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) …
There's a lot of hype about AI right now, and while it's a fundamental tool, the adoption of AI is exaggerated. When most people think of AI, they think of robots. But, in reality, AI consists of algorithms that conduct systems like data processing, that are too bulky and time-consuming for human capabilities. Despite not being widely adopted yet, the future belongs to AI because it enables business systems to operate with granular precision and scalability that simply isn't possible at a human level. The caveat: AI cannot completely replace human input.
Machine learning, combined with neuroimaging data, has the potential to objectively determine whether a patient is suffering pain and where it's located. Accurate pain assessment is critical to provide proper diagnosis and treatment, medical experts agree. However, it's difficult to quantify pain, and most assessments are subjective. Subjective assessments are inconsistent and can't be used when a patient can't communicate, such as during surgery. They're also of limited value in understanding the neurophysiological processes underlying different types of pain.
JERUSALEM (Reuters) - Intel Corp on Tuesday unveiled its latest processor that will be its first using artificial intelligence (AI) and is designed for large computing centers. The chip, developed at its development facility in Haifa, Israel, is known as Nervana NNP-I or Springhill and is based on a 10 nanometer Ice Lake processor that will allow it to cope with high workloads using minimal amounts of energy, Intel said. Facebook, it said, already has started using the product. Intel said its first AI product comes after it had invested in Israeli AI startups, including Habana Labs and NeuroBlade. "In order to reach a future situation of'AI everywhere', we have to deal with huge amounts of data generated and make sure organizations are equipped with what they need to make effective use of the data and process them where they are collected," said Naveen Rao, general manager of Intel's artificial intelligence products group.
The UK is "on the cusp of a huge health tech revolution that could transform patient experience", said health minister Matt Hancock when he announced £250 million to fund a new AI Lab for the National Health Service earlier this month. The lab has been set up to bring together academics and technology companies to work on some of the biggest challenges in health and care. But the AI sector has a reputation for overpromising on what it can deliver – as do politicians.
Cutting-edge robots are on display at the 2019 World Robot Conference in Beijing, running from August 20 to 25, are expected to attract nearly 200 guests from 22 countries. The conference features a series of exhibition areas for new robotic technologies and products - including medical, multi-legged, and smart logistics - as well as four contests with an anticipated 4,500 professional participants. Over 700 robots specialising with more than 21 industrial applications will be exhibited between now and the close of the conference. Among those exhibiting will be HRG Robotics, whose, president Wang Meng, said: 'We will be showcasing a string of successful companies which have got off the ground through the help of HRG, alongside our representative products at WRC 2019, as we aim to form new partnerships with companies around the world.' Also on display will be SmartBird, created by German firm Festo, whose design was inspired by the herring gull and whose flight mimics that of the bird.
SAN FRANCISCO – Soon, you could get fewer familiar ads following you around the internet -- or at least on Facebook. Facebook is launching a long-promised tool that lets you limit what the social network can gather about you on outside websites and apps. The company said Tuesday that it is adding a section where you can see the activity that Facebook tracks outside its service via its "like" buttons and other means. You can choose to turn off the tracking; otherwise, tracking will continue the same way it has been. Formerly known as "clear history," the tool will now go by the slightly clunkier moniker "off-Facebook activity."
USA TODAY Sports' Gabe Lacques breaks down how MLB is trying computer generated strike zones in the Atlantic League. An automated strike zone that converts the home-plate umpire from arbiter to mere messenger is right far more often than it is wrong. A ban on mound visits and relief specialists undeniably speeds the game's pace. And rules changes aimed to encourage balls in play and runners in motion – Thou shalt not shift defensively, but you may "steal" first base – gives hitters options beyond launching balls over a vexing alignment of fielders. Yet as its experiment with a "robotic" strike zone and other nuances enters its second month, the formal partnership between MLB and the Atlantic League illustrates the upsides and consequences of optimization.
When humans learned to extract metals from their ores and mix them into alloys such as bronze, brass and steel, technology took great leaps forward. Now researchers are turning to artificial intelligence to find the next generation of alloys. Scientists are already finding new alloys with increased strength and other improved features. A research team based in China have now published such discoveries in the journal Acta Materialia. Explaining the origins of their work, researcher Yanjing Su of the Beijing Advanced Innovation Center for Materials Genome Engineering cites as his inspiration the success of machine learning in mastering the strategy game Go.
Everyone's talking about the fast.ai Massive Open Online Course (MOOC) so I decided to have a go at their 2019 deep learning course Practical Deep Learning for Coders, v3. I've always known some deep learning concepts/ideas (I've been in this field for about a year now, dealing mostly with computer vision), but never really understood some intuitions or explanations. I also understand that Jeremy Howard, Rachel Thomas and Sylvain Gugger (follow them on Twitter!) are influential people in the deep learning sphere (Jeremy has a lot of experience with Kaggle competitions), so I hope to gain new insights and intuitions, and some tips and tricks for model training from them. I have so much to learn from these folks.
In this blog, we are going to classify images using Convolutional Neural Network (CNN), and for deployment, you can use Colab, Kaggle or even use your local machine since the dataset size is not very large. At the end of this, you will be able to build your own image classifier that detects males and females or anything that is tangible. Let's see a bit of theory about deep learning and CNNs. It is a machine learning algorithm, which is built on the principle of the organization and functioning of biological neural networks. This concept arose in an attempt to simulate the processes occurring in the brain by Warren McCulloch and Walter Pitts in 1943.