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Google Stadia will be “faster and more responsive” than local gaming hardware
Google engineer claims "negative latency" is key to beating local hardware

Speaking with Alex Wiltshire in Edge magazine #338, Google’s top streaming engineer claims the company is verging on gaming superiority with its cloud streaming service, Stadia, thanks to the advancements it’s making in modelling and machine learning. It’s even eyeing up the gaming performance crown in just a couple of years.
“Ultimately, we think in a year or two we’ll have games that are running faster and feel more responsive in the cloud than they do locally,” Bakar says to Edge, “regardless of how powerful the local machine is.”
This would be achieved using Google’s homegrown streaming tech, which it’s been teasing ever since Stadia was first announced late last year with Project Stream. The company believes its tech is capable of overcoming the hurdles presented by over-the-web gaming, despite its extensive web of datacentres sitting potentially hundreds of miles away from a user.
Specifically Bakar notes Google’s “negative latency” will act as a workaround for any potential lag between player and server. This term describes a buffer of predicted latency, inherent to a Stadia players setup or connection, in which the Stadia system will run lag mitigation. This can include increasing fps rapidly to reduce latency between player input and display, or even predictive button presses.
Yes, you heard that correctly. Stadia might start predicting what action, button, or movement you’re likely to do next and do it for you – which sounds rather frightening.
So does that count as the fastest system if technically some clever algorithm is playing the game for you? I’m not so sure.
But Google is plenty confident Stadia will delight users, and in my own experience with the tech back at E3 I didn’t notice any actions going awry. However, that was in a Google-approved environment, and we’ll have to wait until Stadia’s launch this November to find out how efficient Stadia’s streaming algorithms are in the real world.