How Sustainable Growth Also Has Physical Limits

This interesting and well remarked Scientific American article ‘The Delusion of Infinite Economic Growth‘ reminds us that there are physical limits to growth, whatever more “sustainable” technologies are implemented. Any technology that scales find its physical limits.

Every stage of the life cycle of any manufactured product exacts environmental costs: habitat destruction, biodiversity loss and pollution (including carbon emissions) from extraction of raw materials, manufacturing / construction, through to disposal. Thus, it is the increasing global material footprint that is fundamentally the reason for the twin climate and ecological crises.”

While “Technological innovation and efficiency improvements are often cited as pathways to decouple growth in material use from economic growth. While technology undoubtedly has a crucial role to play in the transition to a sustainable world, it is constrained by fundamental physical principles and pragmatic economic considerations.”

In addition, economic growth is exponential and not linear: “unfortunately, the situation is even more dire. Economic growth is required to be exponential; that is, the size of the economy must double in a fixed period.” Thus, “the inescapable inference is that it is essentially impossible to decouple material use from economic growth.” As a result, more is required today than to develop ‘sustainable’ solutions: solutions to the future raw material crises also need to be investigated.

Even sustainable growth will find its limits – as the economy and technologies scale, they require increasingly raw material and space, often in an exponential manner. But the world is finite, therefore a change of paradigm may be required.

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How Challenging the Energy Transition Will Be

This excellent article in The Atlantic ‘Why the Energy Transition Will Be So Complicated‘ provides an important reminder and insight into how dependent we are on carbonated fuel, and how tough it will be to change: “The degree to which the world depends on oil and gas is not well understood“.

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The article underlines how much we are dependent on oil&gas for a variety of materials in addition to energy, and how pervasive usage of oil can be in our societies. As a result, some warn “that going into overdrive on transitioning away from fossil fuels would lead to major economic shocks similar to the oil crises that rocked the global economy in the 1970s. “Policymakers,” [Jean Pisani-Ferry] wrote, “should get ready for tough choices.”

The term energy transition somehow sounds like it is a well-lubricated slide from one reality to another. In fact, it will be far more complex: Throughout history, energy transitions have been difficult, and this one is even more challenging than any previous shift.” In addition, it is supposed to happen much quicker than any other such transitions in the past, necessarily impacting the value of assets and making investment into anything related to energy more hazardous. Previously such energy transitions typically took more than a century to be established and to replace previous energy sources.

I am personally convinced that oil & gas will remain an important industry in the next 2 decades, while coal may start to whither. The solution may lie more in carbon capture than cutting too fact our dependency on oil & gas.

The current energy transition will be more challenging and complex that usually anticipated, in particular because it is supposed to be much quicker than any such historical transition. Let’s not forget this in our anticipations.

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How AI Algorithms Evolution Approaches Provide Insight Into Natural Evolution

This interesting article ‘AI is now learning to evolve like earthly lifeforms‘ provides some insight about advances in AI algorithm development. Researches are trying to find the most effective way for algorithms to go through the process of natural evolution. And this provides interesting learning about our natural world.

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The interest of this research is of course also to enlighten our understand of the principles of natural evolution, and how to keep its cost low (as it requires many trials for very few successful variants). “In their new work, the researchers at Stanford aim to bring AI research a step closer to the real evolutionary process while keeping the costs as low as possible. “Our goal is to elucidate some principles governing relations between environmental complexity, evolved morphology, and the learnability of intelligent control,” they write in their paper.

It involves the simulation of robotic agents in an environment, with some evolution algorithm for the AI algorithm driving the creatures.

Interesting results include: “validating the hypothesis that more complex environments will give rise to more intelligent agents“, and “in line with another hypothesis by DeepMind researchers that a complex environment, a suitable reward structure, and reinforcement learning can eventually lead to the emergence of all kinds of intelligent behaviors.”

Teaching AI algorithms how to evolve provides interesting insights. The fact that more complex environments will give rise to more intelligent agents is definitely a key insight into life’s evolution.

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How Implementing AI Requires Organizational Transformation

This interesting article ‘Artificial intelligence: Everyone wants it, but not everyone is ready‘ takes an interesting angle on the spread of AI-driven systems throughout organizations: as for all new tools, success requires to change the way organizations work, and not all organizations are ready for that change.

While many AI and machine learning deployments fail, in most cases, it’s less of a problem with the actual technology and more about the environment around it,” says Harish Doddi, CEO of Datatron. Moving to AI “requires the right skills, resources,?and?systems.

While it’s arguably true that AI can add significant value to practically any department across any business, one of the biggest mistakes a business can make is to implement AI for the sake of implementing AI, without a clear understanding of the business value they hope to achieve“. In particular, understanding how data biases or poor data hygiene can affect AI algorithms, understanding those effects and how they influence performance appear to be an essential capability.

In addition, the organization processes and particularly the data production, gathering and structuring appears to be an essential area for review and upgrade when implementing AI-based tools.

Like any new powerful tool, AI has transformational impact on organizations and the way their data is gathered and managed. This should not be overseen when implementing those new capabilities.

