Thursday, December 21, 2017

Friday Thinking 22 Dec. 2017

Hello all – Friday Thinking is a humble curation of my foraging in the digital environment. My purpose is to pick interesting pieces, based on my own curiosity (and the curiosity of the many interesting people I follow), about developments in some key domains (work, organization, social-economy, intelligence, domestication of DNA, energy, etc.)  that suggest we are in the midst of a change in the conditions of change - a phase-transition. That tomorrow will be radically unlike yesterday.

Many thanks to those who enjoy this.
In the 21st Century curiosity will SKILL the cat.
Jobs are dying - work is just beginning.

“Be careful what you ‘insta-google-tweet-face’”
Woody Harrelson - Triple 9


Content
Quotes:

Articles:




Every large and successful institution has an immune system – a collection of individuals who are prepared to mobilize at the slightest sign of any “outside” ideas or people in order to ensure that these foreign bodies are neutralized and that the existing institution survives intact and can continue on course. Just like the immune system all organisms have, this institutional immune system is adept at recognizing foreign bodies as soon as they appear and very effective at protecting the institution from infection. It is in fact what has helped large institutions to survive – they are in fact “built to last.”

But here’s the paradox: the immune system that has given large institutions extraordinary resilience in the past may be the very thing that makes these institutions so vulnerable today. In more stable times, institutional immune systems are very effective at keeping institutions focused and on course, resistant to the distractions that might lead to their downfall. In more rapidly changing and volatile signs, this same immune system can become deadly by resisting the very changes that are required for the survival of the institution.

John Hagel - Never Under-Estimate the Immune System




History is full of examples of the relationship between reverie and creativity. Here is one, idiosyncratic example: the German art historian Aby Warburg (1866-1929) organised his library of 50,000 books with the aim of promoting mind-wandering. His collection was the kernel for the Warburg Institute in London, where we now work as researchers. Each of the library’s four floors is devoted to one of four themes – image, word, orientation, and action – and separated into sub-themes, such as ‘magic and science’, ‘transmission of classical texts’, and ‘art history’. Guided by Warburg’s ideas about what makes a good neighbour for a book, this unique approach to classification allows a withered 17th-century medical tome to cluster next to texts on mathematics, the cosmos and harmony. The shelves promote intellectual serendipity as you skip from the book (or thought) you thought you wanted, to another intriguing idea or topic that hadn’t even occurred to you.

‘Let the soul dangle’: how mind-wandering spurs creativity




….Fuchs calls the “conative” – the emotional energy drawing one into the future, toward certain possibilities and away from others. Healthy conation contains an energetic undercurrent of aliveness and self-affection, perceived as being drawn into the future. Picture a large, happy golden retriever exploring a new park. However, healthy conation is also capable of subtle discrimination: some future courses are felt to be desirable, others repellant. That golden retriever would do well to be less enthusiastic approaching, say, a bear, than approaching another goofy dog. In humans, taking the perspective of others is an important check on what to pursue and what to avoid. Dogs seem to do this too, watching a human or other dog’s body language for cues on how to feel about a situation.

….Without conative energy, there is no emotional reason to do any particular thing. In order to function, depressed people must substitute conscious willpower for the lost human capacity of implicit enjoyment and desire.

Feeling the Future




You're probably familiar with the distinction between clock time and event time, which loosely corresponds to the chronos vs kairos distinction in classical Greek thought. Industrial work couples the two with disciplined, tight coordination or synchronization. Work is organized along multiple pathways of event time, and one of them, the critical path, drives the rest, via a coupling to clock time. This creates a single "event-time zone" for the shared work context.... In industrial work, when the discipline is strong you get lean conditions and economies of scale and scope. When the discipline is weak, you get fat conditions and economies of variety. A shared sense of delays/slack/urgency collapses, and the single event-time zone frays into many. Industrial work is disciplined and lean by default ("normal") and sloppy and fat via deviance. It is a paradigm within which exploration and trial and error are pathologized as deviant behaviors, tolerated briefly at best.

