FPGA固件有助于统一BDA的监督和非监督深度学习

MOJ Applied Bionics and Biomechanics Pub Date : 1900-01-01 DOI:10.15406/mojabb.2019.03.00108

H. Szu

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引用次数: 0

摘要

麻省理工学院教授Lex Friedman和斯坦福大学CS教授Andrew Ng都提倡人工通用智能(AGI)。深度学习是一种模拟人类视觉系统(V1-V4)的递归多层学习，由Geoffrey Hinton教授(现就职于Google)和他的同事Yann Le Cun教授(现就职于纽约大学Facebook)、Yoshua Bengio教授(现就职于多伦多大学)发起它们一起在2015年左右的《自然》杂志最近发表的《(监督)深度学习》中得到了展示。

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FPGA firmware helps unify the supervised and un-supervised deep learning for BDA

Artificial general intelligence (AGI) has been advocated by both MIT Prof. Lex Friedman, and Stanford CS Prof. Andrew Ng. The deep learning is a recursive multi-layers learning emulating human visual system (V1-V4) which have been campaigned by Prof. Geoffrey Hinton (now at Google) and his protégée Prof. Yann Le Cun (no at NYU Facebook), Prof. Yoshua Bengio (remains at Univ. Toronto)).1 Together they have been demonstrated in recent Nature publication “(Supervised) Deep Learning” circa 2015.

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MOJ Applied Bionics and Biomechanics

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