Narrative: Apple is Behind in AI
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Narrative: Apple is Behind in AI (Dec 26, 2016)
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Apple Launches Machine Learning Journal (Jul 19, 2017)
★ Apple is Developing a Dedicated AI Chip (May 26, 2017)
It emerged over the weekend that Apple has acquired Lattice Data, a company which specializes in analyzing unstructured data like text and images to create structured data (i.e. SQL database tables) which can then be analyzed by other computer programs or human beings. TechCrunch has a single source which puts the price paid at $200 million, and Apple has issued its usual generic statement confirming the acquisition but offering no further details. It’s worth briefly comparing the acquisition to Google’s of DeepMind in 2014: that buy was said to cost $500 million and was for 75 employees including several high profile AI experts, though it was unclear to outside observers exactly what it was working on, while this one reportedly brought 20 engineers to Apple and has several existing public applications and projects to point to. Lattice is the commercialized version of Stanford’s DeepDive project, which has already been used for a number of applications involving large existing but unstructured data sets. Lattice has a technique called Distant Supervision which it claims obviates the need for human training and instead relies on existing databases to establish links between items that can be used as a model for determining additional links in new data sets. It’s not clear to me whether the leader of the DeepDive team at Stanford, Christopher Ré, is joining Apple, but he was a MacArthur Genius Grant winner in 2015 and this video from MacArthur is a great summary of the work DeepDive does (there’s also a 30-minute talk by Ré on the DeepDive tech). Seeing Apple make an acquisition of this scale in AI is an indication that, despite not making lots of noise about its AI ambitions publicly, it really is serious about the field and wants to do better at parsing the data at its disposal to create new features and capabilities in its products. It’s entirely possible that we’ll never know exactly how this technology gets used at Apple, but it’s also possible that a year from now at WWDC we hear about some of the techniques Lattice has brought to Apple and applied to some of its products. Interestingly, the code for DeepDive and related projects is open source and available on GitHub, so I’m guessing Apple is acquiring the ability to make further advances in this area as much as the technology in its current form.
Google Develops Federated Machine Learning Method Which Keeps Personal Data on Devices (Apr 6, 2017)
This is an interesting new development from Google, which says it has created a new method for machine learning which combines cloud and local elements in a way which keeps personal data on devices but feeds back the things it learns from training to the cloud, such that many devices operating independently can collectively improve the techniques they’re all working on. This would be better for user privacy as well as efficiency and speed, which would be great for users, and importantly Google is already testing this approach on a commercial product, its Gboard Android keyboard. It’s unusual to see Google focusing on a device-level approach to machine learning, as it’s typically majored on cloud-based approaches, whereas it’s been Apple which has been more focused on device-based techniques. Interestingly, some have suggested that Apple’s approach limits its effectiveness in AI and machine learning, whereas this new technique from Google suggests a sort of best of both worlds is possible. That’s not to say Apple will adopt the same approach, and indeed it has favored differential privacy as a solution to using data from individual devices without attributing it to specific users. But this is both a counterpoint to the usual narrative about Google sacrificing privacy to data gathering and AI capabilities and to the narrative about device-based AI approaches being inherently inferior.
Apple GPU Supplier Imagination Tech Says Apple Plans to Build its Own GPU in 1-2 Years (Apr 3, 2017)
This already feels likely to be one of the biggest news items of the week (incidentally, you can now use the Like button below to vote for this post if you agree – the posts that get the most votes are more likely to be included in my News Roundup Podcast at the end of the week). There have been ongoing reports that Apple would like to build more of its own in-house technology, and GPUs have seemed at least a candidate given that Apple was said for a while to be mulling an acquisition of the company, and has been bringing Imagination Tech employees on board since the deal didn’t go ahead. The GPU obviously has a number of existing applications, but GPU technology has increasingly been used for AI and machine learning, so that’s an obvious future direction, along with Apple’s reported investment in AR. Apple’s ownership of its A-series chips (and increasingly other chips like its M and W series) is a key source of competitive advantage, and the deeper it gets into other chip categories, the more it’s likely to extend that advantage in these areas. This is, of course, also a unique example of Apple making a direct statement about a future strategy (albeit via a third party): as Apple is IMG’s largest customer, it had to disclose the guidance from Apple because it’s so material to its future prospects – the company’s share price has dropped 62% as of when I’m writing this.
Apple’s Siri learns Shanghainese as voice assistants race to cover languages – Reuters (Mar 9, 2017)
One of the things that’s often missed by US writers covering Amazon’s Alexa and its competitors is how limited it still is in language and geographic terms. It only speaks English and German and the Echo range is only available in a handful of countries. Siri, meanwhile, just got its 21st country and 36th language, which reflects a long-time strength of Apple’s: broad global support. Apple News is a notable exception, which is only available in a few countries and one language, but almost all of Apple’s other products are available in a very long list of countries and territories, often longer than for other competing services. The article here is also interesting for the insights it provides into how each company goes about the process of localization, which is quite a bit more involved than you might surmise.
Apple Officially Joins Partnership on AI (Jan 27, 2017)
I commented on the reports that Apple was about to join the Partnership on AI yesterday, so I won’t revisit all of this today. Two notable things from today’s announcement, though: Apple’s representative will be Tom Gruber, who runs Siri at Apple, and that may be indicative of where Apple sees ownership of AI residing within the company (it has no formal head of AI); secondly, Apple has been involved with the Partnership from the outset, but hadn’t formalized its membership until today. That might signify that there were some details of Apple’s membership which needed to be worked out before it felt comfortable joining -I’d love to know what those were. Separately from Apple’s involvement, it’s worth noting that the board now has representatives from a number of other organizations beyond tech companies including several universities. So the Partnership won’t just be about driving the agenda of the tech industry here.
This would be a fascinating development – Apple has very rarely been part of such groups in the past, often a holdout among major tech companies. But it does seem to be taking AI very seriously at this point, and seems also to be taking steps to help current and potential employees feel they can continue to contribute in the industry beyond Apple’s walls, including allowing employees to publish research and potentially now joining this group. It’s also worth noting that AI, perhaps more than any other major technology currently being developed, has massive ethics implications, and ethics and related issues are a major focus of the group. Apple may feel that it needs to be both contributing to and learning from others in the field when it comes to these non-technical issues.