{"id":210475,"date":"2025-04-03T14:09:32","date_gmt":"2025-04-03T19:09:32","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2025\/04\/when-ai-builds-ai-the-next-great-inventors-might-not-be-human"},"modified":"2025-04-03T14:09:32","modified_gmt":"2025-04-03T19:09:32","slug":"when-ai-builds-ai-the-next-great-inventors-might-not-be-human","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2025\/04\/when-ai-builds-ai-the-next-great-inventors-might-not-be-human","title":{"rendered":"When AI builds AI: The next great inventors might not be human"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/when-ai-builds-ai-the-next-great-inventors-might-not-be-human2.jpg\"><\/a><\/p>\n<p>In the paper accompanying the launch of R1, DeepSeek explained how it took advantage of techniques such as synthetic data generation, distillation, and machine-driven reinforcement learning to produce a model that exceeded the current state-of-the-art. Each of these approaches can be explained another way as harnessing the capabilities of an existing AI model to assist in the training of a more advanced version.<\/p>\n<p>DeepSeek is far from alone in using these AI techniques to advance AI. Mark Zuckerberg predicts that the mid-level engineers at <a href=\"https:\/\/fortune.com\/company\/facebook\/\" target=\"_blank\" aria-label=\"Go to <a href=\"https:\/\/fortune.com\/company\/facebook\/\"\">https:\/\/fortune.com\/company\/facebook\/\u201d<\/a> class=\u201d\u201d&gt;Meta<\/a> may soon be replaced by AI counterparts, and that Llama 3 (his company\u2019s LLM) \u201chelps us experiment and iterate faster, building capabilities we want to refine and expand in Llama 4.\u201d <a href=\"https:\/\/fortune.com\/company\/nvidia\/\" target=\"_blank\" aria-label=\"Go to <a href=\"https:\/\/fortune.com\/company\/nvidia\/\"\">https:\/\/fortune.com\/company\/nvidia\/\u201d<\/a> class=\u201d\u201d&gt;Nvidia<\/a> CEO Jensen Huang has spoken at length about creating virtual environments in which AI systems supervise the training of robotic systems: \u201cWe can create multiple different multiverses, allowing robots to learn in parallel, possibly learning in 100,000 different ways at the same time.\u201d<\/p>\n<p>This isn\u2019t quite yet the singularity, when intelligent machines autonomously self-replicate, but it is something new and potentially profound. Even amidst such dizzying progress in AI models, though, it\u2019s not uncommon to hear some observers talk about the potential slowing of what\u2019s called the \u201cscaling laws\u201d\u2014the observed principles that AI models increase in performance in direct relationship to the quantity of data, power, and compute applied to them. The release from DeepSeek, and several subsequent announcements from other companies, suggests that arguments of the scaling laws\u2019 demise may be greatly exaggerated. In fact, innovations in AI development are leading to entirely new vectors for scaling\u2014all enabled by AI itself. Progress isn\u2019t slowing down, it\u2019s speeding up\u2014thanks to AI.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In the paper accompanying the launch of R1, DeepSeek explained how it took advantage of techniques such as synthetic data generation, distillation, and machine-driven reinforcement learning to produce a model that exceeded the current state-of-the-art. Each of these approaches can be explained another way as harnessing the capabilities of an existing AI model to assist [\u2026]<\/p>\n","protected":false},"author":396,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[33,6,64,1879],"tags":[],"class_list":["post-210475","post","type-post","status-publish","format-standard","hentry","category-cosmology","category-robotics-ai","category-singularity","category-virtual-reality"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/210475","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/396"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=210475"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/210475\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=210475"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=210475"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=210475"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}