Big data

Intel and Microsoft’s latest investment binge shows AI land grab is intensifying

Intel and Microsoft have been on something of an artificial intelligence (AI) investment binge of late, with the chip and software giants announcing a slew of deals this week via their respective VC arms — Intel Capital and Microsoft Ventures.

Perhaps the most notable of these was Element AI, which raised a gargantuan $102 million in what is one of the largest series A rounds in recent times. The Montreal-based startup, which helps connect companies with machine learning experts, drew in some other interesting investors besides Intel and Microsoft, including rival chipmaker Nvidia.

The Element AI deal followed just a day after Intel and Microsoft joined forces for a $15 million investment into CognitiveScale, a Texas-based startup that uses AI to harness big data and deliver insights and recommendations. The very same day, Intel participated in a $16 million round into California-based robotic vision startup Aeye, while on Monday Microsoft got involved in a $20 million funding round into CrowdFlower, a platform that meshes machines with human input to ensure data science teams have access to properly tagged, clean data. Microsoft also invested in in CrowdFlower last year.

The duo have been investing in AI-related startups all year, too.

Back in January, Intel Capital joined a $14 million funding round into Mighty AI, a…

Your most effective employee could be a chatbot

Image Credit: Shutterstock.com / charles taylor

Advances in artificial intelligence mean chatbots can automate more customer interactions than ever before. According to analyst firm Gartner, the usage of chatbots will triple through 2019 as enterprises seek to increase customer satisfaction and reduce operating costs. But not all chatbots are equal.

For businesses, chatbots (sometimes called “virtual agents” or “virtual customer assistants”) need to be smart in order to be effective. Intelligent chatbots integrate with enterprise systems and the related rules; they can parse big data and use artificial intelligence to help customers resolve issues or perform transactions, such as paying a bill or extending a subscription.

Some chatbots interact with customers to resolve issues, conduct transactions, and answer questions. The fact that these chatbots are bounded — in other words, operating within a certain context such as mortgages, utilities, or wireless — ensures they can better support the conversation.

Because of advances in AI, businesses can artificially replicate the effectiveness of their best agents, reducing customer frustration and wait times. However, it is essential to remember chatbots are still an outward facing extension of the brand, and even though they are machines and not human, customer expectations around their performance will only heighten as the technology becomes commonplace.

Chatbot deployments should be approached in a similar way as any other frontline employee.

Chatbots today and tomorrow

Intelligent chatbots can be deployed on nearly any interface: web, mobile, social, messaging app, voice response, and SMS. They operate in real time and can even predict what a customer is trying to do, offering specific help when they detect that a customer may need assistance. For example, if a customer has a bank mortgage, a chatbot can offer assistance with an understanding of the customer’s chosen product and history in mind. As we look to the future, chatbots will be deployed through augmented reality (AR), virtual reality (VR), and other emerging technologies.

Over time, chatbots will be the primary point of customer interaction. This increased self-service will mean reduced call and email volume in traditional support channels. Recently, a leading global airline created an avatar to personify their chatbot. The chatbot serves as an automated concierge, providing customers with instant, accurate answers to their questions about flight status and baggage rules. The chatbot has helped the airline reduce call and chat volume by 40 percent.

One of Canada’s largest banks introduced an intelligent…

How data analytics will help us understand chatbots

Bots can augment human interaction, create greater business efficiencies, and remove friction from customer interactions.

It’s also a market that’s attracting impressive investment dollars, with 180 bot companies raising $24 billion in funding to date. Industry leaders from IBM to Facebook are making big efforts to take advantage of this trend, spending significant resources encouraging developers to create new bots that enable more personalized customer interactions. In March of 2016, Cisco announced the Spark Innovation Fund, a $150 million investment in bots and developers who want to make new products for Cisco endpoints in offices around the world.

Some of the most obvious uses for bots revolve around communication, customer service, and ecommerce. Chatbots are at the center of the way people communicate today, with over 2.5 billion people worldwide using a messaging platform like WhatsApp, Facebook Messenger, or Telegram. Twitter recently rolled out a bot-like feature within its DM service to enable brands to interact more frequently with customers, with the goal of ultimately improving the customer experience. Facebook is testing a service to enable users to make payments on Facebook Messenger that are facilitated via the use of bots built on its platform. Gaming companies are using bots to help ward off trolls that might interfere with the natural progression of the game.

