59 FUTURE SHOCK MICRO FOCUS
t’s easy to think of artificial intelligence as being something newly discovered, something brand new in 2018. But there are
MACHINE LEARNING BECOMES MORE USEFUL THE MORE DATA IT’S EXPOSED TO
companies that have been steadily working at the coal face of AI for years and have been providing AI-enhanced service to a multitude of customers worldwide. “Micro Focus is the seventh largest pure software company in the world,” says David Humphrey, CTO of rich media. Headquartered in the UK, but with oices globally, the company’s services cover everything from cybersecurity to cloud managment to file and network access. In increasing demand are its video analysis tools. The services run along two main strands. One is security, which includes video analysis for public safety, law enforcement, and worker health and safety. The other is media analysis of broadcast content for businesses, governmental organisations or brands wanting to track the occurrence of specific types of subject matter. “It could be a government or enterprise wanting to know what people are saying about them or what situations are developing that they may need to react to,” explains Humphrey. “Or, to a lesser extent, tracking which logos are appearing on the television – not in a pure advert, because that’s well known and well-documented, but for product placement or in a Grand Prix how many times the Peroni logo is seen. It’s quite a wide gamut.” The company’s video analysis can capture information about all aspects of the video content – who is appearing in the video, what is said, what music is playing, what products are appearing – and is oered as a set of tools for customers to build into their own applications. Micro Focus applications include speech to text and object, facial and optical character recognition and audio classification. Although they may be straightforward and easy to incorporate
from the user end, the technology behind them is the result of years of dogged research by developers in Micro Focus’ Cambridge labs. “To use the current terms, our work is heavily based in AI, machine learning, neural networks. Those seem to be the buzzwords of the time, but we’ve been doing it for many years. Consequently, there is some stu it automatically learns and interprets and understands better and there some parts that we allow you to train. For example, we will provide you with dierent models for dierent languages, but you might be analysing a documentary library on oil rigs and there could be some very industry-specific terms. You can improve the recognition rate by using more specific language models for that industry, or you might want to train the system to recognise some completely new object.” EDUCATING THE AI Machine learning becomes more useful the more data it’s exposed to. Ongoing and ever-developing data sources like news reports can provide an excellent field for machine learning to work in. “We continually monitor news so that we can update our language models. Certain names and places are not in common vocabularly, but when they come up on the news we want to be able to understand what they are. “Unlike certain competitors who have a language model that’s based on actually understanding each word and how each word fits together – which is very diicult to keep track of – we use a probabilistic language model. We focus on the context of the language rather than the individual meanings…The classic example is if I tell
PICTURE WORTH WORDS The above image displays real time speech analytics transcribing broadcast audio to text
you about a flightless black and white bird that lives in the sea in cold climates, you know what it is, even though I haven’t said the name.” Using context, the AI can tell whether an instance of the word “bush” refers to a large plant or a former president of the USA. “Or we might look at how it would approach the appearance of the words “Daesh” and “ISIS”. A simplistic way to do this it is to run synonyms and say, “If you ever hear ISIS, then ISIS equals Daesh”. But that way takes an awful lot of upkeep. The way our system learns, in the probabilistic use of language, it will put together itself that Daesh and ISIS are the same thing.” The underlying architecture of the Micro Focus AI supports about 150 languages, with some 30 languages supported in its speech to text application and its ability to recognise meaning and sentiment, all of which was acquired through machine learning. MASSIVE METADATA Micro Focus works with major media brands in radio, newspapers and journalism, both as an archive tool and a newsgathering facility. “We have worked with TV news companies, helping them understand what is said in other languages and to improve their workflow from getting footage to broadcast. We also do pure newsgathering with our media monitoring where we can learn who said this, who said that. “We also work with companies who are monitoring their own programmes and
TRENDING Micro Focus AI’s can automatically analyse and display trends in news coverage with automatic categorisation
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