“Apple listed John Giannandrea on the site as its first Chief of Machine Learning and AI Strategy. He’s in charge of AI and machine learning, a potent type of AI software, across the whole company.
Prior to Apple, Giannandrea was a top AI executive at Alphabet’s Google. He joins Apple after several years of complaints about the reliability of the Siri voice service, which has become an increasingly important product for Apple given rival offerings like Amazon.com Inc.’s Alexa and the Google Assistant.”
“Goodfellow is known for inventing a form of machine learning training algorithms called generative adversarial networks (GANs). GANs are effectively two AI systems that are pitted against each other. Working against each other, they both improve.”
“A Cisco report estimates that connected home applications, such as home automation, home security, and video surveillance, connected white goods, and tracking applications, will represent 48% of the total machine-to-machine connections by 2022.”
“Apple, they write, stands out: its “Metal” API for iOS runs on a consistent chip platform and the GPUs in those chips are higher-performance, on average, “making Metal on iOS devices with GPUs an attractive target for efficient neural network inference.” Even then, however, the results of a “rigorous” examination of the speed of inference across six generations of Apple’s “A” series chips shows that within each generation of chip there is still “wide performance variability.”
“Programmability is a primary roadblock to using mobile co-processors/accelerators,” they write.
The newest version of Facebook’s “PyTorch” framework, unveiled this year at the company’s developer conference, is designed to “accelerate AI innovation by streamlining the process of transitioning models developed through research exploration into production scale with little transition overhead.” It also supports the “Open Neural Network Exchange,” or ONNX, specification backed by Microsoft and others.”