Social media may offer a wealth of intelligence to journalists as they scout for stories, but harnessing its true potential becomes a challenge given how easy it is to misrepresent information online. With false facts and narratives intertwining these platforms, it becomes an arduous task for them to filter accurate information. And it is not just with texts. Fuelled by the meme culture, images that we find in our newsfeeds may often be fake. With the second-highest number of internet users after China, these issues are magnified in India.

It is an hour past midnight and you are still wide awake. After scrolling through various social media feeds, you decide you need to talk to someone. The question is, who is actually available for a chat right now? Then you remember, your one-night owl buddy who is always up for a conversation the moment you say, "hey, are you awake?" Lo and behold, your buddy is awake, and even though he is busy eating a late night snack of pizzas, he is ready for some banter. You chat for a bit about things like favorite episodes of Stranger Things, how poorly rested he is and that it is getting late, and that you have work tomorrow morning so you say "good night" and fall back to bed.

An international team of researchers spread out over three labs in Switzerland, Italy, and the UK have successfully joined artificial neurons and an organic neuron to form the first operational biological-artificial hybrid neural network. The team set out to recreate a classic experiment showing how neurons can "learn" by transferring information through synapses. Over time the neurons will require more or less stimulation to "fire," thus demonstrating how neural networks adapt and learn. We've studied this concept in organic neural networks such as those found in living brains, but this is the first time it's been done with both living and artificial neurons. We demonstrate a three-neuron brain-silicon network where memristive synapses undergo long-term potentiation or depression driven by neuronal firing rates.

Artificial intelligence is the most electrifying and exciting technology in the business landscape. It has the potential to drive value across the business, particularly delivering enhanced customer experience, reducing cost and spurring revenue. From smarter products and services to better business decisions and optimized business processes, the technology can transform almost everything. However, before getting started with this disruptive technology businesses need to define their AI strategy effectively in order to boost revenue and accomplish business goals. They must ask themselves how do they create a utilitarian AI strategy to harness its power?

Lego and Nintendo have announced a joint product named Lego Super Mario, which combines the toy maker's playsets with the gameplay of the Mario platformers. Full details have not yet been released but as teased on social media this week, the central element of the new Lego sets is a smart Mario figure with small screens on his chest and face, able to detect which bricks he is near. It will involve a range of building and collecting play schemes. Although Lego has collaborated with other video game franchises in the past, such as Sonic the Hedgehog, this is the first time Mario has appeared in Lego form. Lego Super Mario is being described as a product line rather than one-off.

The American retaliation led to a siege of the United States Embassy in Baghdad and then an American drone attack that killed the leader of Iran's elite Quds force, Maj. The cycle of attacks and counterattacks ended more than two weeks later after Iran launched 16 cruise missiles at bases in Iraq that house American forces. No one was killed by the Iranian missile attacks and tensions had appeared to subside. An Iraqi military official said that hours after the attack on Wednesday, the American-led coalition responded with airstrikes on camps used by Kataib Hezbollah near Abu Kamal in Syria, just across the border from Qaim, Iraq. However American officials said the United States had not carried out those strikes.

You can get the book for 37% off by entering fccmunro into the discount code box at checkout at manning.com. One of the most important questions in technology today is how can humans and machines work together to solve problems? More than 90% of applications that use Artificial Intelligence improve with human feedback. For example, autonomous vehicles get smarter the more that they observe human drivers; smart devices get smarter as they hear more voice commands; and search engines get smarter by observing which sites people actually click on for each search term. Human-in-the-Loop Machine Learning Machine Learning details the process for optimizing the interaction between Machine Learning algorithms and humans who create the data that powers those algorithms.

A study to prod an antimony nucleus (buried in the middle of this device) with magnetic fields became one with electric fields when a key wire melted a gap in it. An accidental innovation has given a dark-horse approach to quantum computing a boost. For decades, scientists have dreamed of using atomic nuclei embedded in silicon--the familiar stuff of microchips--as quantum bits, or qubits, in a superpowerful quantum computer, manipulating them with magnetic fields. Now, researchers in Australia have stumbled across a way to control such a nucleus with more-manageable electric fields, raising the prospect of controlling the qubits in much the same way as transistors in an ordinary microchip. "That's incredibly important," says Thaddeus Ladd, a research physicist at HRL Laboratories LLC., a private research company. "This could potentially change the game for nuclear qubits in silicon."

In the three minutes it will take you to read this blog post, a radiologist will review an estimated 45-60 images.1 And they must continue to review an image every 3-4 seconds during each eight-hour shift, five days a week, all year long. This pace is not sustainable, even for the most experienced radiologists working under ideal conditions. As image volume continues to increase, there simply aren't enough of us radiologists to make this formula work over the long term. We're struggling to balance productivity and quality, and it's contributing to physician burnout.

"2020 Is An Important Year For AI Adoption." I was not surprised when I read this news headline. AI and machine learning markets are already growing at a fast pace. According to a recent report by IDC, the global spending for AI systems will be around $97.9 billion in the year 2023. This year alone $37.5 billion will be spent on the same.