All this is happening while we create almost unfathomable amounts of data — data that is expected to reach 35 zettabytes by 2020. So how can companies outside ecommerce take advantage of bots to automate these new data sets and deliver smarter, faster analytics access in the process? Let’s take a look:

The concept of human to machine interaction via natural language processing can drive immediate analytics responses, rather than waiting on human analysis…

How ambient computing will help chatbots evolve

The smart home is stupid compared to what it could be.

In order for the Internet of Things (IoT) to live up to its massive global potential, the smart home needs one key thing: consciousness. Rather than optimizing the “things” — the devices that are facilitating the IoT — IoT providers should understand that the real value of IoT will come from the services enabled by the data from connected devices, a 24/7 consciousness that captures and learns from data, not the devices themselves.

We’re currently experiencing a shift in computing, fueled by bots and ambient computing, that is poised to accelerate innovation in IoT. Bots leverage the intelligence of ambient computing to transform idle data into value-added services and give the smart home consciousness. Predictive analytics help to understand a person’s lifestyle, detect patterns, and anticipate problems. This provides developers with a massive opportunity to design services that aren’t possible with a mobile phone or desktop computer. The future of innovation in IoT today resides in the hands of developers.

What makes bot development different

With history as our compass, it’s clear that we are on the cusp of a huge new economy and a paradigm shift in computing — something that happens about every 10 years. You may recall that mainframe computing was the norm in the 1970s until desktop computing changed everything in the 1980s. The 1990s delivered a more powerful personal computer and increased mobility until the next decade, which brought inventive capabilities in mobile and remote computing. We’re witnessing another shift in computing in the 2010s. This change is not just about cloud computing, but the acceleration of the IoT through bots.

So, what is the key factor that signals these shifts? Developers drove them all. The emergence of Apple’s mobile supercomputer — the iPhone — gave developers an opportunity for supercharged innovation by allowing them to create apps for smartphones.

Today, though, most developers would agree that app development has hit a wall and that momentum is shifting toward bots. Bots are now exploding faster than apps did. According to Citi Research, comparing early market smartphone app development to bot development in its first year, we see three times more bot developers and solutions than we did with apps. The number of bot developers in the past six months, 36,000, is triple that of the first year of app developers.

Companies like Facebook are accelerating this by making it very easy to develop and deploy bots. Bot development is comparatively easy, and it’s designed to deliver recurring revenue streams. With apps, people pay a one-time fee of 99 cents, whereas with bots, developers can make 99 cents as a recurring fee every month. Bots are a promising way for developers to begin making money again by enabling services that don’t require a phone screen like apps do.

So, what’s a bot?

A bot enables micro-services that incorporate deep learning algorithms and the benefits of artificial intelligence while operating in the background of your life. Think of a bot as a small computer program that’s listening to the real-time data from your devices. It’s trying to figure out what to do with that data. It can learn, react, and communicate with you.

While bots became a part of our vernacular this year because of the likes of Facebook Messenger bots, here we’re talking about much more. Messaging bots won’t be what drives big revenue. The bots with huge potential are those that are going to deliver services that get deeper into people’s lives than simple screen interaction. In fact, the next wave of consumer solutions will be comprised of products that don’t even have a screen. Intelligence is beginning to surround us in everyday objects, many having no interface at all — except for a voice prompt.

The interface for bots is the spoken conversation. Connected outcomes…

Why the AI hype cycle won’t end anytime soon

By now, we’ve all heard the hype around AI. According to Google Trends, only 5 percent of the U.S. population searched for information about artificial intelligence in 2012. In 2017, that figure has jumped to an estimated 60 percent. Unlike some other fads that have swept through the tech industry, however, the hype around AI is justified for a number of reasons. AI development will continue to exponentially infiltrate our day-to-day lives.

Unlike in the early days of AI, there are now many useful and powerful frameworks — like TensorFlow and Caffe — that enable easy implementation of AI technologies and remove much of the need for engineers to build code from scratch. These frameworks eliminate considerable time and resources and will continue to make AI more widespread and available to companies of all sizes and across industries.

There are also many pre-trained neural networks that are available for common use in different domains, like content, image, and voice recognition. These networks are also greatly contributing to the growth of entrepreneurial endeavors surrounding AI by allowing the use of pre-prepared neural network models which can be trained on an exclusive dataset. Some of the most trailblazing ones include Yolo, fasText, and Deep Speech 2. These initiatives are allowing AI to flourish at an exponential rate.

Increasingly affordable AI maintenance and the increased speed of calculations thanks to GPU are significant factors in the unbridled growth of AI. Maintenance is becoming more and more inexpensive as cloud providers like Amazon continue to mark down the costs of their services. The efficiency…