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Artificial Intelligence: A Best Revolutionary Feat Of Computer Science

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Artificial Intelligence

Neural Processing Letters is an international journal that promotes fast exchange of the current state-of-the art contributions among the artificial neural network community of researchers and users. The Journal publishes technical articles on various aspects of artificial neural networks and machine learning systems. Coverage includes novel architectures, supervised and unsupervised learning algorithms, deep nets, learning theory, network dynamics, self-organization, optimization, biological neural network modelling, and hybrid neural/fuzzy logic/genetic systems. The Journal publishes articles on methodological innovations for the applications of the aforementioned systems in classification, pattern recognition, signal processing, image and video processing, robotics, control, autonomous vehicles, financial forecasting, big data analytics, and other multidisciplinary applications.

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Journal highlights:

  • An international journal publishing state-of-the-art research results and innovative ideas on all aspects of artificial neural networks and machine learning
  • Coverage includes theoretical developments, biological models, learning theory, applications, hardware implementation, and more
  • Promotes timely exchange of information in the community of neural network researchers and users
  • High degree of author satisfaction: 91% of authors who answered a survey reported that they would definitely publish or probably publish in the journal again

AI and Cyber Security

Hardly a day passes without a news story about a high-profile data breach or a cyber attack costing millions of dollars in damages. Cyber losses are difficult to estimate, but the International Monetary Fund places them in the range of US$100–$250 billion annually for the global financial sector (Lagarde 2012). Furthermore, with the ever-growing pervasiveness of computers, mobile devices, servers and smart devices, the aggregate threat exposure grows each day. While the business and policy communities are still struggling to wrap their heads around the cyber realm’s newfound importance, the application of AI to cyber security is heralding even greater changes.

One of the essential purposes of AI is to automate tasks that previously would have required human intelligence. Cutting down on the labour resources an organization must employ to complete a project, or the time an individual must devote to routine tasks, enables tremendous gains in efficiency. For instance, chatbots can be used to field customer service questions, and medical assistant AI can be used to diagnose diseases based on patients’ symptoms.

In a simplified model of how AI could be applied to cyber defence, log lines of recorded activity from servers and network components can be labelled as “hostile” or “non-hostile,” and an AI system can be trained using this data set to classify future observations into one of those two classes. The system can then act as an automated sentinel, singling out unusual observations from the vast background noise of normal activity.

The New Value of Data

AI technology will alter the cyber security environment in yet another way as its hunger for data changes what kind of information constitutes a useful asset, transforming troves of information that would not previously have been of interest into tempting targets for hostile actors.

While some cyber attacks aim solely to disrupt, inflict damage or wreak havoc, many intend to capture strategic assets such as intellectual property. Increasingly, aggressors in cyberspace are playing a long-term game, looking to acquire data for purposes yet unknown. The ability of AI systems to make use of even innocuous data is giving rise to the tactic of “data hoovering” — harvesting whatever information one can and storing it for future strategic use, even if that use is not well defined at present.

A recent report from The New York Times illustrates an example of this strategy in action (Sanger et al. 2018). The report notes that the Chinese government has been implicated in the theft of personal data from more than 500 million customers of the Marriott hotel chain. Although commonly the chief concern regarding data breaches is the potential misuse of financial information, in this case the information could be used to track down suspected spies by examining travel habits, or to track and detain individuals to use them as bargaining chips in other matters.

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Data And AI Connect

Data and AI connect, unify and unlock both intangible and tangible assets; they shouldn’t be thought of as distinct. Quantity of data is becoming a key factor to success in business, national security and even, as the Cambridge Analytica scandal shows, politics. The Marriott incident shows that relatively ordinary information can now provide a strategic asset in the fields of intelligence and national defence, as AI can wring useful insights out of seemingly disparate sources of information. Therefore, this sort of bulk data will likely become a more common target for actors operating in this domain.

Artificial intelligence (AI) is truly a revolutionary feat of computer science, set to become a core component of all modern software over the coming years and decades. This presents a threat but also an opportunity. AI will be deployed to augment both defensive and offensive cyber operations. Additionally, new means of cyber attack will be invented to take advantage of the particular weaknesses of AI technology. Finally, the importance of data will be amplified by AI’s appetite for large amounts of training data, redefining how we must think about data protection. Prudent governance at the global level will be essential to ensure that this era-defining technology will bring about broadly shared safety and prosperity.

FAQs: Artificial Intelligence: A Best Revolutionary Feat Of Computer Science

What are the 4 types of AI?

4 main types of artificial intelligence
Reactive machines. Reactive machines are AI systems that have no memory and are task specific, meaning that an input always delivers the same output. …
Limited memory. The next type of AI in its evolution is limited memory. …
Theory of mind. …

What is an example of AI artificial intelligence?

The following are the examples of AI-Artificial Intelligence: Google Maps and Ride-Hailing Applications. Face Detection and recognition. Text Editors and Autocorrect.

Is Siri artificial intelligence?

Siri is Apple’s virtual assistant for iOS, macOS, tvOS and watchOS devices that uses voice recognition and is powered by artificial intelligence (AI).

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