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A famous story about the Beatles tells of the collaboration between Paul McCartney and John Lennon on the song Getting Better for their legendary Sgt. Pepper's Lonely Hearts Club Band album. After McCartney wrote the lines I've got to admit, it's getting better; a little better all the time, Lennon wryly added, It can't get no worse. This story could serve as an epigraph as the calendar turns from the year 2020, which could hardly have gotten much worse, to 2021, when we hope life will indeed get a little better all the time. Better from COVID-19 because of the vaccines, better from misinformation spread by outgoing president Donald Trump and his allies, and better, we can hope, when it comes to the production and distribution of scientific knowledge.

There's plenty of exciting science to be optimistic about in 2021 (see News on p. 6). At the end of 2020, the DeepMind group in the United Kingdom announced a major advance in long-standing challenges in protein folding, predicting three-dimensional (3D) structures of proteins from their amino acid sequence. The next year portends even more exciting advances in protein structure and design.

On the cosmic front, there are many efforts underway to bring samples from the Solar System back to this planet. The Hayabusa2 mission that traveled to the asteroid 162173 Ryugu retrieved what could be a treasure trove of material revealing details about the ancient delivery of water and organic molecules to Earth. Similarly, the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, Security, Regolith Explorer) mission has collected samples from the asteroid Bennu that, when they arrive, could reveal important aspects of the formation of the Solar System. The new Mars rover Perseverance will land in February and, in addition to transmitting important data from the red planet, will begin the process of collecting samples that may eventually be studied in terrestrial laboratories.

In biology, the COVID-19 pandemic led to major advances in the development and application of messenger RNA (mRNA) vaccines. It is stunning that science not only came up with a vaccine to a new pathogen so quickly but also advanced a brand new vaccine technology, albeit one that was already in development for several years. The application of mRNA therapies to other problems in infectious diseases and throughout medicine will be exciting to follow.

Quantum computing remains an important area to watch. This year, Science published a paper that describes the application of a quantum computer to an important problem in theoretical chemistry. In the coming months, it's likely that there will be progress in addressing the problem of quantum error correction, pushing quantum computing a little closer to routine application.

Additive manufacturing and 3D printing continue to become more practical. In particular, the ability to apply these techniques to new types of materials will make it more likely that advanced manufacturing can benefit from the science behind these processes.

On the policy front, the continued development of the UK Research and Innovation (UKRI) organizationas described in a recent editorial by Ottoline Leyserwill be of keen interest as the Brexit process continues. Despite choppy politics, the scientific vision of UKRI is strong and could lead to advances in British science.

In the United States, although the Biden White House will certainly be friendlier to science, the science denial that fueled the Trump administration will linger in the American population and among some conservative politicians. The battles ahead are not to be underestimated. Continued denial of climate change and COVID-19 is sadly inevitable, and it will take everything U.S. science and the Biden administration can muster to stay strong. Still, as new leaders are named and confirmed in health and science policy, U.S. science should be able to at least catch its breath and feel optimistic about a new era.

Although 2020 will certainly go down as a year that couldn't get much worse, there is plenty to be proud of and reason to hope that things will be getting better. The virus was confronted. Epidemiologists and other scientists became household names. And the scientific community found a much stronger voice, one that will serve us all well in 2021 and beyond.

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A little better all the time in 2021 - Science Magazine

At a conference on quantum computing and finance on December 10, 2020, William Zeng, head of quantum research at Goldman Sachs, told the audience that quantum computing could have a revolutionary impact on the bank, and on finance more broadly. In a similar vein, Marco Pistoia of JP Morgan stated that new quantum machines will boost profits by speeding up asset pricing models and digging up better-performing portfolios. While there is little dispute that quantum computing has great potential to perform certain mathematical calculations much more quickly, whether it can revolutionize investing by so doing is an altogether different matter.

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Q3 2020 hedge fund letters, conferences and more

The hope is that the immense power of quantum computers will allow investment managers earn superior investment returns by uncovering patterns in prices and financial data that can be exploited. The dark side is that quantum computers will open the door to finding patterns that either do not actually exist, or if they did exist at one time, no longer do. In more technical terms, quantum computing may allow for a new level of unwarranted data mining and lead to further confusion regarding the role of nonstationarity.

