{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"a2eab101-adfc-4a0d-8142-63a4d11cee02","title":"人工智能和资本主义的未来","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9780745338613","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"a2eab101-adfc-4a0d-8142-63a4d11cee02","id":"a2eab101-adfc-4a0d-8142-63a4d11cee02","uuid":"a2eab101-adfc-4a0d-8142-63a4d11cee02","title":"人工智能和资本主义的未来","normalized_title":"人工智能和资本主义的未来","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9780745338613","isbns":["9780745338613","9780745338606","9781786803955","9781786803979","9781786803962"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":225,"navigation_url":"https://workshop.closeclaw.top/ai/book/a2eab101-adfc-4a0d-8142-63a4d11cee02","title_url":"https://workshop.closeclaw.top/ai/title/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%E5%92%8C%E8%B5%84%E6%9C%AC%E4%B8%BB%E4%B9%89%E7%9A%84%E6%9C%AA%E6%9D%A5","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/a2eab101-adfc-4a0d-8142-63a4d11cee02/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/a2eab101-adfc-4a0d-8142-63a4d11cee02/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/a2eab101-adfc-4a0d-8142-63a4d11cee02","page_url":"https://workshop.closeclaw.top/api/ai/books/a2eab101-adfc-4a0d-8142-63a4d11cee02/page","search_url":"https://workshop.closeclaw.top/api/ai/books/a2eab101-adfc-4a0d-8142-63a4d11cee02/search"},"page":{"printed_page":128,"pdf_page":136,"physical_index":136,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"865a3f89a8e609b316c76ae4c3141f50538ba1217a4cd0d7c6d39026d52723b2"},"chapter":"Digital Barricades: Interventions in Digital Culture and Politics","content":"most of the existing ‘machine learning’ works do not belong to AGI … because they define the learning problem in isolation, without treating it as part of a larger picture. They are not concerned with creating a system possessing broad-scope intelligence with generality at least roughly equal to that of the human mind/brain; they are concerned with learning in much narrower contexts. (Wang and Goertzel 2007: 2)\n\nSimilarly, Nils J. Nilsson argues that reaching the goal of HLAI through ‘building special-purpose systems’ may be misplaced and instead advocates a ‘general-purpose educable system that can learn and be taught’ and that has ‘minimal, although extensive, built-in capabilities’ (2005: 68). These capabilities include a sensory-motor system, predicting and planning, learning, and reasoning and representation. In effect, Nilsson argues for a ‘child machine’ that learns and develops in a similar fashion to humans.\n\nNevertheless, while the pursuit of AGI is different from narrow AI, it is not fundamentally so. An AGI researcher may make use of methods from machine learning that concern generalization (e.g. transfer learning and inductive biases) and thus overlap with the goal of creating a general intelligence, but ‘additional architectural and dynamical principles would be required, beyond those needed to aid in the human-mediated, machine learning aided creation of a variety of narrowly specialized AI … systems’ (Goertzel 2014: 4). At the same time, however, a ‘general purpose’ computer system does not necessarily require a ‘single factor … to be responsible for all its cross-domain intelligence. It is possible for the system to be an integration of several techniques’ (Wang and Goertzel 2007: 5). That is, although Wang and Goertzel reject the possibility of aggregating various narrow AIs into an AGI – which would be the equivalent of joining many different automated concrete labours into labour-power – they appear to be open to the possibility that, as long as the general nature of the system is kept in mind while solving narrower problems, they could then be integrated into a general intelligence. Whether a machine with general intelligence can emerge from the current and future refinement of the deep learning approach, or whether the system must be built for a general purpose from the get go, is an ongoing debate in the AI community. It is far beyond our expertise to judge one as more probable or promising than the other.\n\n128\n\ninhuman power","previous_page":127,"next_page":129}