[英]Artificial Intelligence & Von Neumann Model
As we advance further in building AI models it seems that the Von Neuman architecture has some certain limitations.随着我们在构建 AI 模型方面的进一步推进,冯诺依曼架构似乎有一些限制。 In a real-life scenario, neurons work in bulk and information is stored in networks.在现实生活中,神经元大量工作,信息存储在网络中。 Neurons have thousands of input and output connections with other neurons with some of them being weak while others are strong.神经元有数千个输入和 output 与其他神经元的连接,其中一些神经元较弱,而另一些则较强。 When they fire together, a signal based on the weights of the connection path is created and that causes a pattern of other neurons firing back in response.当它们一起发射时,会创建一个基于连接路径权重的信号,并导致其他神经元的模式作为响应而发射回来。 There are no single units that store information.没有存储信息的单个单元。
The major distinction is that there is not discrepancy between storing/retrieving information and computation as in Von Neuman model.主要区别在于存储/检索信息和计算之间没有像冯诺依曼 model 中的差异。
As a starter, I would recommend a very interesting article that talks about this in a broad view: https://medium.com/swlh/the-explosion-of-new-architectures-is-fundamentally-changing-computing-f69b7faae89d作为初学者,我会推荐一篇非常有趣的文章,从广义上讨论这个问题: https://medium.com/swlh/the-explosion-of-new-architectures-is-fundamentally-sharing-computing-f69b7faae89d
On a more technical level, I can recommend the work of Ganguly et al.在技术层面上,我可以推荐 Ganguly 等人的工作。 https://ieeexplore.ieee.org/abstract/document/8697354/ https://ieeexplore.ieee.org/abstract/document/8697354/
I hope these are of interest to you.我希望这些是你感兴趣的。
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