ValueWalk's Raul Panganiban interviews George Mussalli, Chief Investment Officer and Head of Equity Research at PanAgora Asset Management. In this epispode, they discuss quant ESG as well as PanAgoras unique approach to it. The following is a computer generated transcript and may contain some errors. Q3 2020 hedge fund letters, conferences and more Interview . Read More

Any actual sequence of numbers, even one generated by a random process, will have certain statistical quirks. Physicist Richard Feynman used to make this point with reference to the first 767 digits of Pi, replicated below. Allegedly (but unconfirmed) he liked to reel off the first 761 digits, and then say 9-9-9-9-9 and so on.[1] If you only look at the first 767 digits the replication of six straight nines is clearly an anomaly a potential investment opportunity. In fact, there is no discernible pattern in the digits of Pi. Feynman was purposely making fun of data mining by focusing on the first 767 digits.

3 .1 4 1 5 9 2 6 5 3 5 8 9 7 9 3 2 3 8 4 6 2 6 4 3 3 8 3 2 7 9 5 0 2 8 8 4 1 9 7 1 6 9 3 9 9 3 7 5 1 0 5 8 2 0 9 7 4 9 4 4 5 9 2 3 0 7 8 1 6 4 0 6 2 8 6 2 0 8 9 9 8 6 2 8 0 3 4 8 2 5 3 4 2 1 1 7 0 6 7 9 8 2 1 4 8 0 8 6 5 1 3 2 8 2 3 0 6 6 4 7 0 9 3 8 4 4 6 0 9 5 5 0 5 8 2 2 3 1 7 2 5 3 5 9 4 0 8 1 2 8 4 8 1 1 1 7 4 5 0 2 8 4 1 0 2 7 0 1 9 3 8 5 2 1 1 0 5 5 5 9 6 4 4 6 2 2 9 4 8 9 5 4 9 3 0 3 8 1 9 6 4 4 2 8 8 1 0 9 7 5 6 6 5 9 3 3 4 4 6 1 2 8 4 7 5 6 4 8 2 3 3 7 8 6 7 8 3 1 6 5 2 7 1 2 0 1 9 0 9 1 4 5 6 4 8 5 6 6 9 2 3 4 6 0 3 4 8 6 1 0 4 5 4 3 2 6 6 4 8 2 1 3 3 9 3 6 0 7 2 6 0 2 4 9 1 4 1 2 7 3 7 2 4 5 8 7 0 0 6 6 0 6 3 1 5 5 8 8 1 7 4 8 8 1 5 2 0 9 2 0 9 6 2 8 2 9 2 5 4 0 9 1 7 1 5 3 6 4 3 6 7 8 9 2 5 9 0 3 6 0 0 1 1 3 3 0 5 3 0 5 4 8 8 2 0 4 6 6 5 2 1 3 8 4 1 4 6 9 5 1 9 4 1 5 1 1 6 0 9 4 3 3 0 5 7 2 7 0 3 6 5 7 5 9 5 9 1 9 5 3 0 9 2 1 8 6 1 1 7 3 8 1 9 3 2 6 1 1 7 9 3 1 0 5 1 1 8 5 4 8 0 7 4 4 6 2 3 7 9 9 6 2 7 4 9 5 6 7 3 5 1 8 8 5 7 5 2 7 2 4 8 9 1 2 2 7 9 3 8 1 8 3 0 1 1 9 4 9 1 2 9 8 3 3 6 7 3 3 6 2 4 4 0 6 5 6 6 4 3 0 8 6 0 2 1 3 9 4 9 4 6 3 9 5 2 2 4 7 3 7 1 9 0 7 0 2 1 7 9 8 6 0 9 4 3 7 0 2 7 7 0 5 3 9 2 1 7 1 7 6 2 9 3 1 7 6 7 5 2 3 8 4 6 7 4 8 1 8 4 6 7 6 6 9 4 0 5 1 3 2 0 0 0 5 6 8 1 2 7 1 4 5 2 6 3 5 6 0 8 2 7 7 8 5 7 7 1 3 4 2 7 5 7 7 8 9 6 0 9 1 7 3 6 3 7 1 7 8 7 2 1 4 6 8 4 4 0 9 0 1 2 2 4 9 5 3 4 3 0 1 4 6 5 4 9 5 8 5 3 7 1 0 5 0 7 9 2 2 7 9 6 8 9 2 5 8 9 2 3 5 4 2 0 1 9 9 5 6 1 1 2 1 2 9 0 2 1 9 6 0 8 6 4 0 3 4 4 1 8 1 5 9 8 1 3 6 2 9 7 7 4 7 7 1 3 0 9 9 6 0 5 1 8 7 0 7 2 1 1 3 4 9 9 9 9 9 9

