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Moving your business to the cloud, and developing a business architecture within a digital environment, is a lot to do with automation, according to a senior executive at IBM. 

In an exclusive interview with Enterprise Management 360º, IBM’s lead cloud advisor in Europe and part of the overall Watson artificial intelligence unit Rashik Parmar says: “I focus on helping clients sync through their journey into cloud – how they should adopt cloud and leverage cloud to help them in their business.

“And a lot of the cloud journey is about automation, and different forms of automation that flow from that. So we end up in interesting dialogues around automating different aspects of work and working life.”

Parmar gives his “favourite example” of a company in the railroad industry which uses cloud and automation.

“If you look at the big freight trains that go from the east coast to the west coast of the UK, the biggest issue they have is cracked wheels. When a wheel cracks, you’re in danger of getting a derailment, which can be damaging for the goods, and it could potentially be harmful to life.

“So what we’ve done is we’ve built sensors inside the train, on the carriages, and by using cognitive algorithms, we can actually pick up the sound signature of the wheel – compared to the wind noise, compared to the engine noise, and all the other noise that’s going on – and say, ‘That’s the noise of that wheel’, and be able to know when that wheel is about to crack.

“And as the sound signature of the wheel changes, we can use cloud technologies to get information back to the operator to say, ‘Don’t move the train any further because the wheel’s going to crack’.

rashik parmar ibm
Rashik Parmar, lead IBM cloud advisor, Europe

“That could be called preventative maintenance, if you like, but it’s also automating aspects of the work environment in a new way. It’s actually transforming how we do things.”

Other examples Parmar gives include one involving a “robot concierge” at a Hilton hotel. “Connie”, as the robot is called, is a Watson AI-enabled Nao robot, which stands atop the reception desk and supposedly assists advises guests about various things.

“And in the manufacturing space,” continues Parmar, “car manufacturers are looking at using data – not necessarily to improve just the robotics systems, but to improve the assembly line. So they’re starting to use weather data to know and predict the temperature of the water that’s coming down the stream. Water used as part of the manufacturing process needs has to be heated to a certain temperature for different parts of the process. Knowing the water temperature and predict that 24 hours in advance, you can optimise the water usage and the cost of the energy used in your entire manufacturing process.

“Cloud and automation is not just saying, ‘I’m going to replace what people do’, it’s actually about using data to optimise and improve what people do.”

‘A lot of the journey to the cloud is about automation,’ says IBM Click To Tweet

Cloud, says Parmar, is the platform which allows you to utilise “smart algorithms”, or the “brains”, which can bring together the data from perhaps thousands of sensors and other points on the internet of things and analyse them to discover patterns and other useful information.

And there’s something new in those “brains”, says Parmar. It’s got an old familiar name – artificial intelligence – but it’s been working out apparently and is all new.

“The newness is two-fold,” explains Parmar. “One is, we’ve always had the ability to write sophisticated programs, and that’s a logic sequence – a sequence of steps and controls which allow you to do things. And that’s – if you like – embedded intelligence. But there’s an individual or group of individuals writing that program.

“What we’re now finding is algorithms that can learn, based on interactions. And that learning allows them to create completely new interpretations that we wouldn’t really see ourselves.

“So the first set of algorithms are learned algorithms that learn by continually being used.

“And the second aspect is that they’re able to make connections that you wouldn’t be able to make yourself – well, you could if you had enough time, but they start to provide some level of cognition or understanding that is above and beyond what was programmed into them in the first place. And that’s the new aspect.

“So if you look at what we do at IBM with Watson, in the health sector for example, we’re using that cognition to be able to understand and identify potential molecules which attack certain diseases that we wouldn’t have thought about before.

“We [humans] may get there eventually, but it [Watson, AI, and/or machine learning algorithms] is accelerating that process.”

Any sufficiently complex occupation requires voluminous education and training, often retraining or learning new things. This is an ongoing requirement in most professions. Which is why the more experienced a person is, the more likely it is that they will be better at their jobs.

But what if someone new could immediately learn all the things the experienced person knows, and be able to analyse and interpret that knowledge in entirely new and useful ways, and apply its learning to future situations before they even occur? Sounds like a job for Watson and the cloud – probably.

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