Ged Carroll

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  • Magic Leap + more things

    Magic Leap has shared an interesting concept video. Magic Leap that has technology which provides a more immersive experience, layered on top of the real world. It would be impressive if Magic Leap manages to pull it off. A demo are notorious for being the technology equivalent of snake oil salesmen who sell but can’t deliver. There’s even a name for it: vapour ware. I have no idea yet if Magic Leap is vapour ware. But the engineering challenges in terms of optics, software, power management and hardware are immense. More on web-of-no-web type experiences here.

    Once they have nailed the device, there is a requirement for content development. Lots of it. This also has implications for story telling.

    The Rise and Fall of China’s economy is a provocative title. The title was designed to be really good link bait rather than accurately reflecting the content of the video. The video actually does give a good background on how the Chinese economy has developed on a macro-level in a way that the interested non-economist would understand.

    I like the way Nestle has brought on board a gingerbread man character to advertise Coffee Mate in the US. There has been a move away from mascot-type figures in marketing in general. This is a really nice counterpoint to that trend.

    Nikon seem to be reaching out to millennials with this profile of a skateboard photographer, it is likely to appeal to a contingent of generation X too.

    It targets a very different type of photographer who would wouldn’t be impressed by the traditional photography ‘personalities’ from Rankin to Dave Lee Travis (Leica paid him good money back in the day, apparently he was interested in bird-watching).

    This is a world away from the first skating video shot by Stacy Paralta back in the mid 1980s, with grainy low-fi VHS cameras.

    Really nice mobile experience: Sync! Illumination lets you watch Tokyo Disneyland Electrical Parade from home on multiple phones

  • WeChat Life Report

    Chinese consumers literally live a WeChat life as shown by this great  collection of consumer behaviour data on WeChat. Over the past year WeChat has expanded the services that it provides to include Skype like conference calls, which changes and expands the behaviour in this report. (Presentation on Slideshare)

     

    Key takeouts

    • The ubiquity of WeChat can’t be over stated with over 93% usage in tier one cities. It will grow over time in lower tier cities for a couple of reasons. There will be a network effect that will reach out of the tier one cities and into the lower tiers and countryside. Secondly, WeChat services will start to permeate out of the tier one cities and into the lower tiers. You will then have a virtual cycle due to network effects and ever-increasing ubiquity
    • Call and message data shows how it binds the diaspora back to friends and loved ones in China. The Chinese talk about ‘near and far networks’. But WeChat closes the gap, meals can be shared with photos and videos. Voice messages popular with older users also helps with asynchronous communications over difficult time zones
    • Chinese people tend to exercise during the week, rather than at the weekend according to WeChat fitness data. The idea being for rest is an insight and an opportunity for fitness and sports apparel companies
    • Male shoppers spending 30% more than female shoppers  was an interesting statistic emblematic of WeChat life. Generally men are not as enthusiastic a shopper as women are. They have to save for a home, a car and marriage. My take was that women offer WeChat a growth opportunity in payments; if it can address the underlying cause of this disparity
    • The average social circle on WeChat at 128 is very close to the Dunbar number

    More on WeChat here.

  • Nudges + more things

    The Power of Nudges, for Good and Bad – NYTimes.com – how loss aversion and other behavioural traits  (or nudges) can be used as methods for social change and political change. These elements have already been used in UK government projects and the advertising world. They are the reason why games are addictive and so is swiping on Tinder. (paywall) – more on consumer behaviour including the impact of nudges here.

    Chat App Firm Line Focuses On Services After Adding Just 1M MAUs In 3 Months | TechCrunch – I don’t think that this is as bad as the TechCrunch seems to think. US focused services and China focused services are about the advertising eco-system and scale.  LINE hasn’t really tried to blow out the market penetration beyond Asian markets yet. It does really well in places like Thailand, Taiwan and Japan. It is also a media franchise rather like Sanrio, given the licenceable nature of its sticker characters like Brown. Also ARPU (average revenue per user) is as important as numbers – profit share vs. market share. This has been demonstrated in other sectors such as the smartphone market, where Apple has historically earned 70 to 90 percent of smartphone profits from just 15 percent market share.

    U.S. Technology Device Ownership 2015 | Pew Research Center – good data points on device usage by US consumers.

    Hong Kong pupils at risk of ‘becoming like Foxconn workers’ in education system, says former principal – it is problematic for two reasons. Firstly, that kids will be put in such a high stress position by the Hong Kong education system. The second reason is that Foxconn as become a verb for stressful conditions. That is damaging for both Hon Hai Electronics and their customer base. The idea of damaging stressful conditions being so tightly linked with the company name is damaging. It’s like a really bad version of ‘Hoover’ and vacuum cleaner linkage.  (paywall)

  • Beehives + more news

    Melixa | Innovative smart beehives for remote monitoring – beehives as smart cities for bees. I wonder if this is will do anything for colony collapse disorder (CCD) ravaging beehives around the world.