When it comes to investing, there is only one sequence of historical returns. With sufficient computing power and with repeated torturing of the data, anomalies are certain to be detected. A good example is factor investing. The publication of a highly influential paper by Professors Eugene Fama and Kenneth French identified three systematic investment factors, which started an industry focused on searching for additional factors. Research by Arnott, Harvey, Kalesnik and Linnainmaa reports that by year-end 2018 an implausibly large 400 significant factors had been discovered. One wonders how many such anomalies quantum computers might find.

Factor investing is just one example among many. Richard Roll, a leading academic financial economist with in-depth knowledge of the anomalies literature has also been an active financial manager. Based on his experience Roll stated that his money management firms attempted to make money from numerous anomalies widely documented in the academic literature but failed to make a nickel.

The simple fact is that if you have machines that can look closely enough at any historical data set, they will find anomalies. For instance, what about the anomalous sequence 0123456789 in the expansion of Pi.? That anomaly can be found beginning at digit 17,387,594,880.

The digits of Pi may be random, but they are stationary. The process that generates the first million digits is the same as the one which generates the million digits beginning at one trillion. The same is not true of investing. Consider, for example, providing a computer the sequence of daily returns on Apple stock from the day the company went public to the present. The computer could sift through the returns looking for patterns, but this is almost certainly a fruitless endeavor. The company that generated those returns is far from stationary. In 1978, Apple was run by two young entrepreneurs and had total revenues of $0.0078 billion. By 2019, the company was run by a large, experienced, management team and had revenues of $274 billion, an increase of about 35,000 times. The statistical process generating those returns is almost certainly nonstationary due to fundamental changes in the company generating them. To a lesser extent, the same is true of nearly every listed company. The market is constantly in flux and the companies are constantly evolving as consumer demands, government regulation, and technology, among other things, continually change. It is hard to imagine that even if there were past patterns in stock prices that were more than data mining, they would persist for long due to nonstationarity.

In the finance arena, computers and artificial intelligence work by using their massive data processing skills to find patterns that humans may miss. But in a nonstationary world the ultimate financial risk is that by the time they are identified those patterns will be gone. As a result, computerized trading comes to resemble a dog chasing its tail. This leads to excessive trading and ever rising costs without delivering superior results on average. Quantum computing risks simply adding fuel. Of course, there are individual cases where specific quant funds make highly impressive returns, but that too could be an example of data mining. Given the large number of firms in the money management business, the probability that a few do extraordinarily well is essentially one.

These criticisms are not meant to imply that quantum computing has no role to play in finance. For instance, it has great potential to improve the simulation analyses involved in assessing risk. The point here is that it will not be a holy grail for improving investment performance.

Despite the drawbacks associated with data mining and nonstationarity, there is one area in which the potential for quantum computing is particularly bright marketing quantitative investment strategies. Selling quantitative investment has always been an art. It involves convincing people that the investment manager knows something that will make them money, but which is too complicated to explain to them and, in some cases, too complicated for the manager to understand. Quantum computing takes that sales pitch to a whole new level because virtually no one will be able to understand how the machine decided that a particular investment strategy is attractive.

This skeptics take is that quantum computing will have little impact on what is ultimately the source of successful investing allocating capital to companies that have particularly bright prospects for developing profitable business in a highly uncertain and non-stationary world. Perhaps at some future date a computer will development the business judgment to determine whether Teslas business prospects justify its current stock price. Until then being able to comb through historical data in search of obscure patterns at ever increasing rates is more likely to produce profits through the generation of management fees rather than the enhancement of investor returns.

[1] The Feynman story has been repeated so often that the sequence of 9s starting at digit 762 is now referred to as the Feynman point in the expansion of Pi.

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Quantum Computing And Investing - ValueWalk

What better time than now to unveil what to look out for in the world of AI and technology in 2021.

By Prithwis De

The year 2020 will be marked as an unprecedented year in history due to the adverse impact of coronavirus worldwide. This pandemic has started bringing extraordinary changes in some key areas. The trends of faster drug development, effective remote care, efficient supply chain, etc, will continue into 2021. Drone technology is already playing a vital role in delivering food and other essentials alongside relief activities.

