John Giannandrea is Apple's senior vice president of Machine Learning and AI Strategy. He joined Apple in 2018 after his 8-year tenure at Google, leaving as head of Machine Learning. Giannandrea was born in Bridge of Allan, Scotland in 1965. His first claim to fame happened while he worked at General Magic, an Apple spin-off in the '90s.
● Senior vice president of Machine Learning
● In charge of Siri development and Apple Car
● Former Google head of Machine Learning
● Founded Metaweb in 2005
● Founded TellMe
● CTO at Netscape
● Worked at General Magic in the '90s
● Attended University of Strathclyde
● Born in Bridge of Allan, Scotland
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Not much is known about Apple's AI head, having spent most of his career behind closed doors and making few public appearances. John Giannandrea sparked the early days of machine learning. He began working on a smart assistant during his time at General Magic, a company that had branched from the failing Apple of the '90s.
"John hit the ground running at Apple and we are thrilled to have him as part of our executive team," said Apple CEO Tim Cook. "Machine learning and AI are important to Apple's future as they are fundamentally changing the way people interact with technology, and already helping our customers live better lives. We're fortunate to have John, a leader in the AI industry, driving our efforts in this critical area."
John Giannandrea interviewed
"Computers are incredibly powerful but they are also pretty dumb, and I think we need to work hard to make them fulfill the potential that they have and so that means teaching them to be smarter," Giannandrea said to CNBC. "Technology should augment the human intellect, not replace it. It should be a powerful tool to help us think better, and I think that is really the journey we are on."
The industry surrounding machine intelligence and artificial intelligence holds a simple belief — more data means stronger AI. Apple's SVP of ML doesn't think so, he says that algorithms should run locally on small data sets.
"I understand this perception of bigger models in data centers somehow more accurate," he told Ars Technica, "but it's actually wrong. It's better to run the model close to the data, rather than moving the data around."
By close to the data, he means on-device machine learning. If you examine data on the device running a maps app or workout program, the data is more private and algorithms output information faster.
He provided the example of taking a photo using off-device machine learning. "If you wanted to make that decision on the server," he said, "you'd have to send every single frame to the server to make a decision how to take a photograph."
"That doesn't make any sense right? So, there are just lots of experiences that you would want to build that are better done at the edge device," he continued.
On joining Apple
"When I joined Apple, I was already an iPad user, and I loved the Pencil," he said. "So, I would track down the software teams and I would say, 'Okay, where's the machine learning team that's working on handwriting?'"
There wasn't one, so he created it and says that there is now practically no part of Apple that isn't engaging with AI and ML. "I find it very easy to attract world-class people to Apple," he said, "because it's becoming increasingly obvious in our products that machine learning is critical to the experiences that we want to build for users."
Giannandrea says that he was attracted to Apple, and believes it is the right place to work on these topics, because of this same issue of being focused on experiences. "I think that Apple has always stood for that intersection of creativity and technology," he said.
"And I think that when you're thinking about building smart experiences, having vertical integration, all the way down from the applications, to the frameworks, to the silicon, is really essential," he continues. "I think it's a journey, and I think that this is the future of the computing devices that we have, is that they be smart, and that, that smart[ness] sort of disappear[s]."
On Apple Silicon
"We will for the first time have a common platform, a silicon platform that can support what we want to do and what our developers want to do," he says. "That capability will unlock some interesting things that we can think of, but probably more importantly will unlock lots of things for other developers as they go along."
Giannandrea explains that this is specifically because of how Apple is going to be able to leverage the Apple Neural Engine (ANE) works. "It's a multi-year journey because the hardware had not been available to do this at the edge five years ago," he said.
"The ANE design is entirely scalable," he continued. "There's a bigger ANE in an iPad than there is in a phone, than there is in an Apple Watch, but the CoreML API layer for our apps and also for developer apps is basically the same across the entire line of products."
As well as his technology work within Apple, Giannandrea has recently been lobbying European Union officials over their plans to regulate the use and implementation of AI. Separately, Apple is continuing to acquire companies specifically to aid in the development of AI such as Siri.
Apple's SVP of ML
In what was unusually fast, even for Apple, Giannandrea arrived at the company to take a senior executive chair seemingly overnight. He pushed out former Siri lead Bill Stasior and other Siri founders during his internal restructure.
It is believed that Siri is a major target of the new executive, hoping to bring the lagging assistant up to par with the industry.
