I'm done with artificial intelligence. I will settle for human intelligence. Our access to human intelligence -- let's call it HI -- is increasingly limited in our online environment. Humans have become a rare species, accessed only after hours wasted waiting on the phone. Recently, I applied online for the Power Smart rebate on my new, energy-efficient heat pump that purrs away on the wall in my Saturna Island home.

The Federal Aviation Administration (FAA) has declared that it is expanding tests of an automated system that will ultimately provide near real-time processing of airspace authorization requests for unmanned aircraft (UAS) operators nationwide. Moreover, the drone approval to operate in commercial airspace is about to become easier and safer. The agency deployed the Low Altitude Authorization and Notification Capability (LAANC) to evaluate the feasibility of a fully automated solution enabled by data sharing. Drone operators using LAANC can operate their UAV's in the controlled airspace near airports. Air traffic controllers will also be able to see where planned drone operations will take place. Additionally, LAANC will also make use of data streams containing other airspace information such as temporary flight restrictions and airspace data.

China has a chance to lead in AI because it has managed to adopt new technologies very quickly In the future, if not already, the Silicon Valleys of artificial intelligence (AI) will be in China. Alibaba, China's e-commerce giant, is based in Hangzhou. And Tencent, a multinational conglomerate that is investing heavily in AI, is in Shenzhen. Tencent already has a market capitalisation higher than General Electric, and Baidu is larger than General Motors. China has a chance to lead in AI because it has managed to adopt new technologies very quickly. Just as millions of consumers in India went directly from no phones to smartphones – skipping landlines and flip phones altogether – Chinese consumers are now doing the same, and across a wide range of new technologies.

Last month, over 3,000 Google employees signed a letter taking a stand against Google's collusion with the United States' drone assassination program, which has killed and maimed tens of thousands of people throughout the Middle East and North Africa. Google employees demanded that the company end its participation in "Project Maven," a system of mass drone surveillance integrated with the US drone warfare program, declaring, "We believe that Google should not be in the business of war." It called for the adoption of a policy stating that "neither Google nor its contractors will ever build warfare technology." Google's collusion with the drone assassination program highlights the growing integration of the major technology companies with the US military, which, having declared a new era of "great-power competition" with Russia and China, sees pressing Silicon Valley into its war plans as the only way to regain its military power on the world stage. Just as ominous is Google's role in mass domestic surveillance and censorship.

Across a variety of scientific disciplines, sparse inverse covariance estimation is a popular tool for capturing the underlying dependency relationships in multivariate data. Unfortunately, most estimators are not scalable enough to handle the sizes of modern high-dimensional data sets (often on the order of terabytes), and assume Gaussian samples. To address these deficiencies, we introduce HP-CONCORD, a highly scalable optimization method for estimating a sparse inverse covariance matrix based on a regularized pseudolikelihood framework, without assuming Gaussianity. Our parallel proximal gradient method uses a novel communication-avoiding linear algebra algorithm and runs across a multi-node cluster with up to 1k nodes (24k cores), achieving parallel scalability on problems with up to ~819 billion parameters (1.28 million dimensions); even on a single node, HP-CONCORD demonstrates scalability, outperforming a state-of-the-art method. We also use HP-CONCORD to estimate the underlying dependency structure of the brain from fMRI data, and use the result to identify functional regions automatically. The results show good agreement with a clustering from the neuroscience literature.

Designing a new drug is a lengthy and expensive process. As the space of potential molecules is very large (10^23-10^60), a common technique during drug discovery is to start from a molecule which already has some of the desired properties. An interdisciplinary team of scientists generates hypothesis about the required changes to the prototype. In this work, we develop an algorithmic unsupervised-approach that automatically generates potential drug molecules given a prototype drug. We show that the molecules generated by the system are valid molecules and significantly different from the prototype drug. Out of the compounds generated by the system, we identified 35 FDA-approved drugs. As an example, our system generated Isoniazid - one of the main drugs for Tuberculosis. The system is currently being deployed for use in collaboration with pharmaceutical companies to further analyze the additional generated molecules.

"The long-term goal and true potential of AI is to replicate the complexity of human thinking at the macro level, and then surpass it to solve complex problems--problems both well-documented and currently unimaginable in nature."1 Skin cancer has reached epidemic proportions in much of the world. A simple test is needed to perform initial screening on a wide scale to encourage individuals to seek treatment when necessary. Doctor Hazel, a skin cancer screening service powered by artificial intelligence (AI) that operates in real time, relies on an extensive library of images to distinguish between skin cancer and benign lesions, making it easier for people to seek professional medical advice. Hackathons have proven to be a successful way to channel energy and technical expertise into solving very specific problems and generating bright, new ideas for applied technology.

It's hard to remember the days when artificial intelligence seemed like an intangible, futuristic concept. This has been decades in the making, however, and the past 90 years have seen both renaissances and winters for the field of study. At present, AI is launching a persistent infiltration into our personal lives with the rise of self-driving cars and intelligent personal assistants. In the enterprise, we likewise see AI rearing its head in adaptive marketing and cybersecurity. The rise of AI is exciting, but people often throw the term around in an attempt to win buzzword bingo, rather than to accurately reflect technological capabilities.

According to a survey by the American Association of State Highway and Transportation Officials (AASHTO) they have found that 35 of 44 responding State Department of Transportation (DOTs) are using UAV's for varied purposes. According to March 2018 survey, 20 state DOTs have integrated drones into their daily functions. Other 15 state DOTs are in research phase. "This is another example of how state DOTs are advancing innovation to improve safety and productivity for the travelling public." Drones are being used to gather photos and videos of highway construction projects, pavement and bridge inspection, scientific research, pole inspections and traffic control and monitoring.

Composite image showing an infrared view of Saturn's moon Titan, taken from NASA's Cassini spacecraft. Some measures suggest that Titan has the highest habitability rating of any world other than Earth, based on factors such as availability of energy, and various surface and atmosphere characteristics. Developments in artificial intelligence may help us to predict the probability of life on other planets, according to new work by a team based at Plymouth University. The study uses artificial neural networks (ANNs) to classify planets into five types, estimating a probability of life in each case, which could be used in future interstellar exploration missions. The work is presented at the European Week of Astronomy and Space Science (EWASS) in Liverpool on 4 April by Mr Christopher Bishop.