With Covid-19 came a new concept of the Internet of Behaviour within organisations to track human behaviour in the work environment and trace any slack in maintaining guidelines. Now on, organisations are set to capture and combine behaviour-related data from different sources and use it. We can assertively say it will affect the way organisations interact with people, going forward. Students are experiencing distance learning, taking examinations under remotely-monitored and proctored surveillance systems through identity verification and authentication in real time.

All these will have a high impact on technology, which will shape our outlook in the future. Businesses around the globe are taking the giant leap to become tech-savvy with quantum computing, artificial intelligence (AI), cybersecurity, etc. AI and cloud computing are alluring us all towards an environment of efficiency, security, optimisation and confidence. What better time than now to unveil what to look out for in the world of AI and technology in 2021.

What 2020 has paved the way for is quantum computing. Now, be prepared to adapt to a hybrid computing approach (conventional cum quantum computing) to problem-solving. This paradigm shift in computing will result in the emergence of implausible ways to solve existing business problems and ideate new opportunities. Its effects will be visible on our ability to perform better in diverse areasfinancial forecasting, weather predictions, drug and vaccine development, blood-protein analysis, supply chain planning and optimisation, etc. Quantum Computing as a Service (QCaaS) will be a natural choice for organisations to plug into the experiments as we advance. Forward-thinking businesses are excited to take the quantum leap, but the transition is still in a nascent stage. This new year will be a crucial stepping stone towards the future of things to change in the following years.

Cloud providers such as Amazon (AWS), Microsoft (Azure) and Google will continue to hog the limelight as the AI tool providers for most companies leaning towards real-time experiments in their business processes in the months to follow. Efficiency, security and customisation are the advantages for which serverless and hybrid cloud computing are gaining firm ground with big enterprises. It will continue to do so in 2021.

Going forward, the aim is to make the black box of AI transparent with explainable AI. The lack of clarity hampers our ability to trust AI yet. Automated machine learning (AutoML), another crucial area, is likely to be very popular in the near future. One more trend that caught on like wildfire in 2020 is Machine Learning Operations (MLOps). It provides organisations visibility of their models and has become an efficient tool to steer clear of duplicated efforts in AI. Most of the companies have been graduating from AI experimentations and pilot projects to implementation. This endeavour is bound to grow further and enable AI experts to have more control over their work from end-to-end now onwards.

Cybersecurity will gain prime importance in 2021 and beyond as there is no doubt that hacking and cybercrime prevention are priorities for all businesses with sensitive data becoming easily accessible with advanced phishing tools. Advanced prediction algorithms, along with AI, will play a decisive role in the future to prevent such breaches in data security.

AI and the Internet of Things along with edge computing, which is data processing nearer the source closer to the device at the edge of the network, will usher in a new era for actionable insights from the vast amount of data. The in-memory-accelerated-real-time AI will be needed, particularly when 5G has started creating new opportunities for disruption.

In 2020, there was a dip in overall funding as the pandemic had badly impacted the investment sector due to a reduction in activity. Some of the technology start-ups are still unable to cope up with the challenges created due to Covid-19 and the consequent worsening economic conditions. According to NASSCOM, around 40% of Indian start-ups were forced to stop their operations. In 2021, mergers and acquisitions of start-ups are expected. The larger companies are likely to target smaller companies, specialised mainly in niche and innovative areas such as drug development, cybersecurity, AI chips, cloud computing, MLOps, etc.

The businesses in 2021 and beyond will develop into efficient workplaces for everybody who believes in the power of technology. It is important to bear in mind that all trends are not necessarily independent of each other, but rather form the support base of the other as well as work in tandem with human intervention. So, are the hybrid trends and solutions here to stay for the next few years for the smooth running of various organisations? Only time will tell. But the need for AI and newer technology adoption and modernisation increases manifold.

The author is an analytics and AI professional, based in London, working in a big IT company. Views are personal

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Tech trends in 2021: How artificial intelligence and technology will reshape businesses - The Financial Express

In my previous column, I looked at the problem of artificial intelligences forcing hardware to consume too much power, which could lead to an unsustainable spike in demand at data centers in this country by 2025. To test out their appetites for more power, I employed several advanced artificial intelligences, and also their close cousins machine learning, cognitive computing, deep learning and advanced expert system technology. For that column, I only measured how much power they consumed, but my original intention was to actually test them out to show some innovative things the technology was accomplishing. I am circling back to that effort now.

