Microsoft AI vs Google AI vs Amazon AI vs Others

1. Why companies want to be a part of AI revolution

The largest companies in tech, especially Facebook, Microsoft, Google, and Amazon, spent their year hyping up something a little more abstract: their ongoing quests to build a so-called “general artificial intelligence,” and all the extra smarts they’re adding to the product while they’re at it.

Google publically showed off its AI capabilities with an appointment setting call by its AI. Facebook and its self-learning AI have been the talk of the town recently, and Microsoft has released a huge amount of data to help train virtual assistants like Siri and Cortana. Even Amazon has the ever-notorious Alexa!

If you ask the CEOs of these companies, it’s all about building new features and functions to their apps – from facial recognition in Google Photos and instantly translating comments on Facebook, to more subtle things, like using AI to intelligently route internet traffic and make it possible to virtually “teleport” with Microsoft HoloLens.  There are some very practical reasons why Microsoft, Amazon, Google, Facebook, and everyone else is talking about artificial intelligence right here, right now, in just the past several months.

 

 

Google CEO Sundar Pichai, a very vocal fan of AI, has said that he envisions a world in which every user gets their own personal Google. Facebook and Microsoft, as well, have made a huge point of showing how artificial intelligence is improving their own apps, enabling things (like helping you design better PowerPoint presentations) that would never have been otherwise possible. It all points to a brighter future, where all of our photos, documents, messages, and, in general, our lives, are more organized, more intelligent, and overall better, even as we increase our reliance on software for everything from productivity to shopping to getting around.

There’s just one problem: “You can’t hire enough people in the world who are machine learning experts,” Joaquin Quiñonero Candela, the head of Facebook’s Applied Machine Learning (AML) research division, put it to Business Insider.

Silicon Valley firms are already insanely competitive for programmers; and top-tier AI experts are an even hotter commodity, making them ripe targets for poaching from one tech giant to another.

All of this hype, and all of these spotlights on artificial intelligence, then, is less about pushing the concept to consumers, and more about getting developers excited. It’s not just developers working today; it’s college students and self-taught individuals. It’s in Facebook’s, Google’s, and everyone else’s best interest to get these folks interested in AI – especially since, thanks in no small part to pop culture, AI has a reputation as something that’s practically magic, or at least obscenely difficult to learn.

In reality, AI is just applied math and statistics. And you can learn math. But if the next generation of coders is intimidated by the notion of AI, that’s a problem for Google, Facebook and all the other tech giants planning their future on AI.

2. Current products by these companies

Siri and Alexa have now become household names in America, Xiaoice has been a digital friend to million in China since 2014, and the term “chatbot” has been a buzzword for nearly two years.

With all the hype about chatbots for consumers, we set out to discover the potential business implications of conversational interfaces or “chatbots.” By analyzing the chatbot plans at the “big four” technology firms (Microsoft, Google, Facebook, Amazon), we set out to answer the following questions:

• What are the biggest announcements and initiatives of these firms for conversational interfaces?
• What does the state of the chatbot world today mean for business leaders across industries?
• Why are these companies betting on this technology?

We begin with some context on the development of chatbots and why they’ve become popular, followed by a chatbot overview of the initiatives of Facebook, Microsoft, and Google, respectively. In conclusion, we’ll tie together the trends and patterns we picked up across all four tech giants, and shed some light on what their progress and vision might mean for other businesses.

We’ll begin by laying some groundwork as to why chatbots have become an important interface for these tech giants:

 

Drivers of Chatbot Adoption

Companies are investing in chatbots since the technology has started to reach a usable level of maturity and to follow their customers.

One big reason more corporations are using these systems is that they feel many of the technological limitations will soon be overcome. As anyone who has recently interacted with a chatbot or digital assistant knows, the experience can sometimes be frustrating. Chatbots often stumble over anything beyond basic requests.

To build a truly human-like conversational experience, the AI algorithms powering a chatbot must process a massive amount of data and interactions. Tech leaders feel they have gotten to the point where it’s possible to start producing, gathering, and processing that trove of data. Every current use of AI-powered conversational interfaces, such as Facebook Messenger bots, Xiaoice, Alexa, Siri, Cortana, etc., is creating the data needed to make systems like these smarter. From the beginning, Microsoft designed Cortana to get smarter with every use, learning both about the individual consumer’s want and people as a whole with each interaction.