The former Google executive was vocal about AI, even stating that the term was too loose and undefined, preferring to call it "Machine Intelligence." Prior to his departure at Google, he was leading all of the search team and ML team and was vocal about his excitement surrounding self-driving car technology.
John Giannandrea has a long history in the technology world, and it started right next-door to the Cupertino company.
John Giannandrea's career in Machine Intelligence
The earliest mentions of Giannandrea's career always pin him at General Magic, a company that marked the beginning of many innovations in Silicon Valley that would affect the industry all the way to today. One of the company's fledgling projects that never saw the light of day was an early prototype for a smartphone-like device. A part of this device was going to host a smart assistant, and this was Giannandrea's own project.
While the project never made it to the public, it is clear he was an industry pioneer.
A short time after Netscape's founding in 1994, John Giannandrea joined the company. In an interview with Fortune Magazine, he helped detail the early days as employee number 18 of about 30 at the company's formation.
Netscape was apparently hungry for engineers who had some hand in early web development, snatching up whoever it could. Netscape went on to become a pioneer in internet technology as one of the early consumer browsers. AOL purchased the company in 1999 while Microsoft's Internet Explorer had it on its deathbed.
Not resting on his laurels, he went on to help found Tellme, a "voice portal" telephone service. Using voice recognition software, the technology would connect people with a recorded voice that would read specific stock numbers, weather, or even let your kids talk to Santa Claus.
This is an early example of how machine learning, then a simple answer tree, was going to affect consumers' lives. Microsoft acquired Tellme in 2007, but Giannandrea had already moved on.
In 2005, Metaweb was founded and began work on Freebase, an early predecessor to what now runs websites like Wikipedia. John Giannandrea was brought on as Chief Technology Officer to help with the development of the software.
In 2010 Google acquired Metaweb, thus bringing Giannandrea into the search engine company. He and the other engineers joined the machine learning team to push Google's own AI initiatives forward.
In 2016, Google merged the search team with the machine learning team and placed Giannandrea in charge of the whole division. He spent two years there spurring the development of Google Assistant and may have even had a hand in the Google self-driving car project.
In 2018, Apple poached the engineer from Google, just when things were looking a bit bleak for Siri, to come in and revitalize the aging assistant. It is yet to be seen exactly what changes will come to the platform as a result of Giannandrea's leadership, but major shifts internally suggest we will see something soon.
Advancements in the Neural Engine and machine learning can be tied back to John Giannandrea since his start at Apple. An interview revealed that he is tied to many products within Apple, as he tries to expand the machine learning efforts everywhere.
When he first arrived, the Apple Pencil handwriting engine was his first target. Now with iPadOS 14 and Scribble, users can write in any text field without issue.
The move from Intel to Apple Silicon also offers more chances to implement machine learning in general Mac operations. With the Neural Engine in the Apple Silicon being even larger and more powerful than what is found in iPads, the machine learning capabilities will be huge.
John Giannandrea expects that the Neural Engine is key in the growth of software platforms and developers will be able to find new ways to implement it within their apps.
In December 2020 Giannandrea was placed in charge of the Apple Car project. He will run this in parallel to his responsibilities for Siri and machine learning platforms.
The role was previously held by former SVP of hardware engineering Bob Mansfield. He had retired in 2012 but stayed with Apple as an advisor until ultimately coming out of retirement in 2016 for Project Titan. He has now fully retired again.
The day-to-day operations are run by Doug Field who now reports to Giannandrea. The project will rely upon machine intelligence to develop autonomous driving systems.
The Cupertino tech giant's self-driving vehicles drove 18,805 miles on California roads in 2020, up from 7,544 miles in 2019, according to a report filed with the state's Department of Motor Vehicles.
In addition to more road testing, Apple's autonomous technology seems to have improved as well. The same report indicates that Apple's self-driving cars had a disengagement — a situation when a human driver needs to take over — every 145 miles. In 2019, Apple reported a disengagement every 118 miles.
Apple's road testing in both 2019 and 2020 still lagged behind 2018 when the company's cars drove nearly 80,000 miles but had a disengagement about every mile. Giannandrea's hire came at a time when Apple was beginning to accelerate car development.
Rumors in February indicated that Apple was in negotiations with car manufacturers like Hyundai. The rumors have died down, but the need for distribution channels shows how far along Project Titan has come.
Ming-Chi Kuo expects Apple to publically announce the Apple Car by 2025 and release it for sale by 2030. John Giannandrea's experience with machine intelligence and Google's self-driving project will likely spur Apple Car's development.