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How Marketing Rules Have Changed Significantly In a Few Years with AI

Since the beginning of the Fourth Revolution there is a growing concern of the gap building between technology have and have nots. This has been quite alleviated since the arrival of the smart phone. However, there is still a growing issue when it comes to understand how algorithms work and take advantage of them. In this eye-opening piece ‘What’s On My Mind: What About the Gap?‘, Christopher Penn provides a compelling example about the difference it can make in marketing to understand AI-driven algorithms, because it drives directly what potential customers see or not.

In the era before popular, commercial use of machine learning, success in business was largely a combination of effort and luck. Effort encompasses the skill needed to make a good product and sell it well, and luck encompasses being in the right place at the right time, whether you’re the local burger joint or a multinational corporation.”

Today, data science, machine learning, and AI have thrown a bit of a wrinkle into this. So much of our lives are intermediated by machines and machine learning. What products we see, what ads we see, what news we see, what friends we see in the digital realm – which is the primary realm now for so many of these tasks ever since the smartphone became our external brains – are all controlled by machines and algorithms.”

Christopher Penn then continues to provide the example of what he could achieve easily given his background in data science for a florist shop friend, substantially increasing ranking and visibility on the internet through clever understanding of data analytics.

For a while, the Internet presented a level playing field where a small business could appear larger than it was, where relevance and not budget could win the day. That 20-year golden era of Internet marketing – 1997-2017 – has been supplanted by the AI-powered marketing era, and this is an era in which whoever has the technical resources to win will do so.

To be clear, having great products, good prices, and phenomenal service will still be fundamental to succeeding at business. No amount of AI will change a crap product, prices that aren’t competitive, or abusive service and get people to buy, long-term, who would not have bought before. But becoming visible, being seen, will be harder for those without skillful use of AI.”

Certainly a very useful warning. AI and data analytics knowledge is now the key to being visible and we all need to understand that the game has changed only a couple a years. Marketing is now different, rules are different and thus the game changed.

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How Electromagnetic Weapons May Be Decisive in Future Wars

This excellent article ‘‘Revolution in warfare’: Israel has new ‘invisible’ defense system‘ provides useful insight into electromagnetic weapons that aim to destroy the enemy’s electronic systems, which are now so important in all weaponry.

The weapon, which reportedly can halt electronic capabilities of an enemy, is part of a new suite of electromagnetic warfare called Scorpius. The Scorpius “missiles” send narrowly targeted beams of energy that disrupt enemy electronic sensors, navigation, radar or other electronic activity.” Also, this new weapon is supposedly much more discriminating as “the new Scorpius weapons have an advantage over older forms of electromagnetic warfare because they can send targeted beams without interfering with unintended targets.”

We can also observe this type of weapons to be deployed in the form of drone killing devices. It may be difficult to protect electronics from such weapons if the electromagnetic energy sent is very dense. This has not yet be deployed in major conflicts between technological armies, but could certainly be a game changer in terms of requiring a new generation of reinforced electronics in all weapons to survive electromagnetic aggressions.

Electromagnetic weapons are now operational and will have a significant impact on how future wars may develop, not to mention their potentiel effect on unprotected civilian infrastructure. This is certainly a significant change ahead!

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How Brains Predict Perception to Save Energy

This exciting article ‘To Be Energy-Efficient, Brains Predict Their Perceptions‘ discusses how “results from neural networks support the idea that brains are “prediction machines” — and that they work that way to conserve energy“. This has wide ranging consequences in perception and how we may be deceived by this predictive trait.

Many neuroscientists are pivoting to a view of the brain as a “prediction machine.” Through predictive processing, the brain uses its prior knowledge of the world to make inferences or generate hypotheses about the causes of incoming sensory information. Those hypotheses — and not the sensory inputs themselves — give rise to perceptions in our mind’s eye. The more ambiguous the input, the greater the reliance on prior knowledge.”

This results in the development of many models that approximate brain behavior when it comes to perception. Much work has been done on developing neural network models mimicking the brain, and analyzing their energy consumption. “The takeaway is that a neural network that minimizes energy usage will end up implementing some sort of predictive processing — making a case that biological brains are probably doing the same.”

This also explains many effects of visual illusions where the brain unconsciously infers an explanation to the image which may oversee another or be plainly wrong. This well-known phenomenon is also used in psychology to uncover our unconscious by studying what interpretations we spontaneously provide in those situations.

It is not surprising that evolution has found a way to minimise the brain energy consumption, which is already draining a lot of energy for itself. The balance between prediction and actual observation it has found may have made sense in the past, but does it make sense now? How can we exploit it or overcome it depending on the circumstances?

In any case the fact that neural-networks models have been developed of the brain that allow to explain some of its behaviors is a great step forward in understanding at least the perceptual part of the brain.

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How the Profile of the Richest People Has Changed Over History

This interesting infographics ‘the richest people in history‘ reminds us that throughout most of our human history, the Agricultural Age, the richest people have been the kings, emperors and rulers of vast areas of land. Then, in the 15th century onwards (the start of the Industrial Age) came the time of bankers and merchants.

