After Apple’s “Proactive” initiative leaked this week, these words from Google’s I/O keynote — during the reveal of “Google Now on Tap” — caught my attention:
Selective Hearing & Amplification from Google I/O
- Actions
- Answers […] proactively
- Context
- Natural language understanding
- Things (as in, things recognized)
- Places (Google can recognize 100M places)
- Knowledge graph (Google has 1B entities)
- Neural nets (Google’s is 30 layers deep)
- Machine learning
Machine learning […] is going to be a critical [capability] for Apple
Some observations
First, these are all related to, or enabled by, the bottom term: Machine Learning. It’s the ability for a computer to learn new things: shapes, patterns of behavior, relationships, and more. This is already a very important capability for Google, and is going to be a critical one for Apple, too. Why? Well, briefly, to enable Apple devices to make sense of the user’s context (location, activity, history, messages, related information, intent, etc.) and, in turn, to help the user achieve her objective, stated or implied. Things like catching a plane, buying a present, or meeting a friend. Or adjusting exercise frequency, sleep, or diet. The possibilities are many.
The figures [Google showed] speak to the […] massive, massive level of investment Google has made
Second, the figures Google mentioned — 30-layer-deep neural net, 100M places cataloged, 1B entities recognized — these are figures that not only speak to the utility that Google Now on Tap will have, they also imply the massive, massive level of investment Google has made. Investment in computing hardware (a good deal of it custom) and software (neural nets, understanding natural language, learning, user interface, etc.).
Finally, this is what Apple’s project Proactive — or anyone’s machine learning ambition — is up against. The question, for Apple is, does it compete head-to-head (symmetrically) or in a focused way (asymmetrically)? Probably the latter. Either way, I can’t wait to see.
Does Apple compete head-to-head […] or in focused way?
