Evidence is everywhere
Many of the building blocks are already in place.
- Vast server farms with vast renewable energy farms to match
- A deepening relationship with IBM and Watson
- A growing connected health network
- This week’s purchase of augmented reality firm Metaio
- Its recruitment of Yale robotics expert John Morrell in 2012
9to5Mac’s news that Apple is developing ‘Proactive,' an intelligent, context-based solution that protects user privacy while exceeding the features of Google Now lends even more weight to development of big data driven A.I. solutions.
No surprise then that a search of Apple’s job vacancies reveals at least 23 roles with ‘Artificial Intelligence’ in the job description. A job description for a Siri Speech Platform engineer reads:
“Play a part in the next revolution in human-computer interaction. Contribute to a product that is redefining mobile computing. Create groundbreaking technology for large scale systems, spoken language, big data, and artificial intelligence.”
Connect the data
The description makes clear that machine learning and big data are also part of the Siri team’s tasks. That’s the kind of machine intelligence you can expect from IBM’s Watson, or from other deep learning systems in development by other technology firms, including Facebook and Google.
Big data analysis, speech recognition and deep learning are critical to these A.I. machines, and this kind of intelligence also informs developments in robotics.
Morrell was a leading engineer at Segway. Once at Apple, he worked with Segway’s former chief technology officer, Doug Field, who decamped to Tesla Motors in 2013 where he is now vice president for vehicle programs. These connections link neatly with the now much-anticipated Apple Car.
Machine intelligence
If we stop to consider what the features of such a vehicle might be, it isn’t hard to imagine that spoken word instruction, predictive analytics, automatic accident prevention and car-to-car communication will feature in any Apple Car. This isn’t just about texting while keeping your hands on the wheel – though these things will do that, too. Auto manufacturers are already developing these solutions.
Once you accept that Apple is developing in-car intelligence, then it would be foolish to imagine it will not seek to apply this intelligence in other fields, such as self-healing machines, robotics and A.I., augmented services and automation.
That’s not especially surprising when you consider the entire technology industry has been on a trajectory to develop smarter-than-human A.I. since way before the Difference Engine or the writings of the UK’s first Mac user, Douglas Adams.
Social consequences
Five years ago, I was among the first to predict Apple Pay. Lots of people didn’t agree, but all that was required to predict it was to join the dots of what little was already known.
When it comes to A.I., it seems pretty clear that Apple has assembled much of what it needs to achieve rapid progress in the development and deployment of increasingly sophisticated cloud-based artificial intelligence across its growing line of products in the coming years. It certainly has the budget to do it.
“I think we should be very careful about artificial intelligence. If I had to guess at what our biggest existential threat is, it’s probably that,” warned Tesla boss Elon Musk last year.
There remain concerns that A.I. automation will destroy more employment than it creates. Apple is aware of these concerns: Apple board member Andrea Jung (who moved to a new job last year) serves on the Committee for Economic Development, which only last month warned that this new wave of automation could seriously impact employment and further polarize wealth inequality.
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