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Showing posts from 2016

Software is due for a bundling event

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This post was also published on TechCrunch. We are approaching a new phase of enterprise software, where every niche of Software-as-a-Service has been filled and cloud companies are being consolidated into larger companies. Markets have a tendency to cycle from bundling to unbundling, and software is due for a bundling event. The cloud, open APIs, next-generation messengers and machine learning are combining to turn the end-user interface to enterprise software into a unified experience. There have been attempts to do this, ranging from portal servers like Portal Software, to “Enterprise 2.0” collaboration software like Jive Software, to communications platforms like Yammer. However, none of these have stuck pervasively because they only solved one slice of the problem, various backends were difficult to integrate, it was hard to work with people outside of the enterprise and there was no machine learning to sift through all the data on users’ behalf. In just the past couple of

Why app development is going micro

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This post was also published on TechCrunch. Application development has long been fraught with peril: Projects become bloated, expensive and never ship. Implementation technologies tend to match the bloat, ranging from Service Oriented Architecture (SOA) to Business Process Management (BPM). As Redpoint’s Tomasz Tunguz recently pointed out, growth in Software-as-a-Service is slowing , and a next generation of applications will weave new workflows across existing applications in novel ways The “micro wave” of services, apps and flows The “micro” trend in application development is focused on delivering bottoms-up, simple solutions to complex problems. Micro services can easily integrate multiple systems, micro apps can present them as easy-to-consume user interfaces and micro flows allow users to simply complete tasks across systems. This “micro wave” triad of services, apps and flows offers a new way to weave existing systems in novel, organic ways in order to deliver solut

Facebook messenger’s ‘Rich Bubbles’ make dumb bots usable

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This post was also published in VentureBeat. In the week since its launch, Facebook Messenger’s bot platform has seen a litany of complaints , with users arguing that it is tedious and unusable. The reality underlying the feedback is that natural language processing isn’t ready for prime time. The techies at Facebook Messenger clearly recognize this fact and have a few tricks up their sleeve that are very old school and reminiscent of the simplified HTML in Facebook’s app platform from almost a decade ago. Chatting with bots just doesn’t work Artificial intelligence experts are indeed pursuing systems that pose as humans and can pass the Turing test, but companies attempting to sell flowers or airline tickets are fast realizing that even specialized bots are incredibly difficult to create. The bot platforms are providing tools like Facebook’s wit.ai and Microsoft’s cognitive services to make creating interactive bots easier, but it is going to take years for these specia

How Google’s AI paved the way for the next generation of bots

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This post was also published in VentureBeat. Bots are fast becoming all the rage in tech, offering users the ability to use a messaging app to type in simple English requests to services like Uber. The user interface is just like texting a friend, and it’s far simpler to enter a message than to download and use a clunky native app. As more bots and bot platforms like Slack emerge, it’s interesting to note that Google has spent almost 20 years perfecting how to respond to a text query. Today’s bots have a lot to learn from Google’s lessons in natural language interpretation, artificial intelligence, and user interface. The quintessential example of a bot is ordering an Uber on Slack, which is relatively straightforward since Slack on mobile knows where you are. However, most current bots quickly devolve into endless back and forth. For example, picking an airline flight via text is about as tedious as using an airline voice response system. Messaging back and forth with a bot

Bits are beating atoms: the Google, Facebook, Apple and Amazon shuffle

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This post was also published in VentureBeat. Google, Apple, Facebook, and Amazon have been dubbed the four horsemen of the tech industry. They are the biggest consumer companies and dominate the discussion through new initiatives such as drones and acquisitions such as Oculus. As our current tech era has evolved, Apple has led the pile with a huge market capitalization, and Facebook was the newcomer with the smallest market cap. In the past few weeks, however, Apple’s phenomenal iPhone sales have finally slowed and Amazon’s endless losses have finally caught up with it . In the meantime, Facebook has blown past Wall Street expectations and Google is continually growing despite its per click revenue dropping. Google and Facebook are weathering the recent tech doldrums better than their peers. It all makes sense from a macro perspective: It’s far easier for Google to get you to do another search and Facebook to get you to look at another photo than it is for Apple to

What Donald Trump’s hammer would do to U.S. tech

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This post was also published in VentureBeat. Over the holidays, I heard Donald Trump giving his stump speech in South Carolina on my car radio. It strikes me that, for all we hear about Trump’s outlandish statements in the press, there’s very little reported about his actual message. Beneath all of his bluster and meandering, Trump is advocating a cogent economic platform targeting an increasingly disenfranchised middle class. It is well understood in economic circles that a combination of globalization, technology, and government policy — trends that most members of the Republican and Democratic parties fully support — has stagnated wage growth in the middle class. Trump and Bernie Sanders are the lone presidential candidates questioning this status quo, which is why they’re both drawing so much interest. Above: Source: Congressional Budget Office, Average Federal Taxes by Income Group, “Average After-Tax Household Income,” June, 2010, http://inequality.org/income-inequali