Post-industrial work, because it centers exploration and trial and error as normal, and tight synchronization as deviant, flips the valuation. One really powerful way to think about this is that in true trial-and-error exploration regimes, every path is a critical path. ... Since you don't know what the eventual convergent goal might be, or indeed, whether there is even a single convergent goal beyond the fog, there can be no single critical path to rule the rest. Clock and event time are coupled differently. Each path's event time evolves independently, and convergence requires a very non-trivial "merge" operation. Between forks and merges, each local path segment maintains its own relationship with clock time. Concepts like being delayed or "late" only make sense when a single critical path creates a global event time. When there isn't one, merges are conflicts between little local realities that have their own sense of time.

When every path is critical




A report from Intel predicts the rise of a new “passenger economy,” worth a jaw-dropping $7 trillion by 2050. The bulk of that revenue would derive from ride hailing and the freight industry.

Some $200 billion would consist of goods and services provided to people during their rides in robot taxis. Think manicures, massages, lattes, fast-casual meals, mobile health care, remote meetings, immersive digital entertainment. (Intel doesn’t mention it, but practitioners of the world’s oldest profession might ply their trade in self-driving cars as well.)

Robot cars may kill jobs, but will they create them too?




Japan’s population is shrinking, and its economy is booming; the unemployment rate is currently an unprecedented 2.8 percent. “Using robots makes a lot of sense in a country like Japan, where it’s hard to find employees,” CEO Hideo Sawada told me.

Sawada speculates that 70 percent of the jobs at Japan’s hotels will be automated in the next five years. “It takes about a year to two years to get your money back,” he said. “But since you can work them 24 hours a day, and they don’t need vacation, eventually it’s more cost-efficient to use the robot.”

This may seem like a vision of the future best suited—perhaps only suited—to Japan. But according to Michael Chui, a partner at the McKinsey Global Institute, many tasks in the food-service and accommodation industry are exactly the kind that are easily automated. Chui’s latest research estimates that 54 percent of the tasks workers perform in American restaurants and hotels could be automated using currently available technologies—making it the fourth-most-automatable sector in the U.S.

at Zume Pizza, in Mountain View, California, where I watched an assembly line of robots spread sauce on dough and lift pies into the oven. Thanks to its early investment in automation, Zume spends only 10 percent of its budget on labor, compared with 25 percent at a typical restaurant operation. The humans it does employ are given above-average wages and perks: Pay starts at $15 an hour and comes with full benefits; Zume also offers tuition reimbursement and tutoring in coding and data science.

Robots Will Transform Fast Food




The net neutrality battle has been exhausting. It has come at enormous cost in time, energy, attention, and money.
Fundamentally, the net neutrality fight is one where the best possible outcome is preserving the status quo: an internet landscape and connection infrastructure that is dominated by big telecom monopolies. Simply put, the internet is too important to rely on politicians and massive corporations to protect it.

In order to preserve net neutrality and the free and open internet, we must end our reliance on monopolistic corporations and build something fundamentally different: internet infrastructure that is locally owned and operated and is dedicated to serving the people who connect to it.

The good news is a better internet infrastructure is possible: Small communities, nonprofits, and startup companies around the United States have built networks that rival those built by big companies. Because these networks are built to serve their communities rather than their owners, they are privacy-focused and respect net neutrality ideals. These networks are proofs-of-concept around the country that a better internet is possible.

Motherboard & VICE Are Building a Community Internet Network




This is a 30 min video presentation by Stuart Kauffman - an excellent weak signal of a fundamental paradigm change in our understanding of mind and reality - through an advance in applying quantum concepts to biology. There is much that Kauffman forthrightly admits is very speculative - however, it remains an important contribution. Worth the listen to anyone interested in questions of consciousness, mind and quantum.

Mind Body Quantum Mechanics, Stuart Alan Kauffman

Neurobiologists believe the mind brain system is and must be classical physics. For many, at some complexity, consciousness arises. This could be correct but faces what I will call the Stalemate: Such a mind can at most witness the world but, due to the causal closure of classical physics, cannot act upon that world. Such a consciousness must be merely epiphenomenal.

Quantum biology is exploding, showing that quantum effects can and do arise at body temperature. Quantum mechanics allows a partially quantum mind to have ACAUSAL consequences for the “meat” of the brain, thus solving the Stalemate and answering the problem posed by Descartes’ Res cogitans and Res extensa: i.e. the Stalemate. Our human capacity to choose, in turn, demands that the present could have been different, thus the truth of counterfactual claims. If quantum measurement is indeterministic and real, quantum mechanics and measurement allow the present to be different. I shall discuss these issues and the newly discovered Poised Realm, hovering reversibly between quantum and “classical” behaviors, as a new basis both for the mind body system and a new class of constructable and evolvable “computers” which are not algorithmic, Trans Turing.


