Humans are good at tasks which require dexterity and manipulation of flexible materials (like thin tubes or fabric), but often these detailed tasks are associated with big, heavy "chunks" of other things (such as wiring up a heavy car dashboard before dropping it in to place). Typically, people and industrial robots are kept separate to avoid catastrophic injuries, but a new class of robot which is "aware" of its working environment and can react accordingly (e.g. slow down when a human moves closer) promises to make robots even more useful, taking control of the heavy lifting and allowing humans to focus on the complex, fiddly work.
Artificial intelligence can turn the most dangerous industrial robots into helpful coworkers, and that could transform manufacturing.
The move to a cashless society is making steady progress across most of the world. In the UK, for example, more than 50% of transactions were completed cashlessly last year (https://rob.al/2yzozhH), while in China, UnionPay's rapid push in to new markets (as diverse as Malaysia, DRC, and Kazakhstan https://rob.al/2Kd4sdL) demonstrates the sheer scale of the opportunity, with the pace of change hardly altered by the introduction of a new competitor (NetsUnion https://rob.al/2IhFMvN). But there's rightly growing concern about those being left behind (https://rob.al/2KcwHti) and the solutions for that problem are yet to be discovered.
UK spending on debit cards overtook hard currency for the first time in 2017
Recognising AI as a "general-purpose machine", rather than a distinct and immediately implementable tool or technique, can help explain why the anticipated gains are not yet being seen. With the introduction of other general-purpose machines, like the electric motor, the computer, the steam engine, it took decades for companies and industries to identify how they needed to change – simply automating an existing business process is unlikely to give massive benefits. Rethinking how an organisation achieves outcomes independent of the existing process or tooling is – but it'll take many more years to materialize.
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Novel new approaches to the use of AI – highlighting its use as an augmentation to human judgement, not a substitute – are welcome, but still fall far short of addressing the elephant in the room – most machine learning or AI today is still pure statistical inference, often without even implicit acknowledgement of the path of causation (grass grows when the sun shines – but which causes which?). Until this problem question is addressed, even the new approaches outlined in this article will just be fitting data to a curve.
A branch of A.I. called deep learning has transformed computer performance in tasks like vision and speech. But meaning, reasoning and common sense remain elusive.
It's an often overlooked problem, but although electric vehicles produce zero emissions at point of use, and can be powered entirely with emission free fuel (e.g. renewable power sources), they still contain a lot of rare materials, often mined or produced under somewhat questionable ethical standards, so it's great to see how the world is starting to respond.
Conamix, a little-known startup based in Ithaca, New York, has raised several million dollars to accelerate its development of cobalt-free materials for lithium-ion batteries, the latest sign…
Although i was aware of the benefits of sparsely connected neural networks, this paper outlines an additional, slightly counter-intuitive property – scale-freeness through a method they call "Sparse Evolutionary Training). Starting from a sparse network, the model randomly adds new connections and drops weaker ones, "evolving" in to a more model which is more complex to define, but ultimately simpler, with fewer "hubs" (scale-freeness), and this less densely connected end state is quicker to stabilise (as it requires fewer calculations) and to maintain and train than a traditional statically connected network.
An international team of scientists from Eindhoven University of Technology, University of Texas at Austin, and University of Derby, has developed a revolutionary method that quadratically…
As Sweden turns to an increasingly cashless society, criminals are having to find other ways to line their pockets. Last year a high profile string of robberies of moving trucks of Apple merchandise (https://rob.al/2Ji51CR) were finally bought to an end by a police sting, but now criminals have started catching and selling endangered species – some can go for around $120,000 per animal.
As the country ditches cash, some criminals turn to stealing owls.
Uber plans to launch a flying car service ("Uber Elevate"), predicting it'll be ready around 2025 – progress is being further accelerated by a $20M investment in a dedicated Research and Development site in Paris, Uber's first technology centre outside the US, focusing on research in to airspace management and overcoming the legal and practical issues this brings up (do you really want hundreds of flying cars zooming over your home?)
Ride hailing app Uber wants to build flying taxis in France and announced on Thursday it would invest €20 million to develop the project.
It’s becoming increasingly apparent that Level 2 “self driving” cars are quite simply dangerous. The most recent incident (involving a Tesla model S which crashed in to a parked police car) has highlighted that partially automating the complex task of “driving” is potentially worse than not automating it at all (https://rob.al/2kGyxUS). But the “paradox of automation” is not a new phenomena – economist Tim Harford has previously written about this problem (https://rob.al/2kFZB6O), and Alphabet has chosen to skip Level 2 automation entirely, heading straight for vehicles which need no human intervention at all (“level 4” and beyond) https://rob.al/2sujOjo
The impact of self-driving cars will be felt far and wide. Aside from the obvious (insurance industry, petrol stations, professional drivers, crash repair centres), CB Insights points out that seemingly disconnected industries – like fast food, real estate, media and healthcare – are also set to be jolted from their comfort zones. Not all of these are negative – if you could watch movies while being shuttled around that's a boon for those who tell internet access and streaming services. Others are more subtle – how the price of real estate will be affected is as yet unclear (and how will that impact public transport?)
Fast food, real estate, military operations, even home improvement — many large industries will have to shift their strategies in the wake of driverless cars.