My ten year old daughter recently told me that she does not expect to get a driver's license. Upon asking her why, she explained that when she is old enough to drive, she expects all cars to be self-driving. She further elaborated that she should need to be even more vigilant in a self-driving car, because, in her words – "I always know what I am thinking, but who knows what those cars are thinking!" As AI and ML permeate more businesses and become part of daily life, natural human fears are being expressed in various ways, from individual to corporate concerns to government regulations. News stories appear daily, detailing AI mistakes that led to corporate losses or embarrassment [2,3,4,7].

A recent decision by research lab OpenAI to limit the release of a new algorithm has caused controversy in the AI community. The nonprofit said it decided not to share the full version of the program, a text-generation algorithm named GPT-2, due to concerns over "malicious applications." But many AI researchers have criticized the decision, accusing the lab of exaggerating the danger posed by the work and inadvertently stoking "mass hysteria" about AI in the process. The debate has been wide-ranging and sometimes contentious. It even turned into a bit of a meme among AI researchers, who joked that they've had an amazing breakthrough in the lab, but the results were too dangerous to share at the moment.

The FAA will require drone operators in the United States to display their registration numbers on the outside of their small UAVs starting on February 25, 2019. The new regulation revises an existing policy that allows drone owners to put a UAV's registration number inside of the device's battery compartment. Drone operators in the US must register their aerial vehicle with the FAA, at which time they're given a registration number. Since launching the registration requirement, the FAA has permitted drone owners to conceal their identifier within an enclosed compartment on the drone, assuming the compartment could be opened without using tools. This permission aimed to'grant flexibility to the diverse types of small unmanned aircraft commercially available.'

Naval technology is developing so rapidly that Australia's new $50 billion fleet of submarines may one day have to face deadly underwater drones, an expert has warned. Earlier this month, the federal government announced the signing of the Attack class submarine Strategic Partnering Agreement with French shipbuilder Naval Group. It will build 12 attack submarines to replace the Royal Australian Navy's ageing Collins class vessels, with the first one scheduled to be delivered in the early 2030s, the federal government said. But Russia has already provided a glimpse of underwater autonomous – or drone - weaponry. The Russian Ministry of Defence released testing footage of its'Poseidon' – a high-speed nuclear torpedo. Naval chiefs said the weapon is capable of carrying both conventional and nuclear warheads and will have a maximum speed of 200 km/h.

In any business, how can you achieve success? Well, there are many methods, but the best is to follow the changes in technology. In short, technology has always shortened manual work in any industry and made jobs easier for human beings. In recent times, however, many of the industry sectors have implemented artificial intelligence in their operations to enhance the quantity and quality of their products or services. As per a survey, nearly 62 percent of companies in developed countries have implemented Artificial intelligence in one form or the other.

When it comes to analytics tools, data scientists have a plethora of options available to them. Features that may appeal to one data scientist don't necessarily work for another. When it comes to offerings from H2O.ai, users expressed different reasons for their choices. Last week, Datanami was a guest at H2O.ai's annual user conference, called H2O World, and had a chance to talk with several customers, including Ruben Diaz, a data scientist with Vision Banco, and Bharath Sudharsan, director of data science and innovation at Armada Health. Vision Banco is one of Paraguay's largest banks, with consumer and micro-finance lines of business.

So there's been a lot of coverage by various websites, data science gurus, and AI experts about what 2019 holds in store for us. Everywhere you look, we have new fads and concepts for the new year. This article is going to be rather different. We are going to highlight the dark horses – the trends that no one has thought about but will completely disrupt the working IT environment (for both good and bad – depends upon which side of the disruption you are on), in a significant manner. So, in order to give you a taste of what's coming up, let's go through the top four (plus 1 (bonus) five) top trends of 2019 for data science: This single innovation is going to change the way machine learning works in the real world.

In 2014, a group of researchers at Google and NYU found that it was far too easy to fool ConvNets with an imperceivable, but carefully constructed nudge in the input [1]. Let's look at an example. We start with an image of a panda, which our neural network correctly recognizes as a "panda" with 57.7% confidence. Add a little bit of carefully constructed noise and the same neural network now thinks this is an image of a gibbon with 99.3% confidence! This is, clearly, an optical illusion -- but for the neural network.

Kansas WebFile, the state's full service online tax filing portal, has a new feature. "We were the first state to implement a chatbot within a tax system, and we're the first state to offer a chatbot of any nature," Nolan Jones general manager of Kansas Information Consortium said. Agent Kay, the state's 24/7 official chatbot, can help you file your tax return online. "And it provides them a better experience with dealing with the government and some like taxes they don't want to be in there very long. They just want to get their filing done," Jones said.

I am a major sci fi fan. Well, at least I thought I was until I went to my first Star Trek convention in my 20s and realized that I was in the minority of people who did not speak Klingon or know episode numbers, titles or dates. Most recently, I have become inspired by Black Mirror, a show originally aired by the BBC and now offered on Netflix. The brainchild of Charlie Brooker, Black Mirror is the Twilight Zone for our times, giving us a glimpse as to how technology trajectories can be used to affect society in unintended ways in the coming decades. As Frederik Pohl used to say, 'A good science fiction story should be able to predict not the automobile but the traffic jam.' Metaphorically speaking, this show sure is predicting traffic jams.