This is an interesting signal related to the emerging infrastructure of all things mobile and all things ‘IoT’ (Internet of Things).

What is edge computing?

Edge computing will signal a move from what is traditionally understood to be the cloud – but what exactly is it, what’s it good for, and who are the main players?
Another shift in the technology landscape appears to be underway which has the potential to dramatically alter the way data is created and processed.

Edge computing is, in essence, tied to the evolution of the internet of things (IoT). As various industries push to connect previously dumb objects to the internet, the way in which these objects talk to one another will change.

An edge device could be anything that provides an entry point to a network, for example, routers, WANs and switches. They will act as miniature data centres, able to communicate with one another – to form a 'fog' – and typically will be used for communicating urgent data.

For example, think of applications in automotive, manufacturing, fleet management, emergency and disaster response, where it is simply not prudent to transmit data back to a central data centre.

This will enable 'fog computing', a relatively recent term used to describe decentralised computing happening at the level of the object which requires data processing, rather than pinging complex requests to data centres that can be hundreds of miles or more away.


This is a 4 min video by John Hagel that speaks of two types of disruption (I think these are both based on the costless coordination of the digital environment). Each type of disruption is worth considering no matter what type of organization or business.

Deloitte Patterns of Disruption

The term disruption is used very loosely and can mean virtually anything, ultimately for many people it’s anything new becomes disruptive. Center for the Edge believes there’s value in having a more rigorous definition of disruption and so our definition has to do with the ability to unseat the incumbent leaders in a market place by adopting a new approach to the business that is very challenging for the incumbents to adopt themselves. Explore the patterns and corresponding case studies


The idea of disruption is a very important one especially as we’ve entered into the world of platforms and costless coordination. Network effects can breed path dependence which incentivizes more investment - until ubiquitous sensors, devices, data, algorithm, software and more - become an environment of new infrastructure beyond the private ownership.

Can Facebook and Google Be Disrupted?

“Self-reinforcing” is the key problem of the power dynamic inside Silicon Valley. Google’s size is inextricable from its success; the more people that search, the better its results are. A similar loop plays out on Facebook: The more friends that sign on, the better it is to use; the better it is to use, the more people sign on to it. This is the result of “network effects”: the well-known idea that for some services, quality relies in a large part on their ability to build broad networks. For social networks, search engines, ride-share services, and OS companies alike, a large network of users is fundamental to success — and a large network of users is about the one thing you can be sure that a new start-up won’t have. How can Google be disrupted if network effects mean its dominance will only lead to more dominance — and if you need a Google-size network to compete?

But network effects work both ways, as when users leaving Myspace in droves led even more users to leave, helping turn it into the relic it is now. While network effects may be instructive in understanding how the current crop of large-platform companies got where they are, they don’t entirely explain why those companies are so effective at holding their positions and making it hard for users to leave. Robyn Caplan, a researcher at Data & Society, suggests that it may be helpful to think of how they do this using another concept: path dependence, “which holds … that once a country or society has started down a particular road, the costs of reversal are very high.”

Network effects can help create path dependence, but they aren’t some sort of foolproof method for maintaining it. That requires the work that platforms like Facebook and Google have done getting other industries to buy into what Caplan describes as “the social and economic relationships that have been forged between publishers, platforms, intermediary ad companies, analytics companies,” and so on. For instance, media companies have spent so much time and money training employees on how to distribute articles and videos on Facebook, as well as how to use a specialized type of cookie called the Facebook pixel and other products developed by Facebook to garner whatever traffic they can, that they’re now extremely path dependent on the company and its products.

