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) …
The evolution of computing and cost efficiency has made commercial devices capable of running full-on operating systems and complex algorithms, right in the office. IoT platforms in 2018 are continuing to push for the fastest connectivity. That's of course where the concept of Edge Computing comes in, where workload is processed on the edge of the network where the IoT connects the Cloud with the physical world. A key part of this progression is the fast and effective integration between IoT and the Cloud, locating many of the processes onboard the devices themselves and connecting them with the Cloud for the most essential functions. As machine learning algorithms evolve and advance, there are a few things we can expect.
Artificial intelligence and the Internet of Things are two of tech's most popular buzzwords. Put them together, and you have a potent combination for handling the mind-boggling amounts of data flooding enterprises from all directions. Worldwide spending on IoT is expected to reach $1.4 trillion by 2021, according to IDC, as organizations invest in IoT-enabling hardware, software, services and connectivity. IoT is seen as the future of just about everything, from smart-city advances like traffic congestion relief and intelligent street lighting, to better energy management, to industrial robotics and asset tracking, to monitoring of medical equipment and patient condition (not to mention the array of home consumer applications). All of these devices and sensors – an oft-quoted Gartner prediction places the number of connected things at 20.4 billion by 2020 -- produce nearly unimaginable volumes of data.
A major challenge in current climate prediction models is how to accurately represent clouds and their atmospheric heating and moistening. This challenge is behind the wide spread in climate prediction. Yet accurate predictions of global warming in response to increased greenhouse gas concentrations are essential for policy-makers (e.g. the Paris climate agreement). In a paper recently published online in Geophysical Research Letters, researchers led by Pierre Gentine, associate professor of earth and environmental engineering at Columbia Engineering, demonstrate that machine learning techniques can be used to tackle this issue and better represent clouds in coarse resolution ( 100km) climate models, with the potential to narrow the range of prediction. "This could be a real game-changer for climate prediction," says Gentine, lead author of the paper, and a member of the Earth Institute and the Data Science Institute.
In this article, we're going to talk about machine learning, the modern data lake, and what this means for you. But first, let's go back to the first Olympic games in modern times, held in Athens in April of 1896. This photograph is from the men's 100m final. There's only one runner in the 4-point stance, crouched down with hands on the ground, right behind the start line. That was Tom Burke, and he won--even though he was actually more of a distance runner.
Fridays can be the most productive work day, as you look to shore up everything before the weekend starts. Or, maybe instead, it's a day filled with long lunches and listless Internet surfing, as you seek out all the interesting articles you missed during the week. Fear not: Xconomy has done the work for you, bringing a smattering of some of the most interesting reads out there. From Facebook to Microsoft to the NIH, organizations keep working to push forward the uses of A.I. Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So --The New York Times Wait, you're saying we might have invested too much in deep learning?
If the predictions of the UN's Food and Agricultural Organization (FAO) are to be believed, the population of our blue planet is set to reach 9.2 billion by the year 2050. Currently, we are already touching the limits of available acreage for planting crops and breeding cattle. Estimates indicate that we only have as little as 4% available land for agriculture to potentially expand into. So, obviously, we will not be able to feed more mouths by adding more farmland. Instead, we need to process the land we have more efficiently in order to achieve higher yields.
Jun 6, 2016 @ 06:00 AM AI Is The Wave, And CIOs Must Learn To Surf Share to email Oracle Tweet This As compute power increases, so will the capabilities of machine-learning models. " As compute power increases, so will the capabilities of machine-learning models. After years percolating in the backwaters of IT, AI is catching a dynamic wave of interest and investment. Self-driving cars and Go-playing computers have grabbed the public's attention. But AI's potential to dramatically improve cost/benefit equations is why "CIOs should start looking at how this is going to change the business they're in and potentially disrupt the types of applications they're using," says IDC Research Director David Schubmehl.
Researchers have long struggled with accurately predicting climate models because clouds and their atmospheric heating and moistening prove to be a challenge. 'This could be a real game-changer for climate prediction,' said Pierre Gentine, lead author of the paper, and a member of the Earth Institute and the Data Science Institute. 'We have large uncertainties in our prediction of the response of the Earth's climate to rising greenhouse gas concentrations. 'The primary reason is the representation of clouds and how they respond to a change in those gases,' he said. 'Our study shows that machine-learning techniques help us better represent clouds and thus better predict global and regional climate''s response to rising greenhouse gas concentrations.'
Whether Father's Day, Mother's Day, a birthday or simply "just because," buying gifts can feel like counting grains of sand - i.e., it's not easy. Meanwhile, there are 250,ooo--300,000 e-commerce companies in the U.S. all vying for the attention of shoppers. How are consumers possibly expected to decide where to spend their hard-earned money? And how can retailers create a more personalized shopping experience, rather than facing the same demise as the 6,700 retail locations that closed their doors in 2017? In short, the retail sector is in a sticky wicket.
With each passing year, our sector continues to demonstrate its evolving approach to fighting cyber threats, as cyber crime itself continues to evolve. As both business and government move forward with digital transformation initiatives to improve processes and efficiency, the overall security attack surface continues to expand with more potential points of access for criminals to exploit. However, our industry is tackling these challenges head-on, with numerous innovative solutions continuing to come to market. So, what have been the key trends of 2018 thus far? From attending trade shows, to speaking to customers, partners, analysts and the media, several examples have come to the forefront.