As a futurist, an entrepreneur, and a lawyer, I always get asked, 'What do you think is the next big thing in the legal world?' I always begin my response with a catch-all reply: 'The next big thing is anything that helps you attract and keep a client. No client equals no business. A bit of a cliché, I know. But you must constantly rethink how to do things better and be more efficient by using the latest research, thinking, and innovations.'

In one of the year's most telegraphed tech reveals, Facebook announced in April that it was opening its Messenger APIs so brands could deploy chatbots to create rich, automated customer engagement on the app. But barely 24 hours passed before users discovered that the first chatbots on Messenger could not understand some simple questions, were slow to respond, and did not interact in much of a conversational manner. In other words, they were more chatbust than chatbot. Weather app Poncho took the lion's share of the tribal frustration by giving quippy, off-topic responses to questions it didn't understand. And it clearly was not understanding much.

It could change the workplace, our culture, our sense of humanity, and our relationship not only to one another, but to machines. We are joined by Lucy Suchman, professor of Anthropology of Science and Technology at Lancaster University. Also joining us are Nathaniel Popper a business reporter at the New York Times, and Zeynep Tufecki an associate professor at the University of North Carolina and a contributing opinion writer at the New York Times.

We all know about the incredible progress that deep learning has made in recent years. In just 5 years, we went from near-unusable speech recognition and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to beating a world champion. We went further than anybody could have foreseen --if you went back to 2010 and told AI researchers about the things we can do today, most likely no one would believe you. And we keep on making remarkable progress on a month-to-month basis.

In robotics, the Artificial Intelligence (AI) is probably the most exciting field today. Yes, we all think that a robot can work on an assembly line, but there is no harmony that a robot can ever be intelligent. Though the functionality and universality of Internet and computers have outranked the myths about technology advancements and usefulness in everyday life. It's true that AI is changing our lives since decades, but the presence of AI everywhere today was not felt ever like this. Nearly, every scientist has the different opinion about the future of Robotics and AI and about the change which will happen due to the combo of these two.

The consumer sentiment analysis of this one's pretty easy, but will they be compensated? When a person feels sufficiently wronged to lodge a complaint with the Consumer Financial Protection Bureau (CFPB), there's likely to be some negative sentiment involved. But is there a connection between the language they use and the likelihood they will be compensated by the offending company? At the upcoming Sentiment Analysis Symposium, I will discuss how machine learning and rule-based sentiment analysis can support each other in a complementary analysis, and produce actionable information from large amounts of free form text. In this case, machine learning and sentiment analysis could improve and evolve the CFPB's ability to assess consumer complaints.

In three months (as of June 2016) the New Orleans Saints will play a football game against the Atlanta Falcons. I want to know who will win. I ask my friend and he says the Saints. Technically this is a predictive model, but it's probably not worth much. I can improve upon this model by asking other people who they think will win.

When Mark Zuckerberg announced Facebook Messenger would open up to branded chatbots at the F8 conference in April, 1-800 Flowers' was the example he used in his demo. "I love this one," he said. "It's pretty ironic: To order from 1-800-Flowers, you never have to call 1-800-Flowers again." With the "chatbot gold rush" now in full swing, Facebook's launch partner should be a good barometer for the success of Messenger bots so far. Two months in, is anyone getting roses besides the recipient of Zuck's announcement flowers, head Messenger honcho David Marcus?

Emerging Seattle-based fintech startup Kavout has just launched its new investment platform, driven by artificial intelligence (AI), for clients to find trading opportunities using tools powered by machine learning and big data, and with a beta-version of the platform made available to investors. As robo-advisors and automated trading products continue to emerge on the retail side, following the use of algorithmic trading and A.I.-driven technology by institutional firms, Kavout's announcement today appears to reflect the growing related interest from the market for such products. Kavout uses what it calls Kai, the core AI and machine learning process that fuels Kavout's main attributes and functions, including scanning historical SEC filings and stock quotes and examining millions of points of data ever second while analyzing stocks using an objective approach. There is also a Kai Score feature within the platform that provides a predictive analysis ranking reflecting data analytics processed for each security, and based on a stock's future performance related to its valuation, growth, momentum and other qualities. An excerpt of the platform as seen below, upon logging into the beta-version of Kavout, shows one of the Kai Score features. Commenting in an official corporate announcement, Kavout's CEO and co-founder Alex Lu said: "On Wall Street, you'll see that many hedge funds and investment banks are hiring top talent in artificial intelligence and machine learning."

NEW YORK, July 6, 2016 /PRNewswire-USNewswire/ -- Thanks to his business acumen, poster boy looks, and relentless activism for freedom of the internet, Reddit's co-founder Alexis Ohanian has become one of the most high-profile residents of Brooklyn. A startup based in Armenia and San Francisco named 1AI Solutions has recently launched a working AI-based version of Alexis Ohanian named Avedis Ohanian. Additionally they used 3-D printing to replicate the body of Alexis Ohanian, infusing it with their proprietary Artificial Intelligence engine. "There's a lack of qualified IT professionals here in Armenia", said Dr. J.P. Hagopian, the CEO of 1AI Solutions. "We need to hire people, but we simply can't find enough good candidates. At some point our HR manager said that we should clone one of the high-performing Silicon Valley guys. She was kidding, but the idea stuck."