Of course, they’re not the first companies to recognize the potential of a platform business model — AOL and Microsoft both made a run at platform dominance in the 1990s. But Microsoft was, to use Pasquale’s phrase, “softened up” by antitrust actions taken against it by the U.S. government. AOL, for its part, entered a period of decline because technology broke the moat it had built around its users — once people switched to broadband from AOL’s dial-up connection, they weren’t spending most of their time inside the company’s walled garden of content anymore. This kind of sea change in technology is the likeliest path to the downfall of this era’s giants. But where widespread broadband internet was the kind of technological development that opened up the playing field for smaller and less well-funded start-ups, the exciting new technologies on the horizon — machine learning, self-driving cars, and augmented or virtual reality — all require enormous investments, not to mention the kind of vast troves of data only available to the biggest and most successful companies in Silicon Valley.


Another signal in the current swarm of concern about AI - this one is longish but David Weinberger is always worth paying attention to.
AI = Artificial Intelligence? Algorithmic Intelligence? Alien Intelligence?
Models are always reductive: They confine the investigation to the factors we can observe and follow. For thousands of years we acted as if the simplicity of our models reflected the simplicity — the elegance, the beauty, the pure rationality — of the universe. Now our machines are letting us see that even if the rules are simple, elegant, beautiful and rational, the domain they govern is so granular, so intricate, so interrelated, with everything causing everything else all at once and forever, that our brains and our knowledge cannot begin to comprehend it. It takes a network of humans and computers to know a world so thoroughly governed by contingency — one in which it’s chaos all the way down. And up.

OUR MACHINES NOW HAVE KNOWLEDGE WE’LL NEVER UNDERSTAND

The new availability of huge amounts of data, along with the statistical tools to crunch these numbers, offers a whole new way of understanding the world. Correlation supersedes causation, and science can advance even without coherent models, unified theories, or really any mechanistic explanation at all.
So wrote Wired’s Chris Anderson in 2008. It kicked up a little storm at the time, as Anderson, the magazine’s editor, undoubtedly intended. For example, an article in a journal of molecular biology asked, “…if we stop looking for models and hypotheses, are we still really doing science?” The answer clearly was supposed to be: “No.”

But today — not even a decade since Anderson’s article — the controversy sounds quaint. Advances in computer software, enabled by our newly capacious, networked hardware, are enabling computers not only to start without models — rule sets that express how the elements of a system affect one another — but to generate their own, albeit ones that may not look much like what humans would create. It’s even becoming a standard method, as any self-respecting tech company has now adopted a “machine-learning first” ethic.

We are increasingly relying on machines that derive conclusions from models that they themselves have created, models that are often beyond human comprehension, models that “think” about the world differently than we do.

But this comes with a price. This infusion of alien intelligence is bringing into question the assumptions embedded in our long Western tradition. We thought knowledge was about finding the order hidden in the chaos. We thought it was about simplifying the world. It looks like we were wrong. Knowing the world may require giving up on understanding it.


This is a marvelous essay by Kevin Kelly - a good antidote to the raging panic about looming AI. Not that there aren’t serious concerns - but real problems are less about AI and more about human weaponizing AI.

The AI Cargo Cult - THE MYTH OF A SUPERHUMAN AI

I’ve heard that in the future computerized AIs will become so much smarter than us that they will take all our jobs and resources, and humans will go extinct. Is this true? That’s the most common question I get whenever I give a talk about AI. The questioners are earnest; their worry stems in part from some experts who are asking themselves the same thing. These folks are some of the smartest people alive today, such as Stephen Hawking, Elon Musk, Max Tegmark, Sam Harris, and Bill Gates, and they believe this scenario very likely could be true. Recently at a conference convened to discuss these AI issues, a panel of nine of the most informed gurus on AI all agreed this superhuman intelligence was inevitable and not far away.

Yet buried in this scenario of a takeover of superhuman artificial intelligence are five assumptions which, when examined closely, are not based on any evidence. These claims might be true in the future, but there is no evidence to date to support them. The assumptions behind a superhuman intelligence arising soon are:
  • Artificial intelligence is already getting smarter than us, at an exponential rate.
  • We’ll make AIs into a general purpose intelligence, like our own.
  • We can make human intelligence in silicon.
  • Intelligence can be expanded without limit.

Once we have exploding superintelligence it can solve most of our problems. In contradistinction to this orthodoxy, I find the following five heresies to have more evidence to support them:

  • Intelligence is not a single dimension, so “smarter than humans” is a meaningless concept.
  • Humans do not have general purpose minds, and neither will AIs.
  • Emulation of human thinking in other media will be constrained by cost.
  • Dimensions of intelligence are not infinite.
  • Intelligences are only one factor in progress.