The other reason is that companies are following the customers. According to a BI Intelligence analysis, in 2015, the number of monthly active users on messaging apps quickly surpassed the number of active social network users. WhatsApp reached the one billion user mark, meaning roughly one in seven people on the planet use the Facebook-owned messaging platform. Their Chinese competitor, WeChat, claims to have 768 million daily logged in way back in 2016. More importantly, half of their users use it for at least 90 minutes a day. The number of WeChat messages sent increased by 67% from 2015 to 2016.

Messaging has become a major way people interact with their smartphones. Companies want chatbots to literally be a part of the conservation. If you are talking with your friends about travel plans or going to a movie, a chatbot can directly enter the conversation to provide these services. Oracle recently surveyed major companies around the world and found 80 percent plan to use chatbots for customer interactions by 2020 and 36 percent have already started implementing them.

Facebook ‘s Chatbot Efforts

Via both its Messenger platform and its ownership of WhatsApp, Facebook is the dominant player in messaging services, which is why they have invested so heavily in communication bots. Facebook is working to make it easy for companies to use its bot technology to contact customers within its messaging services. Instead of using different apps, people could, for example, order an Uber directly from Messenger. Facebook currently has 1.2 billion people using Messenger and over 100,000 monthly active bots.

Facebook has also opened up its Messenger service to developers and launched its bot store in early 2016, and has been constantly updating it for the past year. One advancement is allowing multiple people to communicate with a bot in a single conversation. A group of friends could, for example, be discussing evening plans and seamlessly order movie tickets.

Zuckerberg has enthusiastically pursued the chatbot market, putting it to be in the strongest position to become the ubiquitous chat interface of everyday consumers. It’s not clear whether Facebook’s 1 billion daily users will change their behavior from “likes” and posts to shopping and booking flights through chat, but the company is certainly poised to test that hypothesis. Below, Zuckerberg shares a bit of his vision for Facebook Messenger, as well as some novel use cases:

Several company bots have very successfully convinced users to get information or make purchases using a conversational interface. For example, Sephora’s bot allows people to tell them what services to book appointments. It saw an 11 percent increase in bookings via the bot compared to other avenues.

What Facebook sees as the future is “M,” their AI-powered virtual assistant. A small number of beta testers have access to full-fledged M, which is backed by humans. When a question is too difficult for the AI bot, it is referred to a human backup to address. Each time a human needs to step in, the program learns from what the human does. Once the AI has learned to handle a feature sufficiently in testing, it could be rolled out to over a billion people using Facebook. The launched personal assistant M can scan your conversation for certain prompts, like the indication you owe someone money or are planning to go somewhere, and can suggest ways to transfer money or hail a rideshare service directly in the conversation. Messenger now allows chat extensions which allows users to contextually bring bots into their conversation. People can use bots to directly split bills, share music, or order food within their conversation.

The engineers behind the program aren’t sure if it will take three years or ten, but their long-term vision is to create a truly human-like AI assistant. Unlike current bots that people primarily use for the same simple requests over and over again, this would be an AI that could handle almost any request — one people will rely on for everything.

Microsoft’s Chatbot Efforts

Microsoft CEO Satya Nadella thinks chat-based interfaces will replace apps as the primary way people use the internet and is investing big on this vision of the future. Stating last year, “Bots are like new applications, and digital assistants are meta apps or like the new browsers.  And intelligence is infused into all of your interactions. That’s the rich platform that we have.”

Nadella has also stated that Conversation as a Platform will “fundamentally revolutionize how computing is experienced by everybody,” in a paradigm shift comparable to the development of the web browser. Microsoft sees Conversation as a Platform as its chance to regain an edge, and is focusing resources accordingly. The idea is that instead of a person opening an app or program and needing to enter in their information in a very specific way to get the program to do what they want, a person can just use basic language to tell an AI powered machine what you want, and it will all be taken care of.

Microsoft may be able to parlay its broad enterprise adoption to become the “bot platform” for companies who already use their other tools.

Where Microsoft feels it has an advantage is in AI technology and in creating chatbots with conversational capabilities. Microsoft prides itself by releasing the first true platform for text-based chat interfaces and an early start on building bots that resonate with people on an emotional level. It introduced the chatbot Xiaoice in China in 2014, and the chatbot Rinna in Japan in 2015. They have been successful, not just as tools for people getting basic information, but also as entities people enjoy interacting with on an emotional level. Millions of people use these two chatbots for emotional support, to the extent that 25 percent of Xiaoice users have told the bot, “I love you.”

In addition to launching their own chatbots and integrating Cortana  into most of their products, Microsoft launched their Bot Framework in early 2016 — a set of tools to help developers produce their own chatbots. So far, over 130,000 developers have registered with the Bot Framework.

