These days we are all striving for connections. In families, between generations, in neighborhoods, and even among co-workers. We rely on it for learning, for trading, for economic growth, for innovation and for global change.
If we didn’t know it before, we certainly realize it now: our connectedness—the ways we are knit together—holds both benefits and risks for our health, our economies, our communities, and our planet.
That’s the essence of sustainability, really. It’s not just an environmental issue but also a fundamental economic issue. And it’s not just a health issue but also a moral imperative. The size and complexity of the challenges we face require creative, systems-level thinking.
No one acting alone—no country, no sector, no scientist, no corporation—will effect meaningful change. Solving the world’s biggest sustainability challenges will require a new kind of innovation, one that leverages insights and expertise from across a broad spectrum of sectors and industries.
Tackling plastic waste
Take the plastic waste problem. Every year, $80 to $120 billion dollars of economic value is thrown away in the form of single-use plastic packaging.(i) Every minute the equivalent of a garbage truck’s worth of plastic waste is dumped into the ocean,(ii) and according to University of Georgia environmental engineering professor Jenna Jambeck, at the current rate, by 2030 it will be a football stadium’s worth of plastic waste being dumped into our oceans every day.(iii)
Stemming the tide of plastic waste will require innovation across the entire plastics value chain – from how it is formulated in the lab, designed into products, used by consumers, and ultimately collected, recycled, and disposed of.
Two years ago, Morgan Stanley launched its Plastic Waste Resolution,(iv) not because we produce or use a lot of plastic, but because as a global financial firm we are connected to the investors, the corporations, the governments, the innovators, and the nonprofits that can make a difference. If we all work together.
The resolution is very straightforward: as a firm, we committed to facilitating the prevention, reduction, and removal of 50 million metric tons of plastic waste from nature by 2030. As part of that, we’re underwriting the Debris Tracker app,(v) which supports citizen science by empowering individuals to collect and report data litter so scientists and researchers can better understand the causes of plastic waste in coastlines and waterways.
Our social compact
Of course, sustainability is bigger and broader than plastic pollution, and “environment” is just one leg of the environmental, social, and corporate governance (ESG) stool. The last year, in fact, has brought renewed attention to the full spectrum of sustainability, and again, innovation and partnership were key to the response.
A relatively new product, “social bonds” are now helping foundations and other nonprofits fund the critical work of renewing communities, battling racial injustice, and securing a more equal future for all people. Last year, for example, Morgan Stanley partnered with the Ford Foundation to underwrite a first of its kind $1 billion social bond,(vi) which allowed the foundation to increase grant making to nonprofits during the pandemic and ensure the continuity of organizations fighting for equality and supporting vulnerable communities. And later in the year we raised our own $1 billion with a social bond that allocated capital in equal amounts to the financing and refinancing of affordable housing projects for low- or moderate-income individuals and families across the US.(vii)
That broad understanding—that sustainability takes integrated, innovative approaches to achieve—sits at the core of Morgan Stanley’s Global Sustainable Finance Group. We started it more than a decade ago with the express purpose of partnering with teams across our businesses to implement sustainable solutions and integrate sustainability into our products and services. It is also why as a firm, in September, building on our announced goal to be carbon-neutral by 2022,(viii) we became the first major US bank to pledge to reach net-zero financed emissions by 2050.(ix)
What seemed like a novelty to some back then has become core to many investor portfolios and corporate risk statements. Sustainable investing accounts for $1 out of every $3 under professional management in the US,(x) and is now a more-than $30 trillion market globally.(xi) In a recent survey, a remarkable 85% of US individual investors express interest in sustainable investing strategies,(xii) and we think the investment, the innovation and the commitment will only grow.
Real efforts are underway at our firm and across many sectors to develop, launch, and scale real sustainability efforts that together will make a difference for us and future generations. That’s good news, because our most pressing complex ESG problems will not be solved in silos.