If the expectation of a superhuman AI takeover is built on five key assumptions that have no basis in evidence, then this idea is more akin to a religious belief — a myth. In the following paragraphs I expand my evidence for each of these five counter-assumptions, and make the case that, indeed, a superhuman AI is a kind of myth.


This is a great signal about the paradigm change that Blockchain technologies have enabled and the ongoing evolution of these technological approaches to accounting for value creation and exchange. This also provides another way to understand the 21st century as the century of ‘entanglement’.

A Cryptocurrency Without a Blockchain Has Been Built to Outperform Bitcoin

The controversial currency IOTA rests on a mathematical “tangle” that its creators say will make it much faster and more efficient to run.
Bitcoin isn’t the only cryptocurrency on a hot streak—plenty of alternative currencies have enjoyed rallies alongside the Epic Bitcoin Bull Run of 2017. One of the most intriguing examples is also among the most obscure in the cryptocurrency world. Called IOTA, it has jumped in total value from just over $4 billion to more than $10 billion in a little over two weeks. But that isn’t what makes it interesting. What makes it interesting is that it isn’t based on a blockchain at all; it’s something else entirely.

The rally began in late November, after the IOTA Foundation, the German nonprofit behind the novel cryptocurrency, announced that it was teaming up with several major technology firms to develop a “decentralized data marketplace.”

A what, now?
Though IOTA tokens can be used like any other cryptocurrency, the protocol was designed specifically for use on connected devices, says cofounder David Sønstebø. Organizations collect huge amounts of data from these gadgets, from weather tracking systems to sensors that monitor the performance of industrial machinery (a.k.a. the Internet of things). But nearly all of that information is wasted, sitting in siloed databases and not making money for its owners, says Sønstebø.

Now, here’s where things get really interesting. Instead of a blockchain, IOTA uses a “tangle,” which is based on a mathematical concept called a directed acyclic graph. Sønstebø says his team pursued an alternative approach after deciding that blockchains are too costly—it has recently cost as much as $20 per Bitcoin transaction because of high demand—and inefficient to operate at the scale required for the Internet of things.

Part of Sønstebø’s issue with Bitcoin and other blockchain systems it that they rely on a distributed network of “miners” to verify transactions.
So IOTA has dispensed with the miners. Instead, when a user issues a transaction, that individual also validates two randomly selected previous transactions, each of which refer to two other previous transactions, and so on. As new transactions mount, a “tangled web of confirmation” grows, says Sønstebø.


This is an interesting signal - and until actually proven may be best considered weak and significant. A different model of quantum computing and certainly a new model of computing. The article may be too detail for most of us - yet it’s worth the view.

Japan’s Quantum Computer Prototype Is 100 Times Faster Than Supercomputers

In November 2017, Japan unveiled it’s first quantum computer prototype that is opened up for free to the public over Internet for trials. With this machine, Japan has joined the race of building world’s most powerful computer with larger brute force, which is the key towards utilizing the full potential of artificial intelligence.

The project is developed by Nippon Telegraph and Telephone Corporation, University of Tokyo, National Institute of Informatics, Stanford University, and financially supported by the Government of Japan’s ImPACT program.

The machine is based on quantum neural network that can theoretically solve complex problems around 100 times faster than traditional supercomputers. What’s more impressive is, it does all of this while consuming only 1 kilowatt of power, rather than 10,000 kilowatts which is used by conventional supercomputers to perform the same task. Let’s find out what exactly they have developed and how does it work.


This is a great signal of many emerging trends - renewable energy, urban farming, new business models, re-imagining the city.

This Underground Urban Farm Also Heats The Building Above It

Truly local food is when it’s grown in your basement. Plantagon CityFarm wants to create a network of underground urban farms–and whole skyscrapers filled with plants.
Underneath a 26-floor office tower in Stockholm, an underground space once used as an archive for a newspaper will soon become a farm. And because of a unique business model, the urban farmers growing greens in the new farm won’t pay rent–their farm will pay for itself in heat.

Like some other indoor farms, the Plantagon CityFarm, set to begin production in early 2018, will grow greens in vertical towers under LED lights. But by capturing the heat from the lights–heat that would normally have to be vented out of the room and require air conditioning to keep the plants from overheating–the farm operators can send it into a heat storage system for the office building, and the heat can be used to help keep the offices warm through the winter.

