IT Week: Autonomy has started to talk about itself as a provider of meaning-based computing [MBC]. As its chief executive, how do you define this concept?
Mike Lynch: Meaning-based computing is the ability for a machine to act on the basis of what something means – something being text like email and documents, but also PDFs, voice over IP and other types of content. The reason it is important is that information is broken into two distinct groups: structured stuff that goes in relational databases and all the unstructured stuff, which, while it is exploding in terms of usage, doesn’t fit into IT infrastructures very well.
Why is unstructured data important to organisations?
More and more of the information in companies – estimated to be 85 percent – is unstructured and it is often the most interesting information... [Accessing this information] gives you the opportunity to better leverage your information assets. But there is also a really big negative in the form of compliance problems caused by unstructured data and the need, in the case of litigation, to find all this data.
How can MBC systems help?
The problem with unstructured data is computers haven’t been able to do anything with it apart from move it around. The way we’ve got used to working with it is that we retrieve it, which is why people like search, then a human being looks at it and does the work. In contrast, with structured information the point of IT is to automate, so if you are a bank, the database with the account information spots if someone goes overdrawn and then sends them a letter, with no human being involved in the process at all. The aim of MBC is to enable companies to do a similar thing with unstructured information.
What types of technology fall under the banner of MBC?
It is a broad church. There are lots of methods that go into MBC, from sp eech recognition to text understanding, but the whole point is to produce platforms that can go that step further. This is a big change [in the way IT works] as it is really moving the data back to what humans want. We started with human data, then IT came along and we took all the rich information and boiled it down to database tables. Now we are going back and computers are catching up with what the humans can do. We are just at the beginning of this movement, but in a few years time you will see unstructured information used and processed all over the place.
How will this happen?
By eliminating high entry costs for big data analysis, you can convert more raw data into valuable business insight.
A discussion of the "risk perception gap", its implications and how it can be closed