John Giannandrea

John Giannandrea is a software engineer who has worked on the development of machine learning and artificial intelligence with various companies. He is also the cofounder of Metaweb and Tellme, has worked at General Magic, Netscape, Google, and is the senior vice president of Machine Learning and Artificial Intelligence Strategy at Apple. Giannandrea was born in Bridge of Allan, Scotland. He attended the University of Strathcyde, where he received his Bachelor of Science with Honours in Computer Science in 1988, and from where he would receive his Doctorate Honoris Causa in 2013. Giannandrea is on the board of trustees at the SETI Institute.

After graduating from the University of Strathclyde in 1988, John Giannandrea worked as a software engineer at the INMOS Corporation from 1988 to 1990 and Silicon Graphics from 1990 to 1992 before joining General Magic in 1992 as a senior engineer. General Magic was an Apple spinout, which focused on early personal digitial assistants and a novel service architecture based on peripatetic programming. In 1994, Giannandrea moved to Netscape, where he worked as a chief technologist.

In 1999, John Giannandrea cofounded Tellme Networks with Mike McCue. Giannandrea took on the role of chief technology officer at the company, which worked on applied voice recognition systems for voice applications. This included developing directory assistance systems for telephone companies, such as AT&T, and developing customer support systems for Fortune 100 companies (including 1-800-Fedex, Merrill Lynch, and more).

In 2005, John Giannandrea left Tellme to cofound Metaweb with Danny Hillis, where he took on the role of chief technology officer once more. Metaweb pitched itself as a database of the world's knowledge, which worked to make the internet more knowledgeable by making it more understandable to computers. Metaweb's goal was to create virtual entities or representations of ideas that allowed computers to understand connections between people, places, or things and use these associations to lead a search back to a main entity. In 2010, Google acquired Metaweb to turn the company's technology into Google's Knowledge Graph.

Following the acquisition of Metaweb by Google, Giannandrea became the head of machine learning research and was responsible for projects foundational to Google's AI pursuits, including working on Google's Computer Science Research and Machine Intelligence groups; leading teams in machine learning, machine intelligence, computer perception, natural language understanding, and quantum computing; was part of developing the company's Photos app, including reverse image search and Clips; created voice-recognition software for voice search and Google Home; and working on Google's self-driving car project. Giannandrea also oversaw the integration of machine learning into Google's main search, known as RankBrain, which would offer Giannandrea a promotion to the head of search in 2016. The promotion of Giannandrea to the head of search was noted as part of a broader trend, as machine intelligence advances continued to see the technology integrated into more of Google's core product.

At the time of his promotion to the head of search, Marc Andreessen—co-founder of Netscape (where Giannandrea worked as Chief Technologist)—said of Giannandrea: "He's an OG Valley technology visionary, always on the leading edge; [I] always learn new things when I talk to him."

John Giannandrea joined Apple in 2018 and oversees the strategy for artificial intelligence and machine learning across the company and the development of Core ML and Siri technologies. Shortly after joining Apple, Giannandrea was promoted to the executive team, where his title became "Senior Vice President of Machine Learning and Artificial Intelligence Strategy" and reported directly to Apple CEO Tim Cook. The promotion came after the hiring of Giannandrea brought the Siri and Core ML teams together under unified leadership for the first time.

The hiring of Giannandrea at Apple was motivated by, in part, an attempt to improve the record of Apple's artificial intelligence work, including improving its algorithms and helping recruit more top-level talent for AI research and development at Apple. The company had previously struggled due to the company's stance on user privacy and the large amounts of data neural networks required to be trained. Since his hiring in 2018, Apple has worked to include machine learning in more of the company's product stack. By 2020, when asked about the role of machine learning in the company, Giannandrea said that it would be easier to list software and products that did not include or use machine learning in some way.

Apple hired John Giannandrea to accelerate the company's AI and machine learning development. To do this, Giannandrea has overseen the development of the underlying technology for an AI system, which includes revamping Siri in a way that allows Apple to implement the AI deeper in its technology.

Giannandrea, in a similar interview, noted that Apple's approach to machine learning and AI is founded around building a better user experience and how using machine learning and AI can lead to hardware and software products working better for consumers, noting the Apple Pencil uses machine learning to better distinguish between a user's palm press or an intentional input. He also noted, as Apple works on augmented reality products, that AI and machine learning will be important to getting the software and hardware products working properly.

As someone who has worked on artificial intelligence, machine learning, and natural language processing for most of his career, Giannandrea has been asked for his opinions on the future of artificial intelligence. He has said, in the past, that his great interest and the "holy grail" of artificial intelligence is language understanding and summary, which Giannandrea has likened to allowing an AI system to begin to mimic the human mind. Similarly, Giannandrea has said in the past that he is less concerned about a supposed "AI apocalypse" but has rather stated his concern is with the bias in machine-learning algorithms. He notes bias may come from biased data, which has the potential of creating an implicit, undetected bias, which (if the bias is pervasive in the industry) may go undetected by developers or users. Giannandrea has stated his belief is that transparency in the training data, and about the training data, used to develop the algorithms which can allow developers and users (among others) to look for the potential bias when building a system.