The system will save the office building 700,000 kilowatt-hours of energy a year, worth roughly three times as much as the previous tenant of the basement was paying in rent.

The company plans to sell food directly to people working in the offices above, along with two restaurants that are located in the high-rise. Roughly a third of the produce will be sold to nearby grocery stores, all close enough that the greens can be delivered without fossil fuels. Another third of the produce will be sold in an on-site store in the skyscraper.


Here is a fascinating signal of the convergence of our domestication of DNA and 3D printing as an new manufacturing paradigm. There is a 2 min video.

3D printer uses ink made with live bacteria

Researchers have created a new kind of 3D-printing platform that uses ink containing living bacteria.
The new ink makes it possible to print small biochemical factories with certain properties, depending on the species of bacteria in the ink. The work also paves the way for the production of biological materials capable of breaking down toxic substances or high-purity cellulose for biomedical applications.
The scientists have named their new printing material “Flink,” which stands for “functional living ink.”

Different bacteria, different functions
The new printing platform offers numerous potential combinations. In a single pass, the scientists can use up to four different inks containing different species of bacteria at different concentrations in order to produce objects with different properties.


There is a current fear of ‘genetically modified organism’ (GMOs) - but here’s an interesting finding that it’s not only bacteria that regularly ‘cut and paste’ DNA from one organism to another (this capability was the source of finding CRISPR) - but also viruses. Thus, the question arises - Is there such a thing as an organism that isn’t GMO?
We discovered many virus-hallmark genes in cellular organisms those viruses are not known to infect.

VIRUSES SHARE GENES WITH ORGANISMS ACROSS THE TREE OF LIFE

A new study finds that viruses share some genes exclusively with cells that are not their hosts. The study, reported in the journal Frontiers in Microbiology, adds to the evidence that viruses swap genes with a variety of cellular organisms and are agents of diversity, researchers say.

The study looked at protein structures in viruses and across all super-kingdoms, or domains, of life: from the single-celled microbes known as bacteria and archaea, to eukaryotes, a group that includes animals, plants, fungi and all other living things.

“It is typical to define viruses in relation to their hosts, but this practice restricts our understanding of virus-cell interactions,” said University of Illinois and COMSATS Institute of Information Technology researcher Arshan Nasir, who led the new research with Gustavo Caetano-Anolles, a professor of crop sciences and affiliate of the Carl R. Woese Institute for Genomic Biology at the U. of I., and Kyung Mo Kim, a senior scientist at the Korea Polar Research Institute, in Incheon, South Korea.

“Recent research has revealed that organisms can form partnerships with other organisms and live in communities. For example, many bacterial and archaeal species reside in and on the human body and constitute the human microbiota,” Nasir said.

The team also discovered a large subset of virus-specific protein folds that were not present in any cellular genomes.
This suggests that viruses can create new genes and, potentially, transfer those genes to cellular organisms,” Nasir said.


One more signal in the transformation of energy geopolitics.

‘Death spiral’: half of Europe’s coal plants are losing money

Air pollution and climate change policies are pushing coal-fired electricity stations to the brink, says a new report. Closing them would avoid €22bn in losses by 2030
More than half of the European Union’s 619 coal-fired power stations are losing money, according to a new report. As a result, the industry’s slow plans for shutdowns will lead to €22bn in losses by 2030 if the EU fulfils its pledge to tackle climate change, the report warns.

Stricter air pollution rules and higher carbon prices are set to push even more plants into unprofitability, according to the analysts Carbon Tracker, with 97% of the plants losing money by 2030. Furthermore, rapidly falling renewables costs are on track to make building new wind and solar farms cheaper than continuing to run existing coal plants by the mid 2020s.

Utility companies continue to run loss-making plants in the hope that competitors will close their plants first or that governments will provide subsidies in return for guaranteed power, though the European commission wants to ban such payments. In Spain, the government has banned Iberdrola from closing its last coal plants, claiming it is concerned over energy security despite the country’s overcapacity in electricity.

Coal in Europe is in a “death spiral”, according to Carbon Tracker, with seven nations including the UK already having announced the end of coal power by 2030 or earlier.


