Have you noticed that more and more websites now seem to have someone just waiting there to answer your questions? It’s a familiar chat interface with the first line saying “Hi There, I’m Amy. Let me know if I can answer any questions” and there’s a text box you can type a response into. In the old days, that wasn’t an actual person. As soon as you engaged with the form, then a human took over and chatted with you. Going forward though, any interactions you have in which you type text to speak to a company will be through the use of a chatbot built by one of the many chatbot startups popping up all over the place.

We wrote before about “The Myth of the Clever AI Chatbot” and how our experience with a conversational chatbot was about as exciting as an MBA alumni networking event. What we failed to note in that article was how important context is. Once you have context, like a visitor to your website that sells shoes, you can then start to train artificial intelligence (AI) algorithms more effectively. That’s why just recently, India’s 3rd largest IT company, WiPro, recently deployed 1,800 chatbots that were able to replace 12,000 workers. After numerous interactions with “John in Mumbai” types, we can assure you those chatbots will actually think outside the box more than the humans they’re replacing (see Exhibit A).

A recent article from IBM titled “How conversation (with context) will usher in the AI future” revealed a consensus among 30 of the most knowledgeable AI scientists and thought leaders, that human-computer interaction or HCI will be the primary driver behind the adoption of AI:

The consensus is that within three to five years, advances in AI will make the conversational capabilities of computers vastly more sophisticated, paving the way for a sea change in computing. And the key lies in helping machines master one critical element for effective conversation—context.

Those smart people over at CB Insights put together a list of 100 Startups Using Artificial Intelligence to Transform Industries and 9 startups in that list fell under under “Conversational AI/Bots”:

Here’s how much funding each of these startups has taken in along with a brief description of what they do:

Startup Funding (Millions) Description Mobvoi $71.6 Leading Chinese voice recognition solution used by Wechat. So impressive even Google invested. x.ai $34 Created a specialized AI personal assistant named Amy (or Andrew) who coordinates all of your emails for you. MindMeld $15.4 Developed Deep-Domain Conversational AI. Chat and voice assistants can demonstrate deep understanding of any knowledge domain. Semantic Machines $12.38 Shifting from understanding commands to understanding conversations. Maluuba $11 Developed NLP technology that is deployed across 50 million devices. Besting Facebook, Google, and IBM in computer reading comprehension. Snips.ai $6.3 Uses AI algorithms to give your device context awareness acting as a kind of personal memory. Clara Labs (clara) $5 Offers similar services as x.ai but at much higher prices. KITT.AI Undisclose Conversational understanding as a service. Helps enterprises build better chatbots. Backed by Amazon. AUTOMAT Undisclosed AI-driven conversational user interface technology. Investors include O’Reilly AlphaTech Ventures (OATV) and Slack.

Now before we dig into each of these companies, please note that there have already been several acquisitions which show us just how eager big corporates are to get their hands on this chatbot stuff.

The first acquisition was San Francisco startup MindMeld which was founded 6 years ago and had taken in $15.4 million. The startup was running on an “Intel inside” business model that enabled any firm to integrate an AI powered conversational interface into their business processes. Just last month, Mindmeld was acquired by Cisco (NASDAQ:CSCO) for $125 million.

The second acquisition was Maluuba which was acquired by Microsoft (NASDAQ:MSFT) earlier this year for an undisclosed amount. This Canadian startup had taken in $8.2 million in funding and first crossed our path in late 2016 when we wrote about “Using Deep Learning to Teach Computers How to Learn“. Maluuba’s natural language understanding technology can already be found on over 50 million devices around the globe.

These acquisitions are a pretty good omen for the remaining 7 chatbot startups we’re going to talk about now.

Mobvoi

A few months ago we wrote about The Top 10 Artificial Intelligence Startups in China and Mobvoi made that list. Mobvoi was founded by a couple of Chinese entrepreneurs who used to work at Google in Silicon Valley but then went back to Beijing and created an AI startup where 60% of the employees are engineers. We were particularly attracted to the beautiful smart watch they developed at a $200 price point that understands Chinese and probably some Engrish as well:

Just 3 days after our last article, Mobvoi took in $180 million in funding led by Volkswagen so now they’ve taken in $251 million total and are just shy of being a full fledged unicorn ($1 billion valuation). Mobvoi isn’t just about consumer gadgets since their core technology includes voice recognition, semantic analysis for chatbots, text-to-speech, and other such technology applications like a mobile voice search service called Chumenwenwen.

x.ai

x.ai first came across our radar in an article we wrote about How AI Personal Assistants Will Fill Secretarial Duties. This New York City startup has taken in $34 million in funding to develop a “smart personal assistant”. Remember when people used to say things like “call my secretary and have her setup a meeting for next week?” Now, you just cc: [email protected] and she will handle it for you. There’s no app and nothing to download since your only interaction with the chatbot is by emailing it. Now that’s a pretty clever way of getting people to use a chatbot.

