The history of battle knows no bounds, with weapons of destruction evolving from prehistoric clubs, axes, and spears to bombs, drones, missiles, landmines, and systems used in biological and nuclear warfare. More recently, lethal autonomous weapon systems (LAWS) powered by artificial intelligence (AI) have begun to surface, raising ethical issues about the use of AI and causing disagreement on whether such weapons should be banned in line with international humanitarian laws under the Geneva Convention. Much of the disagreement around LAWS is based on where the line should be drawn between weapons with limited human control and autonomous weapons, and differences of opinion on whether more or less people will lose their lives as a result of the implementation of LAWS. There are also contrary views on whether autonomous weapons are already in play on the battlefield. Ronald Arkin, Regents' Professor and Director of the Mobile Robot Laboratory in the College of Computing at Georgia Institute of Technology, says limited autonomy is already present in weapon systems such as the U.S. Navy's Phalanx Close-In Weapons System, which is designed to identify and fire at incoming missiles or threatening aircraft, and Israel's Harpy system, a fire-and-forget weapon designed to detect, attack, and destroy radar emitters.

If you have been wondering how there is always so much to do yet so little time, time has come when you can finally put a halt to that thought as artificial intelligence has just the things you need. In fact, with artificial intelligence and cognitive computing you can get things done with greater efficiency and much lesser effort than you thought was possible. Deep learning, which is one of the technologically superior methods behind the formulation of Artificial Intelligence, traces the evolution path of human intelligence design to develop machines that can perform tasks on their own and without human supervision helping in automation. It is very interesting to note how deep learning has altered the way we operate in various aspects of daily activities and necessity areas. Let us take into consideration 10 practical use cases of Deep Learning Techniques that have been witnessed in the last few years.

Car makers, technology companies and governments now have a set of official guidelines to instruct trials of driverless vehicles in Australia. Published by the National Transport Commission and AustRoads, the guidelines [pdf] set out how autonomous vehicles can be tested on public roads in the country, and how triallists can seek exemption from permits and requirements such as Australian design rules (ADR) ahead of testing. Organisations that wish to trial autonomous vehicles must clearly set out the trial location and provide a high-level description of the technology used, the guidelines state. A traffic management plan that takes into account vehicle density, pedestrians, signage, and route complexity will also need to be provided. A comprehensive insurance policy is similarly a must.

In what is likely a warning to nuclear-armed North Korea, the U.S. military on Wednesday showed off to media its Global Hawk surveillance drone, which is temporarily deployed to its Yokota Air Base in western Tokyo. The massive drone, with a wingspan of about 40 meters and a length of about 15 meters, can fly for long durations at altitudes higher than manned aircraft. The main focus of the deployment is believed to be to collect surveillance data on the North's nuclear- and missile-related facilities as well Chinese military activity in the Western Pacific. The aircraft is one of five Global Hawks sent to Yokota from their home base in Guam to avoid the harsh summer typhoon season that annually hits the Pacific island. The drones are scheduled to operate out of Yokota until the end of October.

Deep learning is not as complex a concept that non-science people often happen to decipher. Scientific evolution over the years have reached a stage where a lot of explorations and defined research work needs the assistance of artificial intelligence. Since machines are usually fed with a particular set of algorithms to understand and react to various tasks within a matter of seconds, working with them broadens the scope of scientific breakthroughs resulting in the invention of techniques and procedures that make human life simpler and enriching. However, in order to work with machines, it is important for them to understand and recognize things just the way the human brain does. For example, we may recognize an apple through its shape and colour. For a robot to go through the same cognitive process, it must be fed with programming structures to recognize the same.

But modern tools are helping to revive Ireland's national language. An Irish proverb advises that it is often wise for one to hold his tongue. An té is ciúine is é is buaine, or "he who is silent is the stronger." But that ancestral wisdom isn't the best policy when the very language it comes from is threatened. The Irish language, Gaelic, is one of more than 40 percent of the world's 6,000 spoken languages that are endangered, according to UNESCO.

There is a lot of AI action in Aotearoa this year. Yes, Artificial Intelligence is a red-hot topic. Many-a-talk at Tech Week last week featured the topic of AI somewhere in the mix. Layered on top of all this is a decent dollop of AI-related media hype. Fair enough; there are some intriguing stories based on comments by thought leaders such as Stephen Hawkings and Elon Musk. But the hype, I believe, contributes to some misunderstanding about exactly what AI is - and what you can and cannot do with it.

Artificial intelligence (AI) has played an important part in B2C relationships over the years. There are thousands of applications, ranging from the recommendation of TV shows to the fraud detection systems deployed across many commercial establishments. The current rise in the use of chatbots is just another level in the use of AI in the B2C space. Perhaps surprisingly, however, the uptake of AI in the B2B world has been rather slow. Interestingly, experts in the B2B niche are aware of the need to embrace AI. 80% of marketing executives in the B2B niche expect AI to transform marketing by the end of the decade.

AIXIjs is a JavaScript demo for running General Reinforcement Learning (RL) agents in the browser. In particular, it provides a general and extensible framework for running experiments on Bayesian RL agents in general (partially observable, non-Markov, non-ergodic) environments. UPDATE (May 2017): I'll be presenting a conference paper containing a literature survey along with some experiments based on AIXIjs at IJCAI 2017, in Melbourne, Australia. The paper (to appear) is: J. S. Aslanides, Jan Leike, and Marcus Hutter. See the main site for more background, documentation, references, and demos.

Google I/O 2017 culminated Friday, but tech circuits are still abuzz about the many announcements that came out of the conference. Several new products, features within products and initiatives were announced at Google I/O and should be prominent throughout the rest of 2017. As with many Google conferences, the tech giant announced the latest figures of its continued growth, which include over 2 billion active users on Android and over 1 billion monthly users on each of its major platforms, including Google Search, Android, Play Store, Gmail, Chrome, YouTube and Google Maps. Here's a rundown of the other announcements and details shared during Google I/O 2017. Google Lens is essentially a search engine, which uses images and videos instead of words.