    Google combining Android and Chrome is bad for developers – Business Insider – my problem with tablets is their ‘lugablity’. I found the original iPad too big

    Microsoft has trapped its biggest partners between a rock and a hard place (MSFT) | BusinessInsider – “The Surface Book will have a harder time stealing away MacBook users,” says Linn Huang, an analyst for IDC. “The Apple brand has been sticky, and I don’t have much cause to think it won’t continue to be in the immediate future.” – whilst it might appeal to enterprise customers, it is also a big threat to existing Microsoft OEMs. There is a larger question about whether the touch interface is the right context for a lot of laptop work, which is one of the reasons why Apple has kept iOS and OSX separate despite their Darwin / BSD / Mach microkernel guts

    Why Windows XP Won’t Be Going Away Anytime Soon | Makeuseof – interesting challenge that Microsoft has in that its greatest competitor is is older products

    ‘Can’t hide it forever’: The model who became a meme – BBC News – I can’t see JWT coming out of this well

    Carrier DT Targets Startups After Europe Agrees Net Neutrality Rules | TechCrunch – inevitable based on the recent EU regulatory changes

    Nexus 6P Teardown – iFixit – interesting teardown, appalling repairability. More gadget related content here.

    Mead Johnson dives into parenting issues using WeChat | Marketing Interactive – influential parent campaign on WeChat

    BuzzFeed Press Blog – A cross-platform global network – interesting vision piece on the future of Buzzfeed by Jonah Peretti

    WeChat Still Way Ahead of Facebook | L2: The Daily – really good slideware on messaging platform

  • Learning machines discussion

    Why learning machines? Simply because I don’t want to get into an argument of what an AI actually is, so hence the title change – but interesting watching.

    The Churchill Club manage to get top drawer panelists for this session on learning machines

    • Yoshua Bengio, Professor, Department of Computer Science and Operations Research, Universite de Montreal
    • John E. Kelly, Senior Vice President, Solutions Portfolio and Research, IBM

    The panel was moderated by long time New York Times technology journalist  John Markoff.

    Key takeouts for me were:

    Cycle since the 1950s of over-promising and under delivering that drove nuclear winters and booms. Current cycle goes back to the DARPA autonomous vehicle competitions of the past decade. Neural networks weren’t seen as ‘AI’, they went out of research fashion in the 1990s and research picked back up in 2005. Deep learning is basically layers of neural network – more layers = ‘deeper’. Deep nets are now the standard for learning machines. Object recognition improved in 2012 and both industrial and media interest took off.

    Performance has been helped by improved hardware, which has driven the breakthroughs.

    Learning machines still need a lot of human guidance, unsupervised learning isn’t doing as well. It probably explains why IBM has so many people working on Watson projects. This also explains why Watson is externally seen primarily as a ‘marketing concept’.

    Rate of change in semiconductors. Moore’s Law is likely to top out at 5nm. Carbon nanotube devices will be the new silicon in semiconductors. Quantum computing will drive performance in certain types of calculations by a factor of 20. Graphene is better for analogue devices, nanotubes are better for switching. The cost of transistors has stopped falling, which has an implication for new disruptive industries.

    We’ll get performance and density, the cost of which is more uncertain. Computing power is important for learning machine technologies. Power consumption (computing power per watt) is tremendously important. IBM Watson on Jeopardy used 85,000 watts to beat two 20 watt humans.

    Back propagation allows the use of lower power processors. Speech and vision are areas of a big push, but the most exciting area is language recognition and understanding with recurrent networks – implications for conversational interfaces and services.

    IBM think cognitive computing is a wider area than ‘machine learning’. Cognitive computing is what IBM think will transform ‘digital transformation’ through learning machines.

    AI has a definition problem due to fashion and academic quarrels.

    Watson was originally designed to deal with massive unstructured data rather than building an AI. Data was growing faster than IBM could develop for. Watson had a data centric focus. It sounds rather like the vision I once heard articulated for both Autonomy and Palantir.

    Consumers will see Watson as ‘insights’. Watson as a learning machine focuses on comparing and contrast to try and find patterns.

    Interesting that IBM went in so hard on healthcare as an example, given how they eventually retreated from the sector after scandals over unsafe diagnosis.

    UPDATE: October 6, 2020 – report on AI progress here.

    More technology related content here.