\u7136\u6f14\u5316\u4e3a\u901a\u7528\u667a\u80fd\u3002\u53ef\u4e00\u65e6\u8fdb\u5165\u6280\u672f\u548c\u7406\u8bba\u5c42\u9762\uff0c\u8fd9\u79cd\u76f4\u89c9\u51e0\u4e4e\u7ad9\u4e0d\u4f4f\u811a\u3002\u6240\u8c13\u7684\u201c\u7a84\u57df\u4eba\u5de5\u667a\u80fd\u201d\uff0c\u672c\u8d28\u4e0a\u662f\u4efb\u52a1\u7ed1\u5b9a\u7684\u7cfb\u7edf\uff0c\u5b83\u4eec\u5728\u65e2\u5b9a\u76ee\u6807\u548c\u7ea6\u675f\u4e0b\u8868\u73b0\u5f97\u518d\u51fa\u8272\uff0c\u4e5f\u5e76\u4e0d\u610f\u5473\u7740\u5b83\u4eec\u5177\u5907\u7edf\u4e00\u7684\u8ba4\u77e5\u7ed3\u6784\u3001\u81ea\u6211\u7ef4\u6301\u7684\u80fd\u529b\uff0c\u6216\u8005\u5728\u964c\u751f\u60c5\u5883\u4e2d\u8fdb\u884c\u771f\u6b63\u8fc1\u79fb\u548c\u91cd\u7ec4\u7684\u80fd\u529b\u3002\u800c AGI \u5728\u539f\u59cb\u8bed\u5883\u4e2d\u6240\u6307\u5411\u7684\uff0c\u6070\u6070\u662f\u4e00\u79cd\u6574\u4f53\u6027\u7684\u3001\u4ee3\u7406\u7ea7\u522b\u7684\u667a\u80fd\u5f62\u6001\u3002\u8fd9\u4e24\u8005\u4e4b\u95f4\u7684\u5dee\u5f02\uff0c\u4e0d\u662f\u8986\u76d6\u9762\u5927\u5c0f\u7684\u95ee\u9898\uff0c\u800c\u662f\u7ed3\u6784\u548c\u5b58\u5728\u5c42\u7ea7\u7684\u4e0d\u540c\u3002<\/p>\n\n\n\n
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When \u201cAGI\u201d Gets Lost in Translation<\/p>\n\n\n\n
I\u2019ve recently noticed a fairly common phenomenon that rarely receives serious attention: in Chinese discussions, \u201cgeneral artificial intelligence\u201d is often understood as something that existing AI systems will naturally become, as long as they grow stronger, broader, and more versatile. The assumption feels intuitive, almost self-evident. Yet the more I think about it, the more convinced I am that this intuition is already misguided at the very starting point.<\/p>\n\n\n\n
The root of the problem appears first at the level of language, especially translation. Artificial General Intelligence, if rendered more literally, would be closer to \u201cartificial general intelligence\u201d rather than \u201cgeneral artificial intelligence.\u201d In Chinese, this subtle shift in word order quietly changes the center of gravity of the concept. The emphasis slides toward \u201cgenerality,\u201d making intelligence itself seem like something that can simply be expanded, generalized, and applied everywhere. In English, however, general intelligence is contrasted with narrow intelligence; it refers to a category or type of intelligence, not to the degree to which a system is broadly applicable.<\/p>\n\n\n\n
This linguistic shift gives rise to a particularly persistent misunderstanding: the idea that narrow intelligence, once made sufficiently general in its application, will eventually become general intelligence. But once we move beyond language and into technical and theoretical territory, this assumption quickly begins to unravel. Narrow AI systems are, at their core, task-bound. No matter how impressive they appear within specific domains, this does not imply that they possess a unified cognitive structure, self-sustaining agency, or the capacity to reorganize themselves meaningfully in unfamiliar situations. AGI, as originally conceived, points toward an agent-level form of intelligence\u2014a fundamentally different mode of existence, not merely a broader toolbox.<\/p>\n\n\n\n
Seen from this perspective, treating the two as points on a smooth continuum is a category mistake. The gap between them is not simply one of scale or coverage, but of structure. It resembles divergent evolutionary paths rather than incremental optimization: a cat does not become a dog by being trained more thoroughly, and each follows its own internal logic of development. Whether a future architectural breakthrough might bridge this gap is an open question, but it is clearly not something that can be reached through linear engineering alone\u2014by stacking more data, more tasks, or more computation.<\/p>\n\n\n\n
This is why I increasingly feel that many debates about AI are already skewed at the moment of translation. Language is not a neutral vessel; it actively shapes how problems are framed and what kinds of solutions seem plausible. Sensitivity to this is not pedantry but intellectual hygiene. In that sense, learning English and engaging directly with original technical and philosophical discussions is not merely a practical skill\u2014it is a way to avoid being quietly misled by second-hand concepts, and to stay closer to where the real questions actually begin.<\/p>","protected":false},"excerpt":{"rendered":"
In the realm of AI, the debate over ‘general artificial intelligence’ often overlooks a critical linguistic twist. It’s time to rethink our understanding of this transformative concept.<\/p>","protected":false},"author":17897162,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"image","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":true,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_geoff_meta_description_en":"","_geoff_meta_description_zh":"","_wpcom_ai_launchpad_first_post":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"\u4ec0\u4e48\u662f\u901a\u7528\u4eba\u5de5\u667a\u80fd\uff1fWhen \u201cAGI\u201d Gets Lost in Translation","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[784633319],"tags":[],"class_list":["post-11675","post","type-post","status-publish","format-image","hentry","category-ai-frontiers","post_format-post-format-image",""],"jetpack_publicize_connections":[],"jetpack_likes_enabled":false,"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p1ar9H-32j","jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/geoffreychen.com\/zh\/wp-json\/wp\/v2\/posts\/11675","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/geoffreychen.com\/zh\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/geoffreychen.com\/zh\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/geoffreychen.com\/zh\/wp-json\/wp\/v2\/users\/17897162"}],"replies":[{"embeddable":true,"href":"https:\/\/geoffreychen.com\/zh\/wp-json\/wp\/v2\/comments?post=11675"}],"version-history":[{"count":3,"href":"https:\/\/geoffreychen.com\/zh\/wp-json\/wp\/v2\/posts\/11675\/revisions"}],"predecessor-version":[{"id":11678,"href":"https:\/\/geoffreychen.com\/zh\/wp-json\/wp\/v2\/posts\/11675\/revisions\/11678"}],"wp:attachment":[{"href":"https:\/\/geoffreychen.com\/zh\/wp-json\/wp\/v2\/media?parent=11675"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/geoffreychen.com\/zh\/wp-json\/wp\/v2\/categories?post=11675"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/geoffreychen.com\/zh\/wp-json\/wp\/v2\/tags?post=11675"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}