Quantum computing--considered to be the next generation of high-performance computing--is a rapidly-changing field that receives equal parts attention in academia and in enterprise research labs. Honeywell, IBM, and Intel are independently developing their own implementations of quantum systems, as are startups such as D-Wave Systems. In late 2018, President Donald Trump signed the National Quantum Initiative Act that provides $1.2 billion for quantum research and development. TechRepublic's cheat sheet for quantum computing is positioned both as an easily digestible introduction to a new paradigm of computing, as well as a living guide that will be updated periodically to keep IT leaders informed on advances in the science and commercialization of quantum computing. SEE: The CIO's guide to quantum computing (ZDNet/TechRepublic special feature) Download the free PDF version (TechRepublic) SEE: All of TechRepublic's cheat sheets and smart person's guides Quantum computing is an emerging technology that attempts to overcome limitations inherent to traditional, transistor-based computers. Transistor-based computers rely on the encoding of data in binary bits--either 0 or 1. Quantum computers utilize qubits, which have different operational properties.

In my opinion the late Jerry Fodor was one of the most brilliant cognitive scientists (that I knew of), if you wanted to have a deep understanding of the major issues in cognition and the plausibility/implausibility of various cognitive architectures. Very few had the technical breadth and depth in tackling some of the biggest questions concerning the mind, language, computation, the nature of concepts, innateness, ontology, etc. The other day I felt like re-reading his Concepts -- Where Cognitive Science Went Wrong (I read this small monograph at least 10 times before, and I must say that I still do not comprehend everything that's in it fully). But, what did happen in the 11th reading of Concepts is this: I now have a new and deeper understanding of his Productivity, Systematicity and Compositionality arguments that should clearly put an end to any talk of connectionist architectures being a serious architecture for cognition -- by'connectionist architectures' I roughly mean also modern day'deep neural networks' (DNNs) that are essentially, if we strip out the advances in compute power, the same models that were the target of Fodor's onslaught. I have always understood the'gist' of his argument, but I believe I now have a deeper understanding -- and, in the process I am now more than I have ever been before, convinced that DNNs cannot be considered as serious models for high-level cognitive tasks (planning, reasoning, language understanding, problem solving, etc.) beyond being statistical pattern recognizers (although very good ones at that).

MIT Lincoln Laboratory has established a new research and development division, the Biotechnology and Human Systems Division. The division will address emerging threats to both national security and humanity. Research and development will encompass advanced technologies and systems for improving chemical and biological defense, human health and performance, and global resilience to climate change, conflict, and disasters. "We strongly believe that research and development in biology, biomedical systems, biological defense, and human systems is a critically important part of national and global security. The new division will focus on improving human conditions on many fronts," says Eric Evans, Lincoln Laboratory director.

The short answer to What is Artificial Intelligence is that it depends on who you ask. A layman with a fleeting understanding of technology would link it to robots. They'd say Artificial Intelligence is a terminator like-figure that can act and think on its own. An AI researcher would say that it's a set of algorithms that can produce results without having to be explicitly instructed to do so. And they would all be right. AI courses at Great Learning provide you with an overview of the current implementation scenario in various industries. With an in-depth introduction to artificial intelligence, you can easily master the basics for a better future in the course.

People crave company when socially isolated -- such as amid lockdown -- in almost exactly the same way that a hungry individual longs for food, a study has concluded. US experts found that after ten hours of seclusion, people not only want company but also exhibit increased brain responses to pictures of social interactions. Social interactions are rewarding, the team said -- and related images (like smiling faces or people chatting) also engages the brain's dopamine-based reward system. The findings build on past work that found mice exhibited increased responses in the midbrain dopamine system when being social after a period of isolation. While this had suggested that the midbrain may play a role in feelings of social isolation, it had been unclear exactly whether the same would apply in humans.

