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Akibot: An Enterprise Twitter Clone Infused with A.I.

Written by Sarah Perez / July 20, 2009 11:30 AM / 9 Comments

What if Twitter understood what you were saying and could then take action on your messages? What if Twitter wasn't just a place to post your random thoughts, but an A.I. bot that actually helped you get your work done? That's the concept behind Akibot, a new enterprise microblogging service. At first glance, Akibot may look very much like your typical Twitter clone, but it does something very different: it combines the collective intelligence provided by microblogging with an artificial intelligence engine that lets the service take action on the messages posted.

When Akibot's developer Marcelo Pham first heard about Twitter, (surprisingly, only a few months ago!) he thought that it sounded like a silly idea. Yet the more he thought about it, the more he thought it began to make sense...just not the way that Twitter had envisioned it. Instead, Marcelo saw microblogging as a "very tiny step towards the machine reading our minds." He then began to work on a concept for an enterprise microblogging platform that would take Twitter to the next logical step: analyzing what users are posting. He then added another function: intelligence. The end result is Akibot, the first "semantic actionable microblogging platform for the enterprise."

Examples of Akibot in Use

To understand how Akibot works, imagine the following scenario: you post a message that reads "There will be a meeting next Wednesday morning at 1 PM regarding the new development project." In other enterprise Twitter clones like Yammer and Present.ly, only those others reading the stream of posts would see the message and would then be able to act on it, if need be. In Akibot, however, the system itself would understand the message and would create an appointment on the team calendar for you. It could even send you and your colleagues a reminder in the form of a text message or email when the meeting time drew near.

Another example goes like this: say a colleague posts a message stating "here is the latest Penske file http://xxxxxxxxx," - pointing to the resource hosted on the company's intranet. A week later, another user could ask "Does anyone know where the latest Penske file is?", and Akibot could then respond with a message pointing to the location previously posted.

Akibot can also function as a time-tracking tool. All you would have to do is post a message letting everyone know when you're beginning to work on a particular project and then post another when you're done.

The microblogging service could even update your CRM system with information about customers and your interactions with them. Again, all you'd have to do is post the information to Akibot.

How Does Akibot Work?

In order for Akibot to do what it does, it seeks out various keywords in a post, but not using simple search or in a "brute force" sort of way. Instead, it looks at the sentence structure as a whole to determine meaning. Akibot's main module is called the "preprocessor" which uses common elements of natural language processing (NLP) combined with two proprietary modules: a "contextual analyzer" and a "context>action" dictionary. The contextual analyzer take the results from the NLP module and finds the context using noun/pronoun/verb structures and then the "context>action" dictionary stores the relevant data and takes action on the item (e.g. it sends a reminder, updates your business software, etc.)

Because Akibot understands natural language - that is, the way people naturally speak - end users posting their messages don't have to use any special syntax in order for Akibot to understand them. However, if you do end up posting something Akibot doesn't understand, it will just ask you to explain and then learns from that explanation so it never has to ask again.

Even Simpler Than Twitter?

There are a few things that Akibot does differently than Twitter. For example, there is no "follow" functionality. By default, everyone follows everyone else, but can "opt-out" from following certain other users if they wish. Since Akibot is meant to be used within a single company, this makes sense. The system is also designed to be uncomplicated so there are no groups, no tabs, no browse functionality, and no search.

Like Twitter, though, Akibot supports private messages, but no special syntax is required here, either. To create one of these types of updates, a user simply clicks on "private" when posting.

Still in Private Beta

The company is still brand-new and there are no exact launch dates yet regarding when it will become publicly available. A lot will depend on the feedback provided by the initial crop of beta testers. Also, if Akibot was to receive funding (they have none now), development could proceed at a faster pace, notes Marcel.

At the moment, the company is considering offering Akibot for free for up to three users and then any additional users would cost $1/per user per month.

If your company wants to join the private beta, you can sign up to be considered on Akibot's homepage under the "Signup" option.


