Topic: AI
Facebook’s AI assistant will now offer suggestions inside Messenger – The Verge (Apr 6, 2017)
This change was reported by The Information a while back but has now been confirmed by Facebook: the M hybrid human-virtual assistant Facebook was testing last year has now been released in a much reduced and entirely AI-based role inside of Messenger. That makes a ton of sense and it sounds like Facebook has been successfully testing this feature for a while with positive user response. The only worry I’d have is that it could be seen as invasive or intrusive, both in the sense of invading users’ conversations uninvited and in the sense that it will appear to be “listening” to users’ conversations for key words and phrases that will trigger that intervention. Privacy isn’t a one-size-fits-all thing – everyone has their own preferences and tolerances for the tradeoffs online services can sometimes entail – so I’d expect to see a range of reactions from delight to outrage.
via The Verge
Apple’s Clips app offers promising & fun editing features, but confusing & difficult UI – 9to5Mac (Apr 6, 2017)
Apple announced the Clips app a couple of weeks ago along with the new iPad and other announcements, and when I commented on that announcement I said the proof would be in the pudding with regard to how well the app performed. We now have reviews (and the app itself is out now too), and it looks like a bit of a mixed bag. The app looks clever, with some nifty new features, but it looks like it may suffer from the same problem as some other Cook-era Apple product releases, in that it seems like it may try to do too much, and therefore can be confusing to use. Here, as with the Apple Watch, Apple Music, and other recent efforts from Apple, it looks like it may have been better served by starting simpler and adding functionality over time. The real test will be whether we start seeing Clips-generated videos showing up in a big way on Instagram, Snapchat, and Facebook, because since this app lacks its own social features the output needs to be shared elsewhere. I still suspect, as I said in my first comment, that this is a better fit for the older Facebook generations than the Snapchat and Instagram generation, but we’ll see.
via 9to5Mac
Google Shares Performance Characteristics for its Machine Learning Chip (Apr 5, 2017)
It’s time to roll out that old Alan Kay maxim again: “those who are serious about software should make their own hardware”. Google started working on its own machine learning chip, which it calls a Tensor Processing Unit or TPU, a few years back, and has now shared some performance characteristics, suggesting that it’s more efficient and faster than CPUs and GPUs on the market today for machine learning tasks. While Nvidia and others have done very well out of selling GPU lines originally designed for computer graphics to companies doing machine learning work, Google is doing impressive work here too, and open sourcing the software framework it uses for machine learning. As I’ve said before, it’s extremely hard to definitively answer the question of who’s ahead in AI and machine learning, but Google consistently churns out evidence that it’s moving fast and doing very interesting things in the space.
via Google Cloud Platform Blog
Microsoft launches Sprinkles, a silly camera app powered by machine learning – TechCrunch (Apr 4, 2017)
As I mentioned recently in the context of Microsoft’s Indian AI chatbot, the company appears to be in an experimental mood as regards AI, trying lots of things in lots of separate spaces, without pushing all that hard in any particular direction. There’s nothing wrong with experimentation, but there is a worry that Microsoft both spreads itself a little thin and risks diluting its brand, which has become more focused of late around productivity. There’s an argument to be made that this Sprinkles app fits its other, newer focus on creativity, but it’s probably a bit of a stretch given the minimal ties into any of its other offerings. On the consumer side, Microsoft’s biggest challenge continues to be not just producing compelling offerings but finding ways to monetize them.
