Survival of the Fittest Amidst the Cambrian Explosion of Processor Architectures for Artificial Intelligence : Invited Paper

Abstract The singularity of artificial intelligence (AI), which transcends human intelligence to play the role of God, is imminent. In this context, the Chinese judicial system has gained some latecomer advantage, with the help of information technology, the Internet, big data, cloud computing, and AI to improve the efficiency and transparency of case handling. The trial process has undergone extensive and profound qualitative mutations. This represents a challenge to the institutional arrangements of the modern rule of law. At this stage, we should adopt a cautious and prudent attitude towards the design and application of legal-expert systems as well as machine learning. Especially from the aspect of computer sentencing, it is even more necessary to avoid a rush for quick results, and there is no need to completely exclude the judge’s discretion and free evaluation of the evidence through inner conviction. The finality of the judicial power is destined to choose a correct final solution through a debate on the survival of the fittest mechanism. In the face of such a modern rule-of-law system, big data, cloud computing, information technology, and AI are just auxiliary means to achieve legal justice. It is impossible to put the cart before the horses. This is a basic principle that we should always bear in mind.

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Is a Cambrian Explosion Coming for Robotics?

The Journal of Economic Perspectives ◽

10.1257/jep.29.3.51 ◽

2015 ◽

Vol 29 (3) ◽

pp. 51-60 ◽

Cited By ~ 76

Author(s):

Gill A. Pratt

Keyword(s):

Artificial Intelligence ◽

Data Storage ◽

Cambrian Explosion ◽

Cloud Robotics ◽

Short Period ◽

Key Technologies ◽

Technological Developments ◽

Rapid Diversification ◽

Virtuous Cycle ◽

Life On Earth

About half a billion years ago, life on earth experienced a short period of very rapid diversification called the “Cambrian Explosion.” Many theories have been proposed for the cause of the Cambrian Explosion, one of the most provocative being the evolution of vision, allowing animals to dramatically increase their ability to hunt and find mates. Today, technological developments on several fronts are fomenting a similar explosion in the diversification and applicability of robotics. Many of the base hardware technologies on which robots depend—particularly computing, data storage, and communications—have been improving at exponential growth rates. Two newly blossoming technologies—“Cloud Robotics” and “Deep Learning”—could leverage these base technologies in a virtuous cycle of explosive growth. I examine some key technologies contributing to the present excitement in the robotics field. As with other technological developments, there has been a significant uptick in concerns about the societal implication of robotics and artificial intelligence. Thus, I offer some thoughts about how robotics may affect the economy and some ways to address potential difficulties.

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Efficient Acceleration of Stencil Applications through In-Memory Computing

Micromachines ◽

10.3390/mi11060622 ◽

2020 ◽

Vol 11 (6) ◽

pp. 622

Author(s):

Hasan Erdem Yantır ◽

Ahmed M. Eltawil ◽

Khaled N. Salama

Keyword(s):

Artificial Intelligence ◽

Computer Architecture ◽

Computer Architectures ◽

Huge Amount ◽

Promising Candidate ◽

Processing Elements ◽

Iterative Processing ◽

Processor Architectures ◽

Stencil Codes ◽

Memory Bottleneck

The traditional computer architectures severely suffer from the bottleneck between the processing elements and memory that is the biggest barrier in front of their scalability. Nevertheless, the amount of data that applications need to process is increasing rapidly, especially after the era of big data and artificial intelligence. This fact forces new constraints in computer architecture design towards more data-centric principles. Therefore, new paradigms such as in-memory and near-memory processors have begun to emerge to counteract the memory bottleneck by bringing memory closer to computation or integrating them. Associative processors are a promising candidate for in-memory computation, which combines the processor and memory in the same location to alleviate the memory bottleneck. One of the applications that need iterative processing of a huge amount of data is stencil codes. Considering this feature, associative processors can provide a paramount advantage for stencil codes. For demonstration, two in-memory associative processor architectures for 2D stencil codes are proposed, implemented by both emerging memristor and traditional SRAM technologies. The proposed architecture achieves a promising efficiency for a variety of stencil applications and thus proves its applicability for scientific stencil computing.

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