DeepMind has another source of leverage, though it requires constant replenishment: favourable publicity. The company excels at this.
DeepMind said in 2016 that they had reduced Google’s energy bill by 40%. But some insiders say such boasts are overblown. Google had been using algorithms to optimise its data centres long before DeepMind existed. “They just want to have some PR so they can claim some value added within Alphabet,” says one Google employee. Google’s parent Alphabet pays DeepMind handsomely for services like these. DeepMind billed £54m to Alphabet companies in 2017. That figure pales in comparison to DeepMind’s overheads. It spent £200m on staff alone that year. Overall, DeepMind lost £282m in 2017.
This is a pittance for the cash-rich giant. But other Alphabet subsidiaries in the red have attracted the attention of Ruth Porat, Alphabet’s parsimonious chief financial officer. Google Fiber, an effort to build an internet-service provider, was put on hiatus after it became clear that it would take decades to make a return on investment. AI researchers wonder privately whether DeepMind will be “Porated”.
DeepMind’s tight control needed for press management doesn’t gel with the academic spirit that pervades the company.
Google’s annexation has angered employees at DeepMind Health. According to people close to the health team, more employees plan to leave the company once the absorption is complete. One member of the IRP, Mike Bracken, has already walked out on Suleyman. According to multiple people familiar with the event, Bracken quit in December 2017 over concerns that the panel was more about window-dressing than genuine oversight. When Bracken asked Suleyman if he would give panel members the accountability and governance powers of non-executive directors, Suleyman scoffed.
Current and former researchers at DeepMind and Google, who requested anonymity due to stringent non-disclosure agreements, have also expressed scepticism that DeepMind can reach AGI through such methods. To these individuals, the focus on achieving high performance within simulated environments makes the reward-signal problem hard to tackle. Yet this approach is at the heart of DeepMind. It has an internal leaderboard, in which programs from competing teams of coders vie for mastery over virtual domains.