via TechCrunch
Facebook Shows Users More Content Which Doesn’t Come From Your Friends – TechCrunch (Apr 3, 2017)
Almost exactly two months ago, I wrote in my Techpinions column that Facebook’s next big opportunity was finally stepping beyond the idea of showing users only content shared by their friends, and using AI and machine learning to show them other content like content they’d previously engaged with. Doing this, I said, would dramatically expand the amount of interesting content that could be shown to users, thereby keeping them on the service for longer, and giving Facebook more time and places to show ads. And as I wrote almost exactly a year ago, this is just another consequence of Facebook becoming less of a social network and more of a content hub. Today, we’re seeing Facebook not only roll out a video tab (and a video app for TVs) with suggested videos, but also now testing a dedicated tab for recommended content of all kinds in its apps. This is yet another extension of Facebook’s increasing absorption of activity from across users’ lives into its various apps in an attempt to capture more of users’ time and advertisers’ dollars, and I suspect it’ll work pretty well if it’s managed right. Of course, it’s demonstrated several times lately that it’s somewhat lost its touch in that department, so it will need to proceed carefully in pushing forward in this area to avoid alienating users.
via TechCrunch
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.
The Samsung Galaxy S8 voice assistant Bixby can’t recognise British accents – Business Insider (Mar 30, 2017)
This is a great example of something I wrote about on Techpinions this week, which is that here in the US we often assume technologies available to us are ubiquitous globally, but that’s actually rarely the case. In this case, it’s the Bixby assistant / interface that ships with the Samsung Galaxy S8 which not only won’t work in languages other than English and Korean but won’t offer voice services at all in the UK, where of course accents are different. (Another tidbit in this piece is that it won’t actually work in US English until May). Building voice interfaces is tough to begin with, but localizing them for different accents and languages is another massive layer of work, often made harder by the fact that voice recognition technologies are trained on single languages like US English.
via Business Insider
Facebook will launch group chatbots at F8 – TechCrunch (Mar 29, 2017)
This is yet another sign that Facebook feels its initial bot strategy from last year isn’t panning out (something I predicted at the time) and that it needs to try alternative approaches. It’s iterated fairly rapidly since then and added some functions to make interacting with bots easier, and it now sounds like it’s trying another different tack, allowing developers to integrate bots into group conversations. But those bots won’t be interactive AI-type creatures, but instead will provide updates on events or processes, such as sporting matches or food orders. Like earlier pivots, this seems more modest in its ambitions but also more likely to be successful. But Facebook’s direction here stands in marked contrast to Microsoft’s, which continues to work on AI-based chatbots.
via TechCrunch
Microsoft launches Ruuh, yet another AI chatbot – ZDNet (Mar 29, 2017)
It’s fascinating to watch Microsoft continue to experiment with AI chatbots after its first effort, Tay, went so badly wrong. But the company’s response to that embarrassment is a sign of the culture changes that have happened at Microsoft over the last few years, as this piece from USA Today a while back points out. Microsoft isn’t afraid of failing, picking itself up, and trying again, and that’s admirable in an area as competitively intense as AI. It’s also interesting to watch these chatbots be launched into markets outside the US with other languages and/or accents (its other recent effort in this space is based in China). There’s a long way to go until these chatbots become really useful, but Microsoft seems determined to keep trying until it gets it right, while another early proponent, Facebook, seems to be changing its strategy lately.
via ZDNet
Google’s AI Explosion in One Chart – MIT Technology Review (Mar 27, 2017)
One of the big problems with evaluating which company is ahead or behind in a field like AI is that there are few external signals – companies work on a variety of AI projects behind closed doors in their R&D departments, and many of them only surface when they’re built into products and services they bring to market. Some have suggested using patents as a way to measure leadership, and this article cites publication in scientific journals as another. Certainly, Google’s publishing is a sign that there’s lots of work going on, but it also reflects the (deliberately) quasi-academic culture at DeepMind, its big AI acquisition, while Apple is also slowly moving in this direction with regard to AI specifically. Neither patent filings nor academic papers, however, have a direct connection to using AI to provide better products and services, and that remains very difficult to measure.
