Computers vs. Brains

Fischetti, Mark

doi:10.1038/scientificamerican1111-104

Cited by 23 publications

(17 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Following current trends without rethinking the way we compute can contribute to energy shortages and environmental issues. Not only are human brains very good at tasks like recognizing faces, but also we do so using a million times less power than supercomputers do when performing these complicated tasks [5], [6]. The development of low-power bioinspired computing will help address these issues.…”

Section: Introductionmentioning

confidence: 99%

Spintronic Nanodevices for Bioinspired Computing

2016

View full text Add to dashboard Cite

Bioinspired hardware holds the promise of low-energy, intelligent, and highly adaptable computing systems. Applications span from automatic classification for big data management, through unmanned vehicle control, to control for biomedical prosthesis. However, one of the major challenges of fabricating bioinspired hardware is building ultra-high-density networks out of complex processing units interlinked by tunable connections. Nanometer-scale devices exploiting spin electronics (or spintronics) can be a key technology in this context. In particular, magnetic tunnel junctions (MTJs) are well suited for this purpose because of their multiple tunable functionalities. One such functionality, non-volatile memory, can provide massive embedded memory in unconventional circuits, thus escaping the von-Neumann bottleneck arising when memory and processors are located separately. Other features of spintronic devices that could be beneficial for bioinspired computing include tunable fast nonlinear dynamics, controlled stochasticity, and the ability of single devices to change functions in different operating conditions. Large networks of interacting spintronic nanodevices can have their interactions tuned to induce complex dynamics such as synchronization, chaos, soliton diffusion, phase transitions, criticality, and convergence to multiple metastable states. A number of groups have recently proposed bioinspired architectures that include one or several types of spintronic nanodevices. In this paper, we show how spintronics can be used for bioinspired computing. We review the different approaches that have been proposed, the recent advances in this direction, and the challenges toward fully integrated spintronics complementary metal–oxide–semiconductor (CMOS) bioinspired hardware.

show abstract

Section: Introductionmentioning

confidence: 99%

Spintronic Nanodevices for Bioinspired Computing

2016

View full text Add to dashboard Cite

show abstract

“…Using autonomous devices updated in real-time eliminates reduces the need for human involvement, removing issues of a non-representative sample of end users or outdated knowledge regarding current business processes. Autonomous UAT devices will perform mission-based scenarios with real environmental parameters, representing the current user experience, and be able to outthink humans as UAT participants, e.g., a faster supercomputer processes 8.2 billion megaflops (million operations per second) and the human brain only 2.2 billion megaflops (Fischetti 2011).…”

Section: Vision 2020: Future Of Completely Automated User Testingmentioning

confidence: 99%

Vision 2020: The Future of Software Quality Management and Impacts on Global User Acceptance

Poston

Calvert²

2015

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. This paper explores the future evolution of software quality management (SQM), testing, and global user acceptance approaches keeping in mind the evolution in software and technology quality management in general, including new technologies and the increasing adoption of new software development life cycle methodologies such as Agile and Scaled Agile. These evolutions are forcing quality organizations to change the way they approach software quality processes, including increased outsourcing of development, and the need to update traditional testing and user acceptance testing approaches which lag behind with manual and invasive techniques. User acceptance as we know it today must evolve.This discussion about evolution should deemphasize the role of the end user in "testing" and emphasize the end user's role in acceptance, adoption, and ability to influence the quality and usability of software much further upstream in the development life cycle. User acceptance teams should increase their role in user experience, the development of usability standards, non-invasive automation techniques gathering usage data, etc. All of these mechanisms should increase the ability of the end user to influence product quality and enhance the user experience and acceptance. Perceptions of end user's participation in user acceptance events need to be transformed away from just another cycle of software testing. User acceptance should not be about testing, but about validating that the end user needs and expectations have been met. All testing and other quality processes should be completed and defects corrected before the end user is engaged in the process of "accepting" the deliverable.Thus, this effort will explore the future of SQM and its impacts on global user acceptance. We will discuss how organizations involve users throughout the development life cycle to facilitate adoption, user experience, and usability of new technologies. This discussion will be embedded in the use of futuristic new technologies and development methodologies. To explore these notions, this study gathers input from technology visionaries about best practices approaches for facilitating SQM and user acceptance throughout the development life cycle.

show abstract

Section: Vision 2020: Future Of Completely Automated User Testingmentioning

confidence: 99%

HCI in Business

2015

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. The Word Sense Disambiguation (WSD) problem has been considered as one of the most important challenging task in Natural Language Processing (NLP) research area. Even though, many of scientists applied the robust machine learning, statistical techniques, and structural pattern matching approach, the performance of WSD is still not able to bit human results due to the complexity of human language. In order to overcome this limitation, currently, the knowledge base such as WordNet has gained high popularity among researchers due to the fact that this knowledge base can extensively provide not only the definitions of nouns and verbs, but also the semantic networks between senses which were defined by linguists. However, knowledge bases are not fully dealing with entire words of human languages because maintaining and expanding the knowledge base is huge task which requires many efforts and time. Expanding knowledge base is not a big issue to concern however, a new approach is the major goal of this paper to solve WSD problem only based on limited knowledge resources. In this paper, we propose a method, named low ambiguity first (LAF) algorithm, which disambiguates a polysemous word with a low ambiguity degree first with given disambiguated words, based on the structural semantic interconnections (SSI) approach. The LAF algorithm is based on the two hypothesises that first, adjacent words are semantically relevant than other words far way. Second, word ambiguity can be measured by frequency differences between synsets of the given word in WordNet. We have proved these hypothesises in the experiment results, the LAF algorithm can improve the performance of traditional WSD results.

show abstract

Computers vs. Brains

Cited by 23 publications

References 0 publications

Spintronic Nanodevices for Bioinspired Computing

Spintronic Nanodevices for Bioinspired Computing

Vision 2020: The Future of Software Quality Management and Impacts on Global User Acceptance

HCI in Business

Contact Info

Product

Resources

About