Photo Credit: evenkolder Flickr via Compfight cc Launching a startup comes with a lot of difficulties and could prove very unnerving. You definitely will want to come up with lots of content and managing this will cost you a lot in financial and human resources if done manually. You must by now be used to different types and forms of content management systems (CMS) workflows. However, the integration of AI will enhance an upgrade of your CMS workflows resulting in the optimization of your content creation, bring about the streamlining of your content preparation, and eventually play a big role in the improvement of much-desired customer experience across multiple channels. All you have seen of AI and machine learning may just be the tip of the iceberg.

Singapore's plan to put autonomous vehicles (AVs) on the roads here was praised by global robotics expert Ayanna Howard, who raised questions about the way AV tests are currently conducted overseas. A former Nasa researcher named by Forbes magazine as one of the top 50 women in tech in the United States, Dr Howard also said there is a need to consider the human factor in testing AVs. "A lot of times, with self-driving cars, the issue is that other cars are driven by humans. Most humans don't always follow traffic rules exactly. In a test done in California, drivers would stop, then go, because they wanted to see what the self-driving car would do," said the 47-year-old professor and chair of interactive computing at Georgia Tech in the US.

The promise of blockchain technology couldn't be greater than in the healthcare sector. A prime example is the groundbreaking deployment of blockchain technology by Intermountain Healthcare, a Utah-based, not-for-profit system of 22 hospitals. This medical group has more than 1,600 physicians and advanced practice clinicians at 180 clinics. Intermountain is using blockchain-based technology coupled with artificial intelligence to identify waste in its massive healthcare system, creating better outcomes for patients, and significant savings all around. According to Frank Ricotta, CEO of BurstIQ, the future of healthcare will be driven by data, and blockchain technology is the enabling foundational technology. He explains, "Blockchain is a trust overlay over the Internet that allows parties to transfer representations of value, like health data, safely and securely."

First thing first, AI is useful. It helps us to search files faster, interpret multiple languages, and execute our daily lives as efficiently as possible. Nowadays, it's increasingly able to replicate high-level cognitive tasks, the like of which we once thought that only humans could manage. And, as we learn more and more about exactly how our brains work -- that is, our organic, biological brains -- there are efforts to try and enhance them using artificial intelligence; to improve things like our memory, reaction times, and even our moods. Various companies are now developing devices that use machine learning software to analyse brain data, with widely used brain-computer interfaces being an end goal for brands like Dreem, Thync, and Elon Musk's Neuralink.

He published Apple's first research paper on AI, which then won the Best Paper Award at the Conference on Computer Vision and Pattern Recognition. His work has contributed to the development of autonomous vehicles, Face ID in the iPhone X, facial microexpression detection, and sign language translation – it also landed him on Forbes' 30 Under 30 in Science for 2018. With a vision that artificial intelligence can improve lives, Tomas Pfister has poured himself into AI research, hoping to have a positive impact on the world with this powerful technology. In this exclusive interview, Pfister discusses the origins of his scientific interest, what made his Apple paper so innovative, and his current research with Google. Tomas Pfister: As a child I was always fascinated by computers.

Artificial intelligence has frequently been used to better identify people and objects. But can AI also be used to mask someone's identity? Facebook recently announced that it has created video de-identification technology that can hide people from facial recognition. Facebook has combined an "adversarial autoencoder" and a "trained-face classifier". An autoencoder is an artificial neural network that learns a representation for a set of data unsupervised.

Authors from the Center for Data Science at New York University were Nan Wu, Jason Phang, Jungkyu Park, Yiqiu Shen, Zhe Huang, Thibault Févry, and Kyunghyun Cho, who is also on the faculty of NYU's Courant Institute of Mathematical Sciences. Also authors were Kara Ho at SUNY Downstate College of Medicine; Masha Zorin in the Department of Computer Science and Technology at the University of Cambridge in the United Kingdom; and Stanisław Jastrzębski from Jagiellonian University in Poland, and Joe Katsnelson in the Department of Information Technology, NYU Langone Health.

Delays, overcrowded departure dates, disgruntled passengers-- airports are rarely stress-free or smooth-sailing. But airports around the globe with savvy management are increasingly experimenting with data analytics and AI in order to make the process of flying more attractive for the customers that pass through their terminals. In Finland, Finavia-- the company behind all of the country's 21 airports-- teamed up with advisory firm Fourkind and agency Reaktor to take a look at its airport of Kittilä in Lapland. Finavia found that the airport wasn't able to keep up with the seasonal demands of the country's booming tourism industry. Tourists flocking to see the Northern Lights and catch a glimpse of Santa Claus were causing lengthy delays.

As a scientific field, the growth of mathematics education can be seen as a continuous process of having a deeper understanding of the complexity of learning and teaching. In order to enrich the curriculum and the teaching-learning process, most teachers are looking for new ways to engage students and each other. There are three ideas behind a revolution in education: diversity, curiosity, and innovation. Education needs to create a diverse curriculum that is accessible to inclusion where students are free to be innovative and awaken their imaginations and teachers encourage learning rather than pursuing compliance. A learning revolution is crucial for higher education, and we propose that thinking about complexity, with a focus on emergence, will empower educators to support substantive teaching-learning changes.

This is also evident in the number of technologies referring to artificial intelligence (AI). Autonomous cars and personal assistants like Apple's Siri are often spoken about, while machine learning, deep learning and neural networks are frequently featured in written text. What do these terms mean, and what is the difference between them? How far has technology based on elements of AI progressed? We discussed these topics in a series of interviews with Juraj Jánošík, an expert on artificial intelligence of the ESET company. If we can simulate human intelligence, consciousness and thinking with some technology, we achieve artificial intelligence. There is a term for it - artificial general intelligence - but there is also a concept called super intelligence. While artificial general intelligence (AGI) is meant to imitate human thinking, including its faults, super intelligence (SI) should go even further and exceed the limits of human consciousness and thinking, and considerably surpass them. However, there are more philosophical discourses involved, and we have to admit that currently, we are still far behind, even in the development of AGI.