Semantic Machines

Founded in 2014, Massachusetts startup Semantic Machines has taken in $12.38 million in a single round of funding. This startup is developing a new platform that is language-independent by shifting conversation from understanding commands to understanding conversations (even tonal languages like Mandarin). Semantic Machines has some serious talent on board including co-founder Larry Gillick, a former Chief Scientist for Siri at Apple and Stanford AI Professor Percy Liang. Talent is everything in this game, and Semantic Machines claims to have “one of the best language-focused AI research groups in the world including 18 top-ranked PhDs”.

Snips.ai

We first came across this startup when we wrote about “Context Aware Computing From Snips.ai” but since then, they’ve opened up a whole lot more about their product offering. The Snips platform can be used to deploy on-device chat capabilities across any type of connected device. “Whether you’re building a lightbulb, thermostat, or speaker – you can add a voice assistant in just a few steps“. Here’s how they stack up to some of the competing technologies that let you do the same:

They really appear to be making a play for privacy-conscious consumers with a tagline that says “Snips is an AI company that does not collect any user data“.

Clara Labs

Founded in 2014, Clara Labs took in $5 million in seed funding to develop “a virtual employee that schedules your meetings”. If that sounds familiar then that’s because we just talked about an identical offering from x.ai. Of course, startups just love it when you say their offering is “just like their competitors” so we dug in a bit. Clara is actually backed 24/7 by real human assistants if that makes you feel any better, and you can brand the email you cc: with your own domain name which is a pretty key feature to have. Of course there’s no free lunch and the prices reflect that with subscriptions ranging from $99 to $400 a month. Note that at a $400 price point you can get an actual human full-time virtual assistant but then you won’t be able to tell your CTO that you’re “using chatbot technology”.

KITT.AI

Founded in 2014, Seattle-based startup KITT.AI has taken in an undisclosed amount of funding from Amazon Alexa Fund. KITT.AI wants you to go with the flow using their service platform called Chatflow to create chatbots like Moviebot, Yelpbot, Lyftbot, and Uberbot. In a nutshell, the startup provides you with tools to create chatbots that don’t require you to have mad programming skills:

You can also interface with any device via voice in your home using a free hotword detection engine from KITT.AI which runs on your smartphone. That tool might be appealing to those people who worry that their “smart home devices” might be listening to a bit more than they should be.

Automat.ai

Founded in 2016, Automat.ai, is a Canadian startup that has taken in an undisclosed, single round of funding from investors that include media publisher O’Reilly and popular startup Slack. Automat is making it easier for anyone to build a bot that uses artificial intelligence and human expertise to enable “business conversations at scale”. They really aren’t saying much else but if you’d like to “implement Conversational Marketing over Facebook Messenger and other messaging platforms” then you can sign up for Automat’s private beta and see what it’s all about for yourself.

Actually, Chatbots Are Going Away

There was a good article by Venture Beat last week which talked about how the term “chatbot” will soon go away and people will just expect to use speech to engage with technology (except puh-leeze don’t do that isht while riding on public transport):

Perhaps the most important evolution we’ll see in five years is that bots disappear entirely. Conversational intelligence will remain — and it will be ubiquitous on the web. But the notion of a bot will begin to recede.

It is truly amazing that with all the sophisticated technology and science behind AI and the funding pouring in from investors, the pervasiveness of AI will be decided by its capacity for deep and relevant conversations with humans. An article titled “Gartner’s Top 10 Strategic Technology Trends for 2017“, declared that conversational systems ‘will shift from a model where people adapt to computers to one where the computer “hears” and adapts to a person’s desired outcome‘. Did you read out recent article on the “Internet of Sound“? Maybe that shift has already begun.

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