"I am telling you, the world's first trillionaires are going to come from somebody who masters AI and all its derivatives and applies it in ways we never thought of," the Shark Tank billionaire said on Sunday at the SXSW Conference and Festivals in Austin. Faster than ever computer processors along with exponentially larger data sets are currently laying the cornerstone for the rapid development of artificial intelligence to new industries like insurance, according to Cuban. "We will see more technological advances over the next ten years than we have over the last thirty. It's just going to blow everything away," he said. To prove the point the investor said Google, which had recently started using AI, added $9 billion in revenue as a result.

From Google to Microsoft to Apple and possibly Samsung, AI is almost the buzzword in the smartphone space as well. But as these systems get more powerful and begin to do more, there is a need to make sure that they are not used by authoritarian regimes and then target certain populations. At the ongoing South by South West (SXSW) event in Texas, USA, Microsoft Research's Kate Crawford explained her point on view on the AI scene and how it makes for an ideal excuse to teach these humongous data systems the wrong ideas without any accountability. The Guardian reported the researcher's take on artificial intelligence, hinting at the rise of ultra-nationalism, right-wing authoritarianism and fascism, thanks to the widespread use of these systems. However, it is not the use of these systems, but the way in which human biases are encoded into them that leads to their misuse when they fall into the wrong hands.

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Intelligence agents and military operatives may come to rely heavily on machine learning to parse huge quantities of data, and to control a growing arsenal of autonomous systems. But the U.S. military wants to make sure that this doesn't lead to blindly trusting in any algorithm. The Defense Advanced Research Projects Agency (DARPA), a division of the Defense Department that explores new technologies, is funding several projects that aim to make artificial intelligence explain itself. The approaches range from adding further machine-learning systems geared toward providing an explanation, to the development of new machine-learning approaches that incorporate an elucidation by design. "We now have this real explosion of AI," says David Gunning, the DARPA program manager who is funding an effort to develop AI techniques that include some explanation of their reasoning.

With the exploding growth of the'bots' industry in the last few months, it is most likely only the beginning as there are more tools that help bot developers create better'bots,' and in general, makes their lives a little bit easier. Alongside more popular tools, which already accumulated some seniority and got the attention of the media like'Watson' from'IBM' or'Chatfuel' -- today is really hard to follow up with all the startup companies and other companies that launch products in this rapidly evolving field. It could very well be that bot creators today, are dealing with problems that other entrepreneurs can already help them to solve or at least deal with them more easily. To this end, I decided to gather a short list of bot developing tools which my colleagues and I have got a chance to explore, ranging from NLP solutions to bot builders, analytics and more, which are already available and can serve you. The list is divided according to categories (some tools may appear under more than 1 category) and includes a short explanation about each tool and a link for further information. What this list is not about: It is not the "trip advisor of bot tools" and I do not rate these platforms.

In the beginning (1966), there was ELIZA – she was the first bot of her kind, had roughly 200 lines of code and was extremely smart. But you probably don't know her. Later, came PARRY who was smarter than ELIZA (and could imitate a paranoid schizophrenic patient). But you probably don't know PARRY either. But you do know Siri!

Talespin is a young Delhi-based startup that wants to place chatbots inside stores. The idea, according to Talespin's product head Tanay Dixit, is to help bring some of the benefits of the online shopping experience - such as personalised recommendations - offline as well, at a low cost. The idea was actually born when Dixit tried to go shopping for a t-shirt at Shopper's Stop, and after being shown a lot of different ones, he finally found something he liked, only to learn it wasn't available in his size. He realised that if there was a system to browse through the store's entire catalogue like you would an e-commerce marketplace, then he would have been able to get a better idea more quickly, and it could even have allowed him to place an order for the out- of-stock item, to be delivered to him. And so that's exactly what he set out to build.

Experts discuss a medical ecosystem where people, policies and technology interconnect, allowing doctors to administer precise treatment to one patient -- the N of 1 -- and then deliver it to everyone. The old "take two aspirin and call me in the morning" cure is antithetical to today's precision medicine approach to healthcare, which zeroes in on an individual's unique genetic makeup, environment and lifestyle to determine an exacting treatment. Traditional healthcare is broadly based on cohort studies that compare risk factors and outcomes for a large set of patients who share similar symptoms. Cohort studies are more credible when the "N" -- the number of patients included in the study -- is very large. That's diametrically at odds with the goal of precision medicine, which aims to find a treatment plan tailored for a particular person: "The N of 1."

On first hearing, "machine learning" and "Artificial Intelligence" sound like technologies that will replace people. Computers will find people and sell them stuff they want, so who needs humans in marketing? Well, it turns out that you do. Computers can do the scut work of counting, but only humans can truly say what counts. Marketers are not going to be replaced by automation, but they can make best use of it so long as they know what it can do and can't do, just like any other tool.

"AI is destined to be the perfect tool to fuel organizations' sales efforts and power sales teams with genuinely intelligent tools to more effectively organize their work and sell more." This quote is from an article Jill wrote on LinkedIn titled "#AI Will Reinvent Sales…and Sales Professionals" and sums up nicely what we think about AI in sales too. Technology is fully embedded in today's sales organizations and it goes beyond just a database of customer or prospect information. Sales software does everything from schedule meetings and write emails to identifying sales behaviors that close more deals. That's how artificial intelligence (AI) is changing the sales landscape today. Nudge is a Modern Sales Platform that uses AI to provide sales teams with actionable insights on their target customers.