by Bruce Robertson | October 1, 2015 | Comments Off on How Will Machines Interact With Each Other? Like Humans Do!
Gartner has just published research I collaborated on with my colleagues Magnus (@MagnusRevang) and Eric (@E): Maverick Research: Machines Will Talk to Each Other in English (G00291027). Clients can read it — and anyone attending Gartner Symposium in Orlando (Thursday, 10/8/15, 11:15am Eastern) can hear Magnus and I present this next week.
We took the maverick approach — that something seemingly counter-intuitive will actually happen for very good reasons. We believe that machines will “literally” talk to each other — not via APIs but the same way humans do: in English conversationally.
Why not? Isn’t it as easy to teach machines human languages now as it has been to teach humans machine languages (programming languages, user interfaces)? We already know our natural language conversational interface (NLCI) for H2H interaction — we believe this will also happen M2M.
Why? We already have H2M and M2H cases working. We can already talk to our individually owned machines directly using Siri and other Virtual Personal Assistants. We can also already talk to (or at least text with) business-owned machines directly using Virtual Customer Assistants like Alaska Airlines Ask Jenn (based on IPSoft’s Amelia technology). Why can’t they just start talking to each other?
They will. Many other machines will start talking to humans (is this being “backward compatible”?) and thus be able to be “forward compatible” to talk to each other. In short: M2M NLCIs will grow as a ubiquitous interaction method for machines to talk among themselves.
Oh, and why English? Because that’s the first language for all computers and the people programming them worldwide. You were thinking Mandarin? Emoji? No matter which one — it’s better than speaking API — since these are all new languages to be discovered and learned by machines.
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.