I got sucked into a month long project applying machine learning filters to video over the holidays. The project began with me doing the research on the economics behind Algorithmia's machine learning services, specifically the DeepFilter algorithm in their catalog. My algorithmic rotoscope work applying Algorithmia's deep filters to images and drone videos has given me a hands-on view of Algorithmia's approach to algorithms and APIs, as well as the opportunity to think pretty deeply about the economics of all of this. I think Algorithmia's vision of all of this has a lot of potential for not just image filters, but any sort of algorithmic and machine learning API. Using Algorithmia is pretty straightforward. With their API or CLI, you can make calls to a variety of algorithms in their catalog (in this case, their DeepFilter solution).

Chatbots are on the verge of becoming the most useful technology in every industry. Their ability to offer assistance and create a bond with different elements or factors that determine the success of a business, including advanced relations with human beings, is simply incredible. The chatbots are increasingly being used by different brands, retaining and maintaining customer relationships and to some extent customer loyalty. Their capability has not yet been fully exploited.

For years, those of us in the technology sectors have been building integrations between disparate systems. In fact, enterprise organizations often have specific resources dedicated toward building and maintaining integrations between mission critical systems. According to dictionary.com, the word integrate is defined as a verb meaning "to bring together or incorporate (parts) into a whole." For decades, technologists have been manually creating integrations between systems whose interfaces have been continuously changing. Those of us who were lucky got the opportunity to create an integration between a mainframe and a front-line database, thus ensuring that fewer updates to the integration were necessary.

Earlier this year I wrote about an interesting new start-up that's using machine learning to provide a more intuitive interface between customers and their banks. The platform utilizes machine learning to classify the transactions we make each month, and then provide intelligent insights into the patterns it observes. For instance, it might tell us how much we're spending at a particular coffee shop, or whether we might be able to save money on our utility bills. It seems part of an interesting trend towards more automated banking. Chatbots have been a hot topic in the news in recent months, and an Indian startup are using them to fully staff their mobile banking service.