Tech community “dumbfounded” by Mnuchin’s dismissal of AI impact on jobs – Axios (Mar 24, 2017)
Treasury Secretary Steve Mnuchin said in an interview that he felt AI taking Americans’ jobs was 50-100 years away, and it wasn’t a concern in the present. Predictably, a whole raft of tech folk who work on AI and are very much aware of jobs being lost to AI today reacted rather poorly to that statement. At best, this feels like yet another government official who doesn’t have a good grasp on technology, something that’s been a worry with the current administration since before it took office. But at worst, this means the government is far less likely to take any meaningful action on helping protect American jobs that might be lost to AI or to retraining workers so that they can find new ones if their old ones go away. Whether you believe either of those things are the government’s job or not is largely a matter of your philosophy on the proper role of government, but at the very least you’d want the government to have a realistic sense of what kind of impact AI will have on jobs and when, in order to make an informed decision.
via Axios
Intel Consolidates its AI Teams (Mar 23, 2017)
Intel is announcing that it’s taking its various AI teams and consolidating them under Naveen Rao, who ran the AI company Nervana which Intel acquired last year. This feels like a sensible move from a company which has dabbled in AI in various parts of the organization but hasn’t become known as an AI powerhouse. Where things get slightly less credible is where Intel talks in the announcement about rallying the industry around a set of standards for AI as it has with past computational trends. Whereas Intel was a major player in personal computing, one of the examples it cites, it’s not nearly in the same position of influence with regard to AI, and so this feels like hubris rather than realism on what Intel’s role will be. Intel also talks, though, about bringing AI to more people, which sounds a lot like the “democratization of AI” message we’ve been hearing a lot from Microsoft lately, and which others including Google have also started parroting lately. This feels like it’s going to become an increasingly important theme in AI: less about individual companies owning capability and more about packaging up and making that capability available to anyone who wants to use it.
via Intel
A.I. Expert at Baidu, Andrew Ng, Resigns From Chinese Search Giant – The New York Times (Mar 22, 2017)
This story is notable for two reasons. Firstly, Baidu especially and Chinese companies in general are often overlooked completely in discussions of who’s making big investments in AI and machine learning, and yet Baidu has made massive investments in this area, and recently hired former Microsoft exec Qi Lu to be its COO and to oversee its AI efforts. Secondly, despite Qi Lu’s recent arrival, the trend of former Silicon Valley execs joining big Chinese tech companies still has fewer long-term success stories than short-term fizzles, as this article points out. Both Hugo Barra and Andrew Ng’s move to Chinese companies were seen as highly symbolic, and as such it’s inevitable that their departures should be too. The big Chinese companies are doing good work, and in some cases pioneering new product and service categories, across a number of different areas, but attracting and keeping high-profile talent from the US (even those with ties to Greater China – Ng was born in the UK to parents from Hong Kong) remains tough.
via New York Times
Samsung’s new virtual assistant will make using your phone easier – The Verge (Mar 20, 2017)
Samsung has somewhat unexpectedly taken the wraps off its virtual assistant Bixby ahead of next week’s Galaxy S8 launch, where I’d expected it to be the main event from a feature perspective. Based on how Samsung is describing the feature, though, I think it’s merely trying to defuse some hype by downplaying expectations of what Bixby will and won’t be. (The hype was fueled in part by Samsung’s acquisition of Viv, which was a more traditional virtual assistant that Samsung acquired last year, but Bixby appears to be something less.) The description from Samsung is somewhat vague, but I think the approach actually has a lot of merit: every other assistant promises to be just that, implying a broad-based ability to meet needs, which inevitably leads to disappointment and frustration when it falls short, over-promising and under-delivering. Samsung looks like it will come at this from the opposite end, starting small and building up functionality over time, app by app, in a way that the voice interface is able to handle everything the touch interface does in the same app. That, incidentally, should be good for accessibility, something Android devices have always done less well than iPhones. But the big limit there as with Bixby overall is that if third party developers don’t support it, it won’t be very useful, and it the S8 ships with the Google Assistant users may just choose to use that instead. I’m very curious to see next week exactly how Bixby is invoked and how it compares to the more traditional assistant model. Samsung doesn’t have a great reputation in software and services, and I’m skeptical that it will get this right.