One such bot is UniBot, which allows university students to manage their courses and pay the university. It is targeted at non-English speaking students who can struggle to navigate university websites in English. It can function in 60 different languages.

Amazon’s Chatbot Efforts

Following Microsoft and Facebook’s lead, Amazon made its conservation interface tool, Amazon Lex, generally available to companies this past April. Using the same technology behind Amazon’s Alexa, companies can build text or voice bots. Developers can use it to create conversational apps or chatbots for chat services, internet of things devices, or any messaging service.

In his 2017 shareholder letter, Jeff Bezos highlighted Amazon’s focus on bringing AI to companies via Lex and told investors to “Watch this space. Much more to come.”

With all of the attention on personal assistants for shopping , it’s interesting to note that Amazon doesn’t seem to have a strong push for it’s equivalent of Facebook’s “M” for Facebook Messenger.

AWS Chatbot Challenge

Amazon’s AWS Chatbot Challenge isn’t geared just toward eCommerce.

Amazon did launch its AWS Chatbot Challenge, but it’s interesting to note that the challenge (which offers winners a total prize pool of $10,000 and complimentary tickets to AWS re:Invent in Las Vegas) isn’t focused entirely on eCommerce – which is what one might expect.

It seems that Amazon has put its chips on Echo and voice interfaces instead of chat interfaces. With over 10 million Echo devices sold, we can’t blame Amazon for aiming to keep up their momentum and focus on the area where their return could be strongest.

Google’s Chatbot Efforts

Google has been slower in entering the chatbot space. It only launched its smart instant messaging app, Google Allo, in late 2016. Allo integrates Google Assistant, which evolved from Google Now. Allo allows people to chat directly with Google Assistant to get basic questions answered. Google Assistant can suggest restaurants or movies to watch directly within conversation between people taking place at Allo.

One way Google is trying to improve its stand in the chatbot space is with their recent launch of their Chatbase. It is an analytic tool to help other companies improve their own chatbots, which are currently being used on places like Facebook Messenger. While it will help these companies improve their chatbots it should also help Google gather important information about the field.

In the home-based conversational device world, Google Assistant is their answer to Amazon’s Lex. Allowing developers to build on top of Google’s existing NLP infrastructure, Google likely hopes to fight for it’s share of the home-based conversational device business. They recent showcase of experimental call answering by Google Assistant firmly placed it as the top AI powered assistant out there, it was unreal watching the events unfold on the stage.

Thanks to its massive user base on Gmail, G Suite, Google Cal, and others, Google has an enormous opportunity to implement conversational technologies into its communications tools. Smart Reply is a Google service that allows Gmail users to automate all or part of their email replies based on past responses and an analysis of the sender. Companies like X.ai have tried to make a name for themselves by handling a small chunk of the “appointment booking” workflow, but there’s a strong chance that Google may eventually crack a wide space of monotonous work communication.

The only other company with the potential to do the same would be Microsoft, whose Outlook and Office suites still dominate in terms of near-ubiquitous enterprise use.

A number of other trends seemed to garner enthusiasm, but the tech giants weren’t as confident about. These trends include:

Companies like Microsoft, Amazon and Facebook are betting heavily that when AI chatbots and personal assistants get smart enough they will change the way people use technology. The current way people use smartphones, like accessing dozens of apps to take dozens of different actions, may soon become anachronistic. They envision a more conversational and natural set of interactions with machines. You just ask and it happens. Based on Facebook’s experiment with an AI assistant that has human backup, it seems that if people have access to a really great assistant program people will use it more frequently.

There is no widely held acceptance criteria for when the technology will reach this envisioned tipping point. Even the top engineers in the field don’t know if the technology will take three years or over a decade to reach that point.

Uncertainty about chatbots

It’s important to note that chatbots are still bumbling their way through the business landscape, trying to find applications that can consistently drive real ROI for businesses. Personal assistants, shopping assistants and customer service applications have tremendous promise, but not much by way of currently successful use cases.

Chatbots may not need to be on the near-term radar of many companies. Any long-term strategic planning should certainly consider voice and text conversation interfaces – but let’s be honest: If Google, Facebook, Microsoft, and Amazon haven’t nailed many succinct use cases with strong ROI, most other businesses probably won’t either. Business leaders at other companies will have the opportunity to let the “big 4” stumble along to find the use cases that prove profitable – at which point other industries can model what works without having to spend tens of millions on “novel” or “toy” applications.

