AI News, Artificial intelligence (AI)

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CES 2019: Nvidia partners with Mercedes on artificial intelligence

Mercedes and Nvidia are aiming to develop a single system with self-driving capabilities and 'smart cockpit' functions, rather than the current system involving multiple small processors known as electronic control units (ECUs), where each ECU controls separate parts of the car such as the windows, door locks, power steering, and braking.

The Mercedes announcement comes a day after Nvidia announced Drive AutoPilot, a driver-assistance system for Level 2+ autonomous vehicles that integrates Nvidia's Xavier SoC processors with new Nvidia Drive software to process data from outside and inside the vehicle.

CES 2019: Nvidia CEO Huang explains how AI changes everything Jensen Huang, fonder and CEO of computer graphics chip maker Nvidia, showed off the achievements of his company's neural network technology during a press conference Sunday night in Las Vegas at the Consumer Electronics Show.

CES 2019: Mobileye inks autonomous vehicle deals across China Mobileye is aiming to provide an autonomous public transport solution in China by 2022, while it also delivers and develops advanced driver assistance systems with Great Wall Motors.

CES 2019: Sprint pairs Curiosity IoT with 5G to power smart cities, autonomous vehicles Sprint is combining its Curiosity IoT platform and its 5G mobile network to power a smart city in South Carolina and an autonomous vehicle test track in Georgia, and to launch more precise mapping technology.

What Is Artificial Intelligence? Examples and News in 2019

Coined in 1955 by John McCarthy as 'the science and engineering of making intelligent machines,' artificial intelligence (or AI) is software that is able to use and analyze data, algorithms and programming to perform actions, anticipate problems and learn to adapt to a variety of circumstances with and without supervision.

Neural networks (often called artificial neural networks, or ANN) essentially mimic biological neural networks by 'modeling and processing nonlinear relationships between inputs and outputs in parallel.'Machine learning generally uses statistics and data to help improve machine functions, while deep learning computes multi-layer neural networks for more advanced learning.

The original seven aspects of AI, named by McCarthy and others at the Dartmouth Conference in 1955, include automatic computers, programming AI to use language, hypothetical neuron nets to be used to form concepts, measuring problem complexity, self-improvement, abstractions, and randomness and creativity.

And while AI is generally a blanket term for these different kinds of functions, there are several different kinds of AI that are programmed for different purposes - including weak and strong AI, specialized and general AI, and other software.

Weak AI is designed to be supervised programming that is a simulation of human thought and interaction - but is ultimately a set of programmed responses or supervised interactions that are merely human-like.

Siri and Alexa are a good example of weak AI, because, while they seemingly interact and think like humans when asked questions or to perform tasks, their responses are programmed and they are ultimately assessing which response is appropriate from their bank of responses.

For this reason, weak AI like Siri or Alexa don't necessarily understand the true meaning of their commands, merely that they comprehend key words or commands and their algorithms match them up with an action.

However, on a basic level, unsupervised learning goes into problems without any pre-programmed answers, and is able to use a mixture of logic and trial and error to learn the answers or categorize things.

In general, much of the cutting-edge, boundary-pushing AI developments of recent years have been general AI - which are focused on learning and using unsupervised programming to solve problems for a variety of tasks and circumstances.

AI has been used in business for various purposes including process automation (by transferring email and call data into record systems, helping resolve billing issues and updating records), cognitive insight (for predicting a buyer's preferences on sites, personalizing advertising and protecting against fraud) and cognitive engagement (used primarily in a customer service capacity to provide 24/7 service and even answers to employee questions regarding internal operations).

For the 2016 year, the global chatbot market was reportedly worth $190.8 million - and could potentially comprise about 25% of customer service interactions by 2020, according to Gartner (IT) .

As far back as the mid 1600s, French scientist and philosopher Rene Descartes hypothesized about two divisions - machines that could one day think and learna specific task, and those that could adapt to perform a variety of different tasks as humans do.

Although ELIZA didn't actually speak (and communicated via text instead), the technology was the first that was developed to relay messages in language (or natural language processing) as opposed to using computer code and programming.

AImoved from a largely cutting-edge technological development to useful applications in business by 1980, when Digital Equipment Corporation's XCONwas able to save the company around $40 million in 1986 through its learning system.

And just six years later, IBM's cognitive computing engine Watson beat Jeopardy's champion, winning the $1 million prize money - further indicating AI's capabilities in successfully navigating language-based problems.

The research paper Building High-Level Features Using Large Scale Unsupervised Learningwas published in 2012 by researchers at Google (GOOG) and Stanford, and explained advances in unsupervised learning through deep neural networks that allowed AI to learn to recognize different pictures of cats without labeling the pictures.

'There are plenty of great things you can do with AI that save lives, including in a military context, but to openly declare the goal is to develop autonomous weapons and have a partner like this sparks huge concern,' Toby Walsh,professor atUniversity of New South Walesand organizer of the boycott, told The Guardian earlier this year.

It just opens up Pandora's box of psychology and science,' McMullen told Forbes earlier this year.'It's been evident that when you are using a very lifelike robot as a conduit for the AI and for the conversation, people tend to talk to that in a different way than they would, say, something on a computer screen.

We're living in a culture where we have a surplus of human beings, we don't have any problems with the amount of human beings that we have in the world, but we're creating this culture and this climate where we're trying to encourage people to form relationships with commercial goods, basically,' Richardsontold Forbes in September.

The principle concern seems to revolve around how exports of AI may boost the industries in other countries like China, potentially to the detriment of the U.S. 'The number of cases where exports can be sufficiently controlled are very, very, very small, and the chance of making an error is quite large,' Jack Clark, head of policy at OpenAI, told The New York Times.

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