Detail from the Catalan Atlas, 1375 (vellum)

The infographic does not go as far, but of course from the 15th century, accelerating into the 19th century, the richest people started to be industrialists and bankers financing new machines and infrastructures. And now, they are industrialists of the economy. Still their wealth is much less than the historical rulers mentioned in the infographic whose wealth could be up to 20% of world GDP – which shows that in a certain measure richer people are now much less proportionally rich than historical figures.

The other interesting transformation to note is that up to the 15th century, wealth was derived regionally and mostly within one’s borders. Then trade spread and fortunes were made on this basis. In the 20th century it started to become truly global, and now it is definitely mostly global for the richest people on earth. Thus the geographical basis of wealth has also significantly changed.

It is often interesting to take such as historical perspective to remind ourselves that what we observe today is the result of a long evolution. Wealth is now not an exclusive property of tyrannical rulers, or industrialists but the domain of businesspeople with global interests that move resolutely into the Collaborative Age.

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How We Need to Have a Threshold Space for Transformation

Charlene Li in her post ‘Why You Need Liminal Space for Seamless Change‘ reminds us that we need to have a threshold, or some kind of intermediate space, when changing.

In her case, “[her] son just graduated from college, and we wanted to create liminal space for him to celebrate what he accomplished and to prepare himself for the future.” To do that they took a long drive across the US.

“Liminal” comes from the Latin word meaning “threshold,” and it’s an unavoidable part of change. Unfortunately, many organizations view change as something to go through as fast as possible. But […] a more effective and disruptive way to change is to slow down and actually create the liminal space of in between. This also creates space mentally and emotionally to expand on possibilities and opportunities.”

I love this idea of the need of having such a threshold and take it a bit slow when going through a transformation, taking the time to achieve it in a safe and sound manner.

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How the Next Big Idea Doesn’t Need to Be Original or in a New Market

I love this blog post by Seth Godin ‘The next big idea‘ that reminds us that it does not need to be new not have no competition.

There are two confusions. The first is that the next big idea must be fully original. The second is that it have no competition. This is almost never the case.”

It is true that many thriving enterprises have just reinvented a small part of a business model, or have built on existing industrial practices just changing one parameter. At the end of the day it depends on the client: “The future of all of these types of organizations isn’t based on a lack of customer choice. It’s based on customer traction.”

Seth Goding reminds us that “The hard part is showing up to lead.”, leading through to get perfect execution in the market that is being addressed.

Looking for an idea to create your company? Don’t necessarily look for original or to create a new market: that’s often too hard. Just execute better than others and get customers to love what you are doing.

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How Intrapreneurs and Entrepreneurs Can Both Spark Innovation

This article ‘Leaving the cult of entrepreneurship: Intrapreneurs are the true drivers of innovation‘ takes position in the debate between intrapreneurs and entrepreneurs as sources of innovation. I don’t think it is as simple: it all depends what kind of innovation we address and we should not oppose the two categories.

Intrapreneurs have the advantage of being able to mobilize considerables resources from their company to get their idea developed, once it is approved and recognized. Those means will dwarf those of the start-up entrepreneur, however one has to overcome the hurdles of internal approval and politics, and recognize the inevitable longer delays in getting things done in large organisations.

Independent entrepreneurs on their side will be more nimble, able to start on ideas without waiting for more approval than their friends and families’ dime. They can thus start on ideas that may be considered ridiculous by corporate committees. They can also often pivot more easily.

I thus think that intrapreneurs and entrepreneurs are both potential contributors to breakthrough innovation, and that frustrated intrapreneurs can also easily become entrepreneurs. They should not be opposed and both can certainly change the world.

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How to Explain the Trend Toward Sovereign Individuals and Entities

Have you heard about sovereign individuals announcing themselves to be above any state or country law? See for example this Forbes article ‘What is a Sovereign Citizen?‘, and a latest example at municipal level: ‘A California city council voted to make itself a ‘Constitutional Republic City’ to skirt state and federal orders it doesn’t want to enforce‘.

It has become a trend, inspired by individualism and often by anarchism thought about the fact that government is superfluous. “The short answer: a sovereign citizen is someone who believes that he or she is above all laws.” The longer answer: finding some basis to avoid applying some law or regulation you don’t like. People involved are often close to conspiracy theory and anarchistic movements.

Still, in the US, “The sovereign citizen movement is big and is growing fast, thanks to the Internet. There are an estimated 300,000 people in the movement, and approximately one third of these are what I would call hard-core believers – people willing to act on their beliefs rather than simply walk away.” It has become a concern and a trend, because it is so easy to declare oneself no obeying to certain laws you don’t like!

You can’t pick and choose the laws you are willing to obey and those you don’t. We all participate in a social construct and much of our wealth and peace is based on the addition of laws and regulations over the year. We also all belong to a country, a municipality. If we want to change something, in our democratic societies we can campaign for it. It is a bit easy to declare oneself a sovereign citizen to do as you like.

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