(i) MacArthur, D. E., D. Waughray, and M. R. Stuchtey. “The New Plastics Economy, Rethinking the Future of Plastics.” World Economic Forum. 2016, https://www.ellenmacarthurfoundation.org/publications/the-new-plastics-economy-rethinking-the-future-of-plastics
(ii) Pennington, James. “Every minute, one garbage truck of plastic is dumped into our oceans. This has to stop.” World Economic Forum. 2016, https://www.weforum.org/agenda/2016/10/every-minute-one-garbage-truck-of-plastic-is-dumped-into-our-oceans/
(iii) Parker, Laura. “Plastic pollution is a huge problem—and it’s not too late to fix it,” National Geographic, October 6, 2020, https://www.nationalgeographic.com/science/article/plastic-pollution-huge-problem-not-too-late-to-fix-it
(x) Nason, Deborah. “’Sustainable investing’ is surging, accounting for 33% of total U.S. assets under management,” December 21, 2020, https://www.cnbc.com/2020/12/21/sustainable-investing-accounts-for-33percent-of-total-us-assets-under-management.html
(xi) Chasan, Emily, “Global Sustainable Investments Rise 34 Percent to $30.7 Trillion,” Bloomberg, April 1, 2019, https://www.bloomberg.com/news/articles/2019-04-01/global-sustainable-investments-rise-34-percent-to-30-7-trillion
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How AI is reinventing what computers are
Fall 2021: the season of pumpkins, pecan pies, and peachy new phones. Every year, right on cue, Apple, Samsung, Google, and others drop their latest releases. These fixtures in the consumer tech calendar no longer inspire the surprise and wonder of those heady early days. But behind all the marketing glitz, there’s something remarkable going on.
Google’s latest offering, the Pixel 6, is the first phone to have a separate chip dedicated to AI that sits alongside its standard processor. And the chip that runs the iPhone has for the last couple of years contained what Apple calls a “neural engine,” also dedicated to AI. Both chips are better suited to the types of computations involved in training and running machine-learning models on our devices, such as the AI that powers your camera. Almost without our noticing, AI has become part of our day-to-day lives. And it’s changing how we think about computing.
What does that mean? Well, computers haven’t changed much in 40 or 50 years. They’re smaller and faster, but they’re still boxes with processors that run instructions from humans. AI changes that on at least three fronts: how computers are made, how they’re programmed, and how they’re used. Ultimately, it will change what they are for.
“The core of computing is changing from number-crunching to decision-making,” says Pradeep Dubey, director of the parallel computing lab at Intel. Or, as MIT CSAIL director Daniela Rus puts it, AI is freeing computers from their boxes.
More haste, less speed
The first change concerns how computers—and the chips that control them—are made. Traditional computing gains came as machines got faster at carrying out one calculation after another. For decades the world benefited from chip speed-ups that came with metronomic regularity as chipmakers kept up with Moore’s Law.
But the deep-learning models that make current AI applications work require a different approach: they need vast numbers of less precise calculations to be carried out all at the same time. That means a new type of chip is required: one that can move data around as quickly as possible, making sure it’s available when and where it’s needed. When deep learning exploded onto the scene a decade or so ago, there were already specialty computer chips available that were pretty good at this: graphics processing units, or GPUs, which were designed to display an entire screenful of pixels dozens of times a second.
Anything can become a computer. Indeed, most household objects, from toothbrushes to light switches to doorbells, already come in a smart version.
Now chipmakers like Intel and Arm and Nvidia, which supplied many of the first GPUs, are pivoting to make hardware tailored specifically for AI. Google and Facebook are also forcing their way into this industry for the first time, in a race to find an AI edge through hardware.
For example, the chip inside the Pixel 6 is a new mobile version of Google’s tensor processing unit, or TPU. Unlike traditional chips, which are geared toward ultrafast, precise calculations, TPUs are designed for the high-volume but low-precision calculations required by neural networks. Google has used these chips in-house since 2015: they process people’s photos and natural-language search queries. Google’s sister company DeepMind uses them to train its AIs.
In the last couple of years, Google has made TPUs available to other companies, and these chips—as well as similar ones being developed by others—are becoming the default inside the world’s data centers.
AI is even helping to design its own computing infrastructure. In 2020, Google used a reinforcement-learning algorithm—a type of AI that learns how to solve a task through trial and error—to design the layout of a new TPU. The AI eventually came up with strange new designs that no human would think of—but they worked. This kind of AI could one day develop better, more efficient chips.
Show, don’t tell
The second change concerns how computers are told what to do. For the past 40 years we have been programming computers; for the next 40 we will be training them, says Chris Bishop, head of Microsoft Research in the UK.