Summary: When convolutional neural networks are trained under experimental conditions, they are decided by the brightness and color of a visual image in similar ways to the human visual system. A convolutional neural network is a type of artificial neural network in which the neurons are organized into receptive fields in a very similar way to neurons in the visual cortex of a biological brain. Today, convolutional neural networks (CNNs) are found in a variety of autonomous systems (for example, face detection and recognition, autonomous vehicles, etc.). This type of network is highly effective in many artificial vision tasks, such as in image segmentation and classification, along with many other applications. Convolutional networks were inspired by the behaviour of the human visual system, particularly its basic structure formed by the concatenation of compound modules comprising a linear operation followed by a non-linear operation.

We are living through one of the greatest of scientific endeavours – the attempt to understand the most complex object in the universe, the brain. Scientists are accumulating vast amounts of data about structure and function in a huge array of brains, from the tiniest to our own. Tens of thousands of researchers are devoting massive amounts of time and energy to thinking about what brains do, and astonishing new technology is enabling us to both describe and manipulate that activity. We can now make a mouse remember something about a smell it has never encountered, turn a bad mouse memory into a good one, and even use a surge of electricity to change how people perceive faces. We are drawing up increasingly detailed and complex functional maps of the brain, human and otherwise. In some species, we can change the brain's very structure at will, altering the animal's behaviour as a result. Some of the most profound consequences of our growing mastery can be seen in our ability to enable a paralysed person to control a robotic arm with the power of their mind.

Decentralized Autonomous Organizations, unlike traditional hierarchical organizations or for the matter of fact even agile organizations are an interconnected network of individuals which work in a self-enforcing manner with self- defined protocols and are not necessarily bound by legal contracts but rather an ecosystem of trust. The unique idea about these organizations is that they are governed by incentive networks in the sense groups of people from disparate disciplines work together on a project which they feel to be highly instrumental for the progress of humanity and science,then at the culmination of the project rewards are distributed in proportions stipulated in the smart contracts those which at the genesis of the project the peers had consented upon. Artificial General Intelligence a discipline created by Ben Goertzel an avid AI researcher, it can be understood and envisaged as an intelligent system possessing the ability to harbor a plethora of mental cognitive states and action capabilities like and more than Humans, possibly it could be a digital twin that leverages on high speed computational advantages. An AGI in contrast with Narrow AI which comprises the current systems in Machine learning discipline, can transcend the barriers that Narrow AI faces because of specialized algorithms that are built for specific use cases whereas AGI can be understood as a general purpose learner constituting in its cognitive organization multiple intertwined yet independent systems the likes of reinforcement learning for grasping new concepts without training data with a purpose of maximizing rewards through trial and error, Natural language processing for deriving important inputs from human interaction, it could go on depending on how incessantly this field is researched with a long term goal of Using AI for better good of Humankind. The plausible form it could manifest is that of Collective General intelligence.

Red Box, a leading platform for voice, announces an extension of its relationship with Microsoft aligned to the launch of Conversa, Red Box's enterprise voice platform. Red Box is already a Preferred Telephony Partner for conversation intelligence, part of Microsoft Dynamics 365 Sales and Customer Service. This latest development in the relationship delivers a unique capture layer for enterprise voice. It combines the power of Conversa audio processing in Microsoft Azure and Microsoft AI, with seamless support of both cloud and premise-based telephony aligned with frictionless zero touch implementations. The on-premise self-install capability provided by Conversa, and powered by Azure Cloud, will simplify the delivery of'AI-Ready', real-time voice capture for those organizations that struggle to gain access to audio data.

"Artificial Intelligence (AI) is the part of computer science concerned with designing intelligent computer systems, that is, systems that exhibit characteristics we associate with intelligence in human behavior – understanding language, learning, reasoning, solving problems, and so on." Artificial intelligence is the practice of computer recognition, reasoning, and action. It is all about bestowing machines the power of simulating human behavior, notably cognitive capacity. However, Artificial intelligence, Machine learning, and Data Science are all related to each other. In the commencement of this blog, we will gain expertise in Artificial Intelligence and its major six branches.