AI or Die | RKG
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Such signs should be alarming to the autonomous-driving industry, which has largely banked on scaling, rather than on developing more sophisticated reasoning. If scaling doesn’t get us to safe autonomous driving, tens of billions of dollars of investment in scaling could turn out to be for naught.
Gary Marcus • Deep Learning Is Hitting a Wall
赛道特点?
1)劳动力替代/补强需求下的大市场(TAM),远期2C场景是万亿规模产业链;2)人工智能技术驱动下高进入壁垒(特别是偏具身模型的算法公司);3)存在规模效应带来头部集中(类比新能源车竞争格局);4)目前智能发展阶段仍然较早
1)劳动力替代/补强需求下的大市场(TAM),远期2C场景是万亿规模产业链;2)人工智能技术驱动下高进入壁垒(特别是偏具身模型的算法公司);3)存在规模效应带来头部集中(类比新能源车竞争格局);4)目前智能发展阶段仍然较早
可风Jason • 陆奇最新演讲实录：我的大模型世界观
The two approaches are powered by the same thing that powers AI: data. Self-driving cars must be trained on millions, maybe billions, of miles of driving data so they can learn to identify objects and predict the movements of cars and pedestrians.