And another signal.

It's Official: The World Bank Will Stop Fossil Fuel Financing After 2019

In a move sure to be celebrated by opponents of fossil fuel-based energy, the World Bank has just made a huge announcement at the One Planet summit called by French President Emmanuel Macron.

The bank, which provides loans to developing countries to foster economic growth, announced on December 12 that it will no longer offer financial support for oil and gas exploration after 2019.

During the summit, the bank released a statement saying it "will no longer finance upstream oil and gas," citing a need to change in a "rapidly changing world".
In 2015, the bank previously vowed to have 28 percent of its portfolio dedicated to climate action by 2020. The bank's latest statement on fossil fuel financing suggests that it is on course to achieve that goal.

This is yet another blow to the fossil fuel energy industry, and a seemingly significant win for environmental advocates.


And one more signal - that we are passing ‘peak demand’.

Top Insurer Axa To Exit Oil Sands

The oil industry is quickly turning into a pariah as more institutional investor are divesting their fossil fuel portfolios. The latest blow to oil’s popularity among investors came from French insurer Axa, the third-largest globally. Axa said in a statement yesterday that it will be divesting US$700 million worth of interests in Canadian oil sands production and pipelines.

The insurer said that oil sands are a very carbon-intensive industry “and a serious cause of environmental pollution,” and it would no longer invest in it. Axa will also divest some US$2.82 billion (€2.4 billion) from companies active in coal production and use.

The divestment targets will include companies that derive more than 30 percent of their revenues from coal, coal-plant builders, businesses with an energy mix that is more than 30 percent coal, and coal producers with production of over 20 million tons annually.

What’s more, Axa will also stop insuring “the main oil sands and the associated pipeline businesses” as well as coal projects, as this, the insurer says, would be the only consistent approach for it in light of the divestment strategy.


This article is a good signal of the rapidly emerging transformation of mass transit - From the demise of the internal combustion engine to all electric vehicles and later self-driving capabilities - from vehicle ownership to transportation access. There is a 2 min video.
“If we don’t do this, competitors will,” Volkswagen strategy chief Thomas Sedran said at the conference.

Volkswagen thinks its ride-sharing electric minibus will take 1 million cars off the road

The world’s largest automaker is getting into the ride-sharing business as it prepares for a world with fewer cars.

Volkwagen’s Moia brand unveiled on Monday (Dec. 4) a much-anticipated vehicle for its first ride-hailing service. The vehicle is a six-seater, all-electric minibus with a 300 kilometer (186 mile) range and USB ports, reading lights, and Wi-Fi for each passenger. A user will be able to hail the minivan using a custom app, and algorithms will optimize the ride-sharing by matching customers with similar destinations.

The minibus service will hit the streets of Hamburg, Germany, in the latter half of 2018 and start with a fleet of 200 vehicles, Moia CEO Ole Harms said on Monday at the TechCrunch Disrupt conference in Berlin. From there, the service will expand to around 1,000 vehicles and enter new cities in Europe and the US. Harms said he expects the minibuses to take 1 million cars off the road by 2025, which Volkswagen acknowledged would in-part cannibalize its car sale business.


Another signal of changing transportation paradigm.

World-first solar train now leaving the platform in Byron Bay with zero emissions

What is claimed to be the world's first fully solar-powered train is operating on the New South Wales North Coast.
A refurbished 70-year-old 'red rattler' is running on a three-kilometre stretch of disused rail line at the popular tourist destination of Byron Bay.
It made its maiden trip yesterday with almost 100 passengers on board.


This is just awesome. A 5 min A Capella account of the Evo-Devo biology. I would offer one critique - in that he doesn't mention Susan Oyama - the first writer I read using evo-devo theory in the 80s.

Evo-Devo (Despacito Biology Parody) | A Capella Science

EVO-DEVO
Huxley
B. Mac.
Oh Carroll, Carroll
Gould, Stephen Jay yeah
D-D-D-D-Davidson and Peter
See -One cell divide and decide on a thousand fates
Did you ever figure how they know?
B. Mac.
We - Are built of modules combined in a planned out way
Each new piece must be told where to go
Oh
Now there's a science helping us to understand
How our cells encode this architectural plan
Signalling each other with genetic tools oh
Oh yeah - Wow……..