via The Verge
Google Home is playing audio ads for Beauty and the Beast – The Verge (Mar 16, 2017)
This feels like an extremely stupid move for Google. Though Google claims this wasn’t an ad, that’s utterly disingenuous, and inserting ads this early in the Google Home lifecycle (if ever) is a huge mistake – this is just the kind of thing that will put people off buying a Google Home, especially because it fits a narrative of Google only being interested in advertising. This is a hardware product, for which users have paid a decent price, and it shouldn’t be playing ads, especially without an opt-out – there is no indication that users would hear ads in any of the marketing material. I just tried my own Google Home to see if it would play this message, but it didn’t, suggesting that Google may have stopped playing the message. If so, good, but it never should have happened in the first place, unless Google wants to kneecap its own product this early in its competition with Amazon’s Echo.
via The Verge
Amazon makes it cheaper to host Alexa skills on AWS – ZDNet (Mar 16, 2017)
This is clever tie-in by Amazon of two of its valuable assets: its Alexa skills engine and its AWS cloud infrastructure. It’s offering developers of Alexa voice skills a better deal on hosting through AWS as a way to remove the barriers to developing smarter and more sophisticated skills for its Echo devices (and the small number of third party devices using Alexa). Amazon has touted its number of third party skills repeatedly since launching them as a sign of Echo and Alexa’s capability, but the reality is that many of those skills are very basic, and the model is clumsy to use. If it’s able to attract better skills to the platform, those numbers will start to be more meaningful as signifiers of the platform’s capabilities.
via ZDNet
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.
via Reuters
Why Amazon Echo And Google Home Can’t Tell Who’s Talking–Yet – Fast Company (Mar 7, 2017)
This is a good counterpart to the Time article from last week about Amazon working on voice identification in their respective home speakers. It points out the complications in providing such a feature, not least that heavy processing to make voices clearer will also tend to distort them and therefore make it harder to recognize and distinguish speakers. The article also makes clear, though, that these challenges are far from insurmountable, which leads me to believe that Amazon or Google or both will eventually figure this out. In fact, whichever does figure it out first could have a big advantage, because for a lot of the most useful features (calendar, emails, etc) individual profiles are critical. So much so that Google misleadingly included that exact use case in its I/O launch video last year.
via Fast Company
‘Artificial Intelligence’ Has Become Meaningless – The Atlantic (Mar 6, 2017)
I’m actually linking to two articles here. The Atlantic article explicitly argues that there’s AI-washing going on and that lots of things are being described as AI which are in reality just computer programs. The Axios article is a little more neutral, pointing instead to a rapid rise in mentions of AI on earnings calls, and taking the upward trend more or less at face value, while attempting to explain what is enabling all the activity in the AI field at the moment. I think they’re both worth reading, but there’s no doubt in my mind that the AI term and its cousin machine learning are being over-applied at the moment, which risks devaluing true AI and real achievements it’s enabling. At least part of the rapid spike in AI mentions Axios cites is down to this over-application and a bandwagon-jumping mentality that serves no one well (least of all investors suckered into believing their investment is in AI and not just bog standard software). Unfortunately, there’s no way to stop this at this point, and I think the problem will only worsen, which will make it that much harder for companies to truly differentiate on the basis of AI claims. But it also reinforces my argument that companies really need to show and not just tell when it comes to AI – real user benefit and not AI capability itself is the key.
via The Atlantic and Axios (see also the Google is Ahead in AI and Apple is Behind in AI narratives)
Google Announces Progress in Using Deep Learning to Detect Cancer (Mar 3, 2017)
Yet another story about using either AI or deep learning (or both) to solve a real-world problem, from Google. This time, it’s an application miles away from any of Google’s current businesses (though perhaps a little relevant to some of the Other Bets), but the point is that Google is finding a very broad set of applications for its capabilities here, which can of course be applied back to lots of things which are relevant to the core Google business (as well as providing tangible human benefits if adopted by other organizations).
via Google