In 2017 we saw unprecedented hype about chatbots, mainly thanks to Microsoft's bot'Tay' and Facebook moving to integrate chatbot capabilities into Messenger. The current use of artificial intelligence to communicate with us in natural language can make us feel like we are experiencing the future already. However, you don't have to be a giant conglomerate with an entire team of developers to be in a position to build one for your own business. With the new readily available technology on the market, you can now literally do it from your own home, and you won't need complex programming skills to do so. Here is a selection of the best current platforms to help to build your chatbot.

Artificial Intelligence is still a growing field! AI is becoming an integral part of most organisations be it Google, Facebook and others in solving some of the most significant problems faced by both companies and customers. In fact, this is one of the most well-funded segment in the field of technology comparatively. Having said that, almost every startup strives hard to bring unique propositions into the market. Recently, the French government under Emmanuel Macron has announced a program by investing $1.8 billion into AI over the next four years.

You are reading a summary of the talk held by Jürgen Gietl at our New Year's Apero 2018 in Zurich. Companies have to learn as soon as possible how they can combine artificial intelligence with their brands and the knowledge they possess about their customers' life scarcities. Because data alone is worth nothing, it needs peak performances and empathy. We cannot relinquish control of our interfaces with the customer – we have to use them: to empathize with his needs, recognize his shortages, and satisfy them better than any chatbot ever could. I have a new girlfriend.

The global insurance industry will grow more strongly than the global economy in 2018 and 2019, Munich Re predicts in its latest outlook. "This year and next, we expect global premium to grow by more than €460 billion in all. This is equivalent to average annual premium growth of 5.3% (in real terms, i.e., adjusted for inflation: 3.7%), whereas global GDP is expected to grow by only 4.9% (3.3% in real terms). Life insurance, in particular, looks set to return to strong annual premium growth of 5.6% (3.9% in real terms) after a weak 2017. Property-casualty insurance is benefiting from the currently favorable economic environment. In this segment, we are expecting annual growth rates of close to 5% (3.3% in real terms). Emerging countries are the primary growth drivers, but somewhat stronger growth rates in high-volume industrialized countries are also contributing to this positive development."

Editor's Note: SHRM has partnered with Harvard Business Review to bring you relevant articles on key HR topics and strategies. It was going to be the factory of the future. Dubbed the "Alien Dreadnought," Tesla's new manufacturing facility in Fremont, California, was designed to be fully automated -- no humans need apply. If all went well, AI-powered robots would enable the company to achieve a weekly production of 5,000 Model 3 electric cars to keep up with burgeoning demand. But Tesla fell far short of that mark, manufacturing just 2,000 vehicles a week.

At a Gamescom 2018 press conference in Cologne, Germany, Nvidia rolled out its newest generation of gaming chips - the RTX 2070, RTX 2080 and RTX 2080 Ti. They are based on its recently launched chip blueprint called "Turing," which Nvidia is also using for higher-priced chips announced last week for game designers, movie makers and other computer graphics professionals. The chips will range from $499 to $999 and will be available in retail stores starting Sept. 20, Chief Executive Jensen Huang said at the event. The biggest selling point of the gaming chips released on Monday is an improvement in so-called "real-time ray tracing," or the ability for the chip to simulate how light rays will bounce around in a visual scene, which helps video games and other computer graphics more closely resemble shadows and reflections in the real world. Part of how the new chip achieves high resolution graphics quickly is a special section of the chip that finishes most of the image but then uses artificial intelligence to guess what the unfinished pixels should look like.

Changing people's behaviour is key to tackling the world's health, social and environmental problems, such as obesity, sustainable living and cybersecurity. To change behaviour, though, we need to know what works, for whom, where and how. But research is generated far faster than humans can access and use it. A search on Google Scholar for "behaviour change" produced over 60,000 hits for the first six months of 2018. Evidence on behaviour change interventions is also messy.

Ibrahim al-Asiri is seen in these images supplied to Yemeni police as part of a terror suspect handbook. A top Al Qaeda bomb maker who masterminded a plot to bring down an airliner over Detroit on Christmas Day 2009 was killed in a U.S. drone strike in Yemen last year, a senior U.S. official told Fox News Monday. The Associated Press previously reported that Ibrahim al-Asiri was dead, citing a tribal leader and an Al Qaeda-linked source who said that he was killed in the governate of Marib in eastern Yemen. The tribal leader said that al-Asiri was struck by the drone, along with two or four of his associates, as he stood beside his car. Al Qaeda itself has remained silent about its top bomb maker.

Are you average in every way, or do you sometimes stand out from the crowd? Your answer might have big implications for how you're treated by the algorithms that governments and corporations are deploying to make important decisions affecting your life. "What algorithms?" you might ask. The ones that decide whether you get hired or fired, whether you're targeted for debt recovery and what news you see, for starters. Automated decisions made using statistical processes "will screw [some] people by default, because that's how statistics works," said Dr Julia Powles, an Australian lawyer currently based at New York University's Information Law Institute.

Bayesian optimization (BO) is a popular algorithm for solving challenging optimization tasks. It is designed for problems where the objective function is expensive to evaluate, perhaps not available in exact form, without gradient information and possibly returning noisy values. Different versions of the algorithm vary in the choice of the acquisition function, which recommends the point to query the objective at next. Initially, researchers focused on improvement-based acquisitions, while recently the attention has shifted to more computationally expensive information-theoretical measures. In this paper we present two major contributions to the literature. First, we propose a new improvement-based acquisition function that recommends query points where the improvement is expected to be high with high confidence. The proposed algorithm is evaluated on a large set of benchmark functions from the global optimization literature, where it turns out to perform at least as well as current state-of-the-art acquisition functions, and often better. This suggests that it is a powerful default choice for BO. The novel policy is then compared to widely used global optimization solvers in order to confirm that BO methods reduce the computational costs of the optimization by keeping the number of function evaluations small. The second main contribution represents an application to precision medicine, where the interest lies in the estimation of parameters of a partial differential equations model of the human pulmonary blood circulation system. Once inferred, these parameters can help clinicians in diagnosing a patient with pulmonary hypertension without going through the standard invasive procedure of right heart catheterization, which can lead to side effects and complications (e.g. severe pain, internal bleeding, thrombosis).