This New [AI] Software Constantly Improves – and that Makes all the Difference

Based on a recent conversation between Joseph Sirosh, CTO for AI at Microsoft, and Roger Magoulas, VP of Radar at O'Reilly Media. Link to video recording below.

Joseph and Roger had an interesting conversation at the recently concluded O'Reilly AI Conference in San Francisco where Joseph delivered a keynote talk on Connected Arms.

Their discussion initially focused on a new low-cost 3D-printed prosthetic arm that can "see" and which connects to cloud AI services to generate customized behaviors, such as different types of grips needed to grasp nearby objects. But the conversation soon pivoted into a discussion about the unlimited set of possibilities that open up when devices such as this are embedded with low-cost sensors, take advantage of cloud connectivity, sophisticated cloud services such as AI, link to other datasets and other things in the world around them.

True digital transformation is not about running a neural network or just about AI, as Joseph observes. It is about this ability to tap into software running as a service in the cloud, with the connectivity and global access that it brings. That can endow unexpected and almost magical new powers to ordinary everyday things.

Joseph draws the parallel between this gadget and the digital transformation that every company and every piece of software is going through. Eventually, nearly everything of some value in this world will be backed by a cloud service, will rely on similar connectivity and the ability to pool data to synthesize new behaviors behaviors that are learned in the cloud and which can be tailored to each individual or situation.

That, along with the ability to improve continuously, is what sets apart this current wave of digital disruption.

Joseph concludes with the latter observation, i.e. that the key differentiator of this AI-powered platform of today is that while traditional software does not improve (on its own accord) this new software constantly improves, and that makes all the difference.  

You can watch their full interview below:



AI / ML Blog Team