Comments

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  1. You always find very interesting stories!

    Posted by: Mathieu | July 20, 2009 1:08 PM



  2. I am sceptic about NLP methods methods can "understanding tweets". First, tweets are short, contain a lot of slang and abbreviations. Second, NLP methods err way too often to adequate support sensitive tasks like setting appointments create an appointment on the team calendar and like. Remember Wolfram Alpha and Powerset examples.

     Posted by: Maria Grineva Author Profile Page Posted on FriendFeed   | July 20, 2009 1:40 PM



  3. awesome overview thanks sarah :)

    Posted by: mike "glemak" dunn Posted on FriendFeed   | July 20, 2009 2:05 PM



  4. We have an APP (the TrialX Twitter App) that does something similar and it uses NLP. The app enables anybody who wants to find a clinical trial to send a tweet @trialx (followed by CT) and we automatically parse the tweet.
    For example a user may send "@trialX CT i am 55 yr old, female and looking for Multiple Myeloma trials in FL". The App can extract the disease name (multiple myeloma), the persons location (Florida), age and other criteria and send the user a tinyurl to a page on TrialX.com that lists trials matching those parameters. Folks have been using this APP on Twitter for 3-4 months now. More details of the TrialX app. The app can parse thousands of medical conditions.

    We call this type of app a PRIA -personalized and responsive information agent

    Posted by: Sarah | July 20, 2009 2:40 PM



  5. I think people's expectations are understandably high once you introduce the concept of NLP to the interface. I mean, how long have people had to conform to the search query rather than the other way around? There's a lot of pent up demand in the marketplace for this (assuming it works! :>)

    That being said, it will still be a long time until we are able to get to the stage of Apple's Knowledge Navigator, where conversational speech is understood by machines because, its *really* hard to do.

     Posted by: Jeffrey Veffer Author Profile Page | July 20, 2009 2:54 PM



  6. What if the world wide web becomes sentient?

    Posted by: melanie couzner Posted on FriendFeed   | July 20, 2009 6:22 PM



  7. Looks really interesting. It would be great to see microblogging perform some truly useful functions in the workplace. Additionally, I think the NLP component of the technology would work exceptionally well in corporates.

    I think we forget, that when we go to work we can adopt different behaviour and writing styles that mean that our tweets will potentially contain more structure.

    Additionally, I'm sure if a company was to adopt something like akibot everyone would have a bit of a "getting to know akibot" kind of period, but after that it could potentially be the best thing since sliced bread.

    Great idea - and nice to see something that is more than just a twitter clone for the enterprise.

    Posted by: Damon Oehlman | July 20, 2009 7:53 PM



  8. Sarah, thanks a million for the comprehensive review.

    @Maria: this is Twitter for the enterprise, not for the masses, no 'slang' or 'abbreviations' (would you talk with slang or trash to your boss?)

    @Jeffrey: NLP for conversational speech is indeed *hard* to do. Akibot has a reduced context (work, corporate) so "understanding" gets a little bit simpler

    @Melanie: it might... if you look at Akibot's logo, it has a sentient shape ;)

    @Damon: thank you for the clarification and thank you for the encouraging words


    Thanks everybody for all the feedback, they're really helpful


    Marcelo
    Akibot Development Team

    Posted by: Marcelo | July 20, 2009 8:16 PM



  9. I'm seeing how this can be done WITHIN Twitter.

    Just sent an @saruhAI message to a conversational agent

    http://twitter.com/saruhAI

    Which seems to range from pre-scripted conversation to entirely AI driven conversation. I even got responses that included Wikipedia links and used it as a Tip Calculator (apparently, it knows math).

    The thing is you have to @saruhAI to start the conversation, then it's more like IM where I got replies in about a minute.

    There is also a private account the people behind this have that seems to have more features...can't get in to find out though?

    Posted by: sam | August 9, 2009 3:07 PM



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