Traditionally, to get a computer to do something like recognize speech or identify objects in an image, programmers first had to come up with rules for the computer.
With machine learning, programmers no longer write rules. Instead, they create a neural network that learns those rules for itself. It’s a fundamentally different way of thinking.
Decarbonizing industries with connectivity and 5G
The United Nations Intergovernmental Panel on Climate Change’s sixth climate change report—an aggregated assessment of scientific research prepared by some 300 scientists across 66 countries—has served as the loudest and clearest wake-up call to date on the global warming crisis. The panel unequivocally attributes the increase in the earth’s temperature—it has risen by 1.1 °C since the Industrial Revolution—to human activity. Without substantial and immediate reductions in carbon dioxide and other greenhouse gas emissions, temperatures will rise between 1.5 °C and 2 °C before the end of the century. That, the panel posits, will lead all of humanity to a “greater risk of passing through ‘tipping points,’ thresholds beyond which certain impacts can no longer be avoided even if temperatures are brought back down later on.”
Corporations and industries must therefore redouble their greenhouse gas emissions reduction and removal efforts with speed and precision—but to do this, they must also commit to deep operational and organizational transformation. Cellular infrastructure, particularly 5G, is one of the many digital tools and technology-enabled processes organizations have at their disposal to accelerate decarbonization efforts.
5G and other cellular technology can enable increasingly interconnected supply chains and networks, improve data sharing, optimize systems, and increase operational efficiency. These capabilities could soon contribute to an exponential acceleration of global efforts to reduce carbon emissions.
Industries such as energy, manufacturing, and transportation could have the biggest impact on decarbonization efforts through the use of 5G, as they are some of the biggest greenhouse-gas-emitting industries, and all rely on connectivity to link to one another through communications network infrastructure.
The higher performance and improved efficiency of 5G—which delivers higher multi-gigabit peak data speeds, ultra-low latency, increased reliability, and increased network capacity—could help businesses and public infrastructure providers focus on business transformation and reduction of harmful emissions. This requires effective digital management and monitoring of distributed operations with resilience and analytic insight. 5G will help factories, logistics networks, power companies, and others operate more efficiently, more consciously, and more purposely in line with their explicit sustainability objectives through better insight and more powerful network configurations.
This report, “Decarbonizing industries with connectivity & 5G,” argues that the capabilities enabled by broadband cellular connectivity primarily, though not exclusively, through 5G network infrastructure are a unique, powerful, and immediate enabler of carbon reduction efforts. They have the potential to create a transformational acceleration of decarbonization efforts, as increasingly interconnected supply chains, transportation, and energy networks share data to increase efficiency and productivity, hence optimizing systems for lower carbon emissions.
Surgeons have successfully tested a pig’s kidney in a human patient
The reception: The research was conducted last month and is yet to be peer reviewed or published in a journal, but external experts say it represents a major advance. “There is no doubt that this is a highly significant breakthrough,” says Darren K. Griffin, a professor of genetics at the University of Kent, UK. “The research team were cautious, using a patient who had suffered brain death, attaching the kidney to the outside of the body, and closely monitoring for only a limited amount of time. There is thus a long way to go and much to discover,” he added.
“This is a huge breakthrough. It’s a big, big deal,” Dorry Segev, a professor of transplant surgery at Johns Hopkins School of Medicine who was not involved in the research, told the New York Times. However, he added, “we need to know more about the longevity of the organ.”
The background: In recent years, research has increasingly zeroed in on pigs as the most promising avenue to help address the shortage of organs for transplant, but it has faced a number of obstacles, most prominently the fact that a sugar in pig cells triggers an aggressive rejection response in humans.
The researchers got around this by genetically altering the donor pig to knock out the gene encoding the sugar molecule that causes the rejection response. The pig was genetically engineered by Revivicor, one of several biotech companies working to develop pig organs to transplant into humans.
The big prize: There is a dire need for more kidneys. More than 100,000 people in the US are currently waiting for a kidney transplant, and 13 die of them every day, according to the National Kidney Foundation. Genetically engineered pigs could offer a crucial lifeline for these people, if the approach tested at NYU Langone can work for much longer periods.