If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
AI research nonprofit OpenAI has created a system that can generate fake text from a single line -- and it's not open-sourcing the code for fear of misuse. OpenAI was cofounded by tech mogul Elon Musk, and its sponsors include Silicon Valley heavy-hitters such as Peter Thiel and Amazon Web Services. Last year it gained the praise of Bill Gates after it built a team of five neural networks capable of beating human players in the computer game "Dota 2." Read more: Bill Gates hails "huge milestone" for AI as bots work in a team to destroy humans at video game "Dota 2" Now the company has created a system, named GPT2, capable of imitating and generating text based on only a sentence. The Guardian's Alex Hern got to play with the system, and tried typing in a single Guardian headline about Brexit. From that headline alone, GPT2 was able to generate quotes from UK Labour leader Jeremy Corbyn as well as a fictional spokesman for Prime Minister Theresa May.
The recent boom in artificial intelligence has produced impressive results in a somewhat surprising realm: the world of image and video generation. The latest example comes from chip designer Nvidia, which today published research showing how AI-generated visuals can be combined with a traditional video game engine. The result is a hybrid graphics system that could one day be used in video games, movies, and virtual reality. "It's a new way to render video content using deep learning," Nvidia's vice president of applied deep learning, Bryan Catanzaro, told The Verge. "Obviously Nvidia cares a lot about generating graphics [and] we're thinking about how AI is going to revolutionize the field."
Managing customer churn is one major challenge facing companies, especially those that offer subscription-based services. Customer churn (aka customer attrition) can be defined as the loss of customers, and it is caused by a change in taste, lack of proper customer relationship strategy, change of residence and several other reasons. In this article, I will employ the superpowers of machine learning to assist a hypothetical company in predicting customer churn. If businesses can effectively predict customer attrition, they can segment those customers that are highly likely to churn and provide better services to them. In this way, they can achieve a high customer retention rate and maximize their revenue.
What are the key skills supply chain professionals should be developing in an AI-enabled future? "I'm a great believer in great passion," says Ron Castro, Vice President, IBM Supply Chain. And it's just as well given that Ron is responsible for all strategy, execution, and transformation of IBM's US$70Bn global end-to-end supply chain, delivering to clients across more than 170 countries. "Always be as bold and as fast as you can," he says. "I've never looked back in a transformation and thought'Darn it! I wish I had gone slower.' There's always room to be bolder and to go faster."
It was with a strangely deflated feeling in his gut that Harvard biologist Mohammed AlQuraishi made his way to Cancun for a scientific conference in December. Strange because a major advance had just been made in his field, something that might normally make him happy. Deflated because the advance hadn't been made by him or by any of his fellow academic researchers. It had been made by a machine. DeepMind, an AI company that Google bought in 2014, had outperformed all the researchers who'd submitted entries to the Critical Assessment of Structure Prediction (CASP) conference, which is basically a fancy science contest for grown-ups.
Community banks are turning to artificial intelligence, and by 2020, AI could perform a number of underwriting functions and even spur reshoring of repetitive service tasks for financial services companies. AI could also help mortgage lenders detect fraud and enhance the customer experience during the mortgage process, according to a recent survey. Responding to Fannie Mae's latest quarterly Mortgage Lender Sentiment Survey, which was released in October, most lenders (63 percent) say they are familiar with AI/machine learning technology, but only about a quarter (27 percent) have used or tried AI tools for their mortgage business. However, there is clearly momentum behind the technology, as nearly three-fifths of lenders (58 percent) say they expect to adopt some AI solutions in the next two years. The survey was based on data collected in the third quarter of 2018 from 195 senior executives, representing 184 lending institutions.
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Robotics investments in January 2019 have crossed a minimum of $644 million worldwide, armed with a total of 25 robotics transactions. The $644 million raised in January is lower than the funding into this industry raised in December in tune of $652.7 million. One of the biggest investments in January that is $104 million Series A has been made into the Beijing Auto AI Technology Co. of China. Other notable investments in January 2019 into Robotics include the $100 million JV into Ekso Bionics Holdings Inc. and a $59.61 million Series B funding into China-based NASN Automotive Electronics Co. Here are the Top 10 Investments that ruled the Robotics Technologies space in January 2019.
Internet of Things (IoT) has been making waves and fascinating the technology circles for some time. Creating a secure ecosystem of the IoT architecture has been an issue of the technology architects. Converging the blockchain technology with IoT can solve these issues is another which is being brainstormed. We shall start our discussion by first understanding the basic building blocks of IoT infrastructure and its limitations. Then we shall discuss the blockchain technology in brief.
Facial Recognition is a biometric application which catches a picture and uses it to distinguish people by applying facial analytics and comparing it with the current database. Facial recognition systems are regularly utilized for security purposes, particularly in the surveillance field however as of late the utilization of facial recognition in different applications has advanced. The facial recognition market is driven by expanding criminal exercises, internationally. Aside from it, the expanding safety efforts at ATMs and the growing establishment of facial recognition systems at air terminals, and shopping centers drive the facial acknowledgment market. Silicon Valley's way to deal with facial recognition, utilizing amazing PCs and huge datasets of appearances to prepare profoundly precise programming, is just the start to enter into the security market.