3. Research into AI and the efforts being made

Artificial intelligence researchers are making tangible progress on difficult problems, and people are starting to talk seriously about AI again.  In the mean time, our increasingly data-driven world has kicked off an arms race between companies seeking to monetize the new intelligence, particularly in the mobile space.

The acquisitions of AI start-ups are getting feisty, as well. The price tags are often not a priority for these deals. Don Harrison, the Head of Corporate Development at Google, for instance, stated: “We’re definitely AI-first. We pay attention to valuation but don’t necessarily worry about it.” Mostly, because acquirers see these start-ups as a talent and technology source rather than a business.

Brandon Purcell, a senior analyst at Forrester says: “AI will precipitate a new data gold rush, marked by data-motivated acquisitions. Companies that acquire data assets around a specific use-case will win. The resulting barrier to entry will be insurmountable.”

Now that we know the major tech titans are getting serious about AI to shape the future, let’s analyse the most active acquirers in the space to obtain a deep grasp that goes beyond the hype. Here is a splendid timeline chart created by CB Insights, providing a glimpse into the mergers and acquisitions of AI start-ups by the top acquirers:

 

Grabbing the talent

Google has acquired more than 11 private AI startups. The acquisition of DeepMind, with a price tag estimated at $660 million, marked one of the largest acquisitions among the M&A deals in the AI area. DeepMind’s specific focus on improvements in general AI research has helped Google apply the research to its business process to beef up its AI capabilities.  Another main drive behind these acquisitions was developing Google’s Home to have a leg up on the competition against the virtual personal assistant market leader, Amazon’s Alexa. To that point, the tech behemoth acquired three companies specialized in image recognition; DNNResearch which is focused on deep learning, image search, and facial recognition; Moodstocks which is specialized in image recognition for smartphones; Vision Factory which is used for improving accuracy and speed in object and text recognition. Many other acquired technologies have also been used for leveraging Google’s search functions.

Since the introduction of Siri, we have consistently seen Apple in the news making a significant number of acquisition and product enhancements to leverage its AI capabilities.

To make Siri better understand human speech and give it a more competitive edge, Apple acquired VocalIQ, and it bought Perceptio to protect consumer data by keeping data local to each device instead of uploading user data to the cloud. Last year, it snapped up Emotient as its technology can read facial expressions to determine a person’s mood. To process the data from iPhones in real time, Apple also bought Tuplejump, who are focused on applying deep learning to large data sets. Of all its recent acquisitions, Turi is arguably the most interesting one as with that deal, Apple allowed developers to build apps through deep learning that could be scaled for many users. The idea is similar to Google’s TensorFlow, the open-source machine-learning library.

We may see more acquisitions, especially related to facial recognition technology, in the upcoming months as the company has been significantly utilizing the technology in the latest releases of its iOS.

To allow users to add various filters in pictures or real-time videos and sharing them on Facebook, the company snatched up Belarus-based Masquerade Technologies specialized in facial recognition technology. Facebook also recently acquired Switzerland-based Zurich Eye, a computer vision startup. Prior to these two acquisitions, Facebook also bought Wit.ai, who are focused on creating an API for building voice-activated interfaces. The Wit.ai product lets developers add a few lines of code to instantly build in speech recognition and voice control so, with the deal, Facebook aimed at leveraging voice-to-text input for Messenger, improving Facebook’s understanding of the semantic meaning of the voice, and creating a Facebook app users can navigate through speech.

Microsoft acquired SwiftKey, which makes predictive keyboard software that learns users’ typing habits and adapts accordingly, for $250 million. This acquisition was followed by the acquisition of a messaging app developer, Wand Labs in June. The deal was part of Microsoft’s strategy for Conversation as a Platform, which Satya Nadella introduced at the Build 2016 conference in March. Lastly, in August, the company also signed an agreement to acquire Genee, an artificial-intelligence-powered scheduling service in an effort to integrate its smart assistant Cortana with Office 365 apps.

 

The present day:

AI has crept in to our pockets via our ever ubiquitous mobile phones. iPhone, Google Pixel are the two big brands which come to mind. Google has flaunted its AI tech in its phones and has delivered some great results in the form of a single camera, capable of shooting better images that multi camera phones. Apple has slowly started expanding its AI focus through Core ML. Smart home devices come integrated with AI assistants. Read Google Assistant, Alexa etc. Looking at the reach Google has gained through its mobile operating system, this author is convinced that only they possess the required touch it would take to actually make AI a part of our everyday lives.