Nikolas Badminton is a researcher and futurist based in Vancouver, Canada, and provides opinions about humanity, the future of work and life with technology. His opinions and thoughts on the future can be seen at nikolasbadminton.com. Money makes the world go round, or so they say. Payments, investments, insurance and billions of transactions are the beating heart of a fractal economy, which echoes the messy complexity of natural systems, such as the growth of living organisms and the bouncing of atoms. Financial systems are larger than the sum of their parts.

But once Feldman was hired to write the personality of a chatbot for Kasisto, a startup that focuses on artificial intelligence software for banks, she became vocal about the importance of taking gender out of the identity equation. Under her watch, MyKai, the bot she was hired to craft a personality for, would be neither female nor male. Feldman's boss at Kasisto, Dror Oren, says the work the team has done with the bot made him more outspoken about the need for equality in tech than he'd have imagined going into the project, and he's a self-proclaimed feminist to begin with. Now, he's hyperaware of the differences between the personality of Kai and overly feminine answers inside similar products made by most large tech companies. Kasisto is on to something.

A friend of mine has spent more than the value of his San Antonio home on Amazon Prime in the last five years. That is precisely why the next big battlefield for marketing and advertising lies with artificially intelligent digital agents like Alexa, Siri, Google Assistant, Facebook M, and Cortana. And it's why the company that cracks AI-powered agents will be the next trillion-dollar corporation. Every communications technology that has ever been invented has been seized by brands as a new way to connect with customers. A marketing manager sent the first spam email in 1978.

As consumers, we're familiar with -- if not yet wholly invested in -- the term "artificial intelligence," whether it's by way of self-driving cars or voice-enabled search like Siri and Amazon's Alexa. Artificial intelligence is on course to drastically change the enterprise, with big implications for productivity and possibly even larger ramifications on the economy. Business intelligence is providing companies with an overabundance of data, but it's AI that's emerging to make this data actionable by giving executives and employees useful insights that are relevant to their specific roles and what they need to accomplish on any given day. To name just a few of implications of how business will change with AI, today's workforce will be empowered to take on new approaches with time management, teamwork and collaboration, client service, and business forecasting. For example, instead of just assessing raw data, artificial intelligence can take into account historical patterns and current context of an employee's role, the nature of the business within which they work and market dynamics.

However, there are two distinct species both referred to as "bots": The first article of this series argued that the latter have a number of serious disadvantages that make them virtually unacceptable. They face problems with deep linking, discoverability and lack of bot-to-bot communication protocols. Intelligent conversational agents offer an intriguing solution to these problems: they don't need new protocols or APIs to communicate with each other and with "master bots" such as Google Assistant. They will communicate in plain English! Bots are the new websites -- every organization will soon have its own bot.

If rumors are true, Microsoft may be one of the few major consumer tech giants that doesn't have a smart, voice-guided speaker in the works... but that doesn't mean it's sitting on its thumbs. In an expansion of recent code discoveries, Windows Central sources claim that Windows 10 is getting a Home Hub feature that will turn supporting PCs into rivals for the Amazon Echo and Google Home. You'd have a shared, login-free desktop that shares family resources like calendars and shopping lists, and a smart home app that would make it easy to control all your connected devices. And as you might surmise, the Cortana voice assistant would play a much, much more important role. Under Home Hub, Cortana would have access to both shared content as well as that of individual users who are signed in.

Amazon's cloud services platform Amazon Web Services recently announced three AI services it said will make it easy for developers to build apps that can understand natural language, turn text into speech, have conversations using voice or text, analyze images and recognize faces, objects and scenes. This, in turn, underscores the increasing importance of AI to consumers, brands and marketers, but also raises some questions about how it will – and should – be developed. Building apps with AI capabilities has been challenging to date because doing so requires access to vast amounts of data and specialized expertise in machine learning and neural networks, Amazon said in a press release. "The combination of better algorithms and broad access to massive amounts of data and cost-effective computing power provided by the cloud is making AI a reality for application developers," added Raju Gulabani, vice president of databases, analytics and AI at AWS, in a statement. "Thousands of machine learning and deep learning experts across Amazon have been developing AI technologies for years to predict what customers might like to read, to drive efficiencies in our fulfillment centers through robotics and computer vision technologies and to give customers our AI-powered virtual assistant, Alexa. Now, we are making the technology underlying these innovations available to any developer…we are excited to see how customers use Amazon Lex, Amazon Polly and Amazon Rekognition to build a new generation of apps that have human-like intelligence and can see, hear, speak and interact with people and their environments."

Machine learning is a cool topic nowadays, people are excited about Google Assistant, Apple Siri, Microsoft Cortana, Amazon Alexa, self-driving cars, robots, even apps like Allo, Uber, Snapchat are using Machine Learning to enhance the experience and of course for smart pieces of stuff. If you are interested in building kick ass apps with intelligence that includes features such as speech recognition, face detection, natural language processing, prediction or anything like that, it's not always an easy option to develop a machine learning system from the ground for any indie developers or small to medium or even for a large team because of it's cost, time (coffee) consumption. But now there are many open source machine learning platforms like Tensorflow, services like Wit.ai, Google Cloud Machine Learning APIs, Microsoft Cognitive Services, IBM Watson are available to the developers to get things done in a very convenient way. Here we will explore various machine learning libraries, APIs, and services. You can build intelligent apps using Tensorflow and even it will work on offline. Here's an Android demo built with inception model for image identification.

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