Cloudera CEO Tom Reilly on law enforcement and fake news
Data Mining

Cloudera CEO Tom Reilly on law enforcement and fake news

Governments, law enforcement and intelligence agencies that are not using big data and machine learning are at a distinct disadvantage when it comes to tackling terrorism and crime, says Tom Reilly, CEO of Cloudera. Reilly, in London to attend the Strata Data Conference at the ExCel conference centre, was talking about all the positives that big data, AI and machine learning can bring to society and keeping it safe and he doesn’t buy into Elon Musk’s assertion that with AI, “we are summoning the devil.”

“There will be nefarious uses for AI of course but the good things will outweigh the bad,” said Reilly, adding that “we will find ways to control it and protect humanity.”

Cloudera, which Reilly says works with 29 governments around the world is already working on it. Using its big data analytics and predictive tools, the company is currently helping law enforcement and intelligence agencies analyse chatter.

“Law enforcement and intelligence organisations need this technology,” he says. “If they are not using it they are at a distinct disadvantage, with all the emails, social media messages, voice calls and attack attempts that need quickly analysing.”

The sheer scale of the data that can be accessed now means that analysing data is no longer about understanding what has happened, it is about predicting what is going to happen, a sort of Minority Report vision but without the floating “precog” psychics.

Reilly is convinced that big data – and more specifically Cloudera’s particular flavour of Hadoop-based big data analytics – is proving to be “transformative” and talks about how the company is working with “over 200 large financial institutions” to help them “combat money laundering and fraud”.

 

Fake news

His suggestion that big data analytics can also help publishing companies fight against the tide of fake news is interesting. Cloudera has just signed a deal with a major international publishing business. Reilly says it’s using machine learning to analyse Twitter posts, giving them a veracity score to help journalists determine whether they are real or not.

“It’s about them getting news stories out quicker,” says Reilley, “helping journalists verify the sources quickly.”

For Reilly, who says that since going public “nothing has changed” except for the fact that being a public business impacts its core values of being open and transparent, this is the sort of thing that fuels the fires and keeps the company relevant.

Talking about fake news and cybersecurity in particular helps to de-mystify big data and apply context. Like rival Hortonworks, Cloudera has found a way to monetise the open source Hadoop although profitability is an issue. While Cloudera points to customers such as Marks and Spencer, ONS, Barclays and BT (BT recently built a cyber security centre based on Cloudera tech), it reported a net loss for the year of over $187m in January 2017. While revenue is good - $261m for the year – could longer-term sustainability be an issue if it can’t use profits to pay for continued development? The stock market seems happy a month into its IPO. The share price has climbed steadily and given the company a capitalisation of $3.2bn.

“It’s been good,” says Reilly. “We have a longer-term plan and now have to execute against it.”

Part of that plan was to develop a new platform to enable large scale data processing applications to be run on a public cloud. Cloudera used the Strata Data Conference to announce Cloudera Altus, a Platform-as-a-Service (PaaS) designed to “helps data engineers use on-demand infrastructure to speed the creation and operation of elastic data pipelines that power sophisticated, data-driven applications.”

For Reilly though it is the applications that will drive interest. The recent ransomware attacks seem to have fired his belly. According to the DCMS, 70 percent of large UK firms suffered a cyberattack last year. Cybersecurity he says has to be front of mind, businesses need machine learning, not people, not traditional signature-based tools.

“Machine learning is not for the faint of heart,” he warns. “You have to understand data science.” And therein lies a bit of a problem. If Reilly is right, all the best ones will be sucked up into government security agencies and major banks leaving businesses scrabbling around for new skills. A small price to pay if all that big data can keep us safe.

 

Also read:
Cloudera’s CEO builds for new world of data-driven insights
Hortonworks’s Cunitz Plots IPO and Slates Cloudera

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Marc Ambasna-Jones

Marc Ambasna-Jones is a UK-based freelance writer and media consultant and has been writing about business and technology since 1989.

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