This month: //The humans behind the chatbots //Total transition to autonomous electric vehicles //(Stop) talking about false meat //The end of forecasting //...and space junk.
New Zealand’s Prime Minister Bill English saw the future at Christchurch’s EPIC building (which also houses Memia) as part of this month’s NZ Techweek programme. Nice work by AR/VR specialist Corvecto, even attracting the unforgiving attention of John Oliver. (Note to self: make sure there are no cameras around next time I put on a VR headset!).
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AR 25%, VR 75%
“Our base case software scenario is driven 75 percent by VR use cases vs 25 percent for AR use cases,” said a Goldman Sachs research report driving Microsoft’s strategic shift away from enterprise AR towards consumer VR, at least for a few years yet: What Happened to the Amazing HoloLens Future We Were Promised?
Idealab’s CEO Bill Gross writes up his takeaways from this year’s TED conference. In particular AI expert Noriko Arai’s talk about how she’s building an AI that can take (and pass) the University of Tokyo entrance exam, including reading and writing essay questions.
As a user of Clara for over a year now, HI+AI services continue to improve. But how much is HI and how much AI? BloombergTech goes behind the scenes and investigates The Humans Hiding Behind The Chatbots.
More on the BMI debate kicked off by Elon Musk’s Neuralink announcement: Wait but actually why: Brain-Machine Interfaces and Unit Economics of Human Output
And my own contribution from this month: Why Neuralink and Kernel are trying to solve the right problem at the wrong time
Huge fan of Jeff Hawkins and his team’s work at Numenta decoding how the neocortex works and reverse engineering it into software – here’s a rough early preview video of their latest work introducing a new concept in Hierarchical Temporal Memory (HTM): The Neuroscience Behind HTM Sensory Inference
Meanwhile… for those who want to learn more Machine Learning, FreeCodeCamp’s David Venturi published Every single Machine Learning course on the internet, ranked by your reviews. Background: “A year and a half ago, I dropped out of one of the best computer science programs in Canada. I started creating my own data science master’s program using online resources. I realized that I could learn everything I needed through edX, Coursera, and Udacity instead. And I could learn it faster, more efficiently, and for a fraction of the cost.” A superb resource, traditional universities should feel very afraid.
Roads, Roads and Less Roads
Recently the government here in New Zealand announced a big pre-election spendup on “infrastructure” – a euphemism for “more roads”.
The NZ Ministry of Transport is admirably transparent on its website about the investment and costs associated with roading: NZ$4Bn per year on the “Land Transport System”. Four. Billion. Dollars. (NZ GDP is NZ$260Bn).
This has set me thinking about how advances in transportation technology could start to be applied now not only to significantly reduce the amount being spent, but to deliver better outcomes for everyone. Auckland’s traffic woes are an example where more roads are not going to solve the problems even today. And flying cars ain’t going to cut it any time soon either.
StartupGrind’s Geoff Nesnow wrote a neat summary last year of 50 implications of driverless cars (and trucks).
Implication no. 21: “Roads will be much emptier and smaller since self-driving cars need much less space between them (major cause of traffic today), people will share vehicles more than today (carpooling), traffic flow will be better regulated and algorithmic timing (i.e. leave at 10 versus 9:30) will optimize infrastructure utilization”.
A recent analysis from thinktank RethinkX predicts an extremely disruptive, total transition to EV / autonomous vehicles in 13 years.
Are any government transport agencies around the world modeling a decline in road usage in the future?
How about borrowing the concept of Negawatts – the amount of power saved from improved energy efficiency – and apply it to road usage – “NegaKm” is the car and truck journey km (and journey times) saved from more efficient and timely road use.
One key tool could be reverse-road-pricing: Rather than spend tens of millions of dollars widening a highway, how about holding that money and rewarding people to stay off that road during peak hours? Surely simple enough to trial for a year, registration through a mobile app and you’re away…Surely…?
Future of Food
More agri agitprop from provocateur-in-chief Rosie Bosworth: interview on NBR radio podcast on Why New Zealand is becoming the Detroit of Agriculture. (Nice turn of phrase, wonder who came up with that :-)). Synthetic biology (synbio) will disrupt the traditional (and, let’s face it, hugely inefficient, polluting and fundamentally unsustainable) pastoral agricultural model and maybe even allow countries such as NZ to meet our Paris Agreement commitments of net-zero greenhouse gas emissions by 2050.
(Incidentally, I was in a meeting recently when the conversation turned to synbio – one of the bankers in the room – maybe starting to feel a bit exposed – said “let’s stop talking about false meat“. Unlikely.)
More future food:
Startup Nutrient Rescue launched their plant-based wholefood powder shots – 5-10 serves of fruit and veges for $2, takes less than 1 min to prepare. Using.
Functional food leader Soylent raised a $50M Series B round led by GV (Google Ventures). “Soylent is addressing one of the biggest issues we face today: access to complete, affordable nutrition”.
Turning Facebook data into money
“…is harder than it sounds, mostly because the vast bulk of your user data is worthless. Turns out your blotto-drunk party pics and flirty co-worker messages have no commercial value whatsoever.” – I’m an ex-Facebook exec: don’t believe what they tell you about ads
The Half-Life Of Forecasting?
The World Economic Forum published an article on The End Of Forecasting? Given the increasing mainstream acceptance of accelerationism and predictions like “The next double-century (2000-2200) promises no fewer than 150 breakthrough innovations on par with the steam engine, antibiotics and the airplane” – the article argues that
long-term forecasting is simply becoming obsolete and we need to adapt to a post-forecasting era.
Alternatively…the meaning of the phrase “long term” has a half-life attached to it: as technology-driven change accelerates, so our view out to the future shortens. But we can still forecast out effectively for the same order of magnitude change as previously – it’s just this will take exponentially less time to happen.
Sometimes the future doesn’t seem so bright:
There’s a link in the WEF article above to a thought-provoking tweet quoting AliBaba founder Jack Ma – as we all live longer, the need may emerge to legislate for a maximum human lifespan.
And finally, here’s a hypnotic (12 mins) video from the European Space Agency showing manmade objects journeying from the outer solar system back to Earth.
More again next month – Comments, feedback, suggestions? Email email@example.com