The Brain vs. Deep Learning Part I: Computational Complexity
The article explores the comparison between the brain's information processing and deep learning architectures. It discusses predictions regarding technological singularity and the computational power of the brain versus artificial intelligence. The author argues that current estimates for achieving brain-like computational power may be outdated, suggesting that a technological singularity is unlikely in this century.
- ▪The article compares the brain's information processing to deep learning architectures.
- ▪Ray Kurzweil's predictions about strong AI and technological singularity are examined.
- ▪The author argues that current estimates for brain-like computational power may not be accurate.
Opening excerpt (first ~120 words) tap to expand
The Brain vs Deep Learning Part I: Computational Complexity — Or Why the Singularity Is Nowhere Near2015-07-27 by Tim Dettmers 183 CommentsIn this blog post I will delve into the brain and explain its basic information processing machinery and compare it to deep learning. I do this by moving step-by-step along with the brains electrochemical and biological information processing pipeline and relating it directly to the architecture of convolutional nets. Thereby we will see that a neuron and a convolutional net are very similar information processing machines. While performing this comparison, I will also discuss the computational complexity of these processes and thus derive an estimate for the brains overall computational power.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Tim Dettmers.
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