For many years we have been reporting on the technology of artificial intelligence, about how its being built out and made more efficient, or how it can be paired with other technologies like quantum computing to become even more accurate. At the same time, the government has been keenly focused on AI ethics, ensuring that our newly created smart programs and machines dont go rogue or make mistakes that could get people hurt. The Defense Department now follows five ethical principles when using AI, while the intelligence community has its own artificial intelligence ethics guidelines.

There is still a lot of learning to do, but at this point we have pretty much covered the basics in terms of building out smart AIs and related technologies, power consumption issues aside. That is why we are starting to see a lot of interesting reports on projects that make use of AI, like figuring out which fishing boats out in the ocean are using forced labor or planning how we can safely get people to Mars.

These are some of the most interesting AIs that I have collected over the past few months, what they do and how well they perform.

COBOL Colleague

The federal government invested big in the COBOL programming language back in the day. It was designed for business, finance and administrative systems within both private companies and government organizations. Today, however, its not actively used for any new projects, having been replaced by more efficient languages. Most COBOL programming today is used to maintain existing systems written in the language that cant easily be replaced or recoded. The problem is that nobody is learning how to code in COBOL anymore, and most programmers that already know it have retired.

That is where Colorado-based startup Phase Change Software and their COBOL Colleague AI comes into play. Instead of trying to teach COBOL to modern programmers, it scans existing programs written in the language for vulnerabilities and problems, and zeros in on exactly what lines need to be fixed.

There is certainly a skills shortage, however, the real problem is that the knowledge of the application is disappearing, said Steve Brothers, COO of Phase Change Software.

Deploying an AI to look at code is almost like hiring a skilled human programmer. In the case of COBOL Colleague, it wont make changes to the code on its own but will show where any changes are needed. Then skilled programmers, even if they are not totally familiar with COBOL, can make the necessary fixes.

ToxMod

ToxMod is an interesting artificial intelligence made by Modulate Inc, a company that specializes in innovative AI. ToxMod is designed to regulate live comments in voice chat rooms and is able to distinguish subtle differences between, say, someone using an explicative in frustration, and someone using it as an attack or as part of a hateful tirade. To give ToxMod a real workout, its being deployed in the ultimate toxic environment, the chat rooms of video games.

Since ToxMod can differentiate something like honest frustration expressed in a toxic way from malicious intent, it can also advise matchmaking or reputation algorithms to improve the player experience, said Carter Huffman, Co-Founder and CTO of Modulate. Additionally, each games private ToxMod instances learn over time about their communitys specifics, on top of ToxMods universal core algorithms which evolve and improve automatically behind the scenes.

ToxMod can listen to and understand emotions, volume, inflections and other factors to determine if speech should be flagged. If hateful speech is detected, site moderators are alerted along with an audio clip to back up the AIs claim. This will let moderators check the AIs work while identifying bad actors and preemptively resolving a problem before it grows into something more serious.

The Test

This last one is mostly just for fun, but I was so impressed that I felt like I needed to include it here. The Test is, on the surface, a series of three games available for less than $2 each on the Steam gaming platform. The games are kind of bizarre in nature. Players sit in front of a demonic-like figure at his desk and are asked a series of very personal questions. The questions consist of typical personality type questions like If you found money on the street and knew who it belonged to, would you return it? But there are also a series of very strange scenarios and off-the-wall questions like if you were starving at home would you eat your pets, if pink is a prettier color than red, or if would you stop a zombie apocalypse if you could.

Behind the scenes, developer Randumb Studios is likely using an expert system as opposed to a true AI to track results and prepare advice for players. The questions were so strange that I really didnt think much of it, though I did try and answer honestly. But the final results, especially for the second game, really floored me.

It told me that I was working too hard and that I needed to take some time to recharge my batteries because I was not doing anyone any good if I was spread so thin that nobody was getting my best. It advised me to allocate two units of personal time for every one unit I spent working for others, which would be a key to both my happiness and success moving forward.

The strange thing is that I was really thinking about this exact same thing over the past two weeks, especially with the holidays approaching. I was worried about burnout and keeping a good work and life balance, and had spent quite a few evenings contemplating that exact topic. But I never told the game this, and dont see how its bizarre questions led it to that conclusion.

I guess that is the magic of expert systems. Its why those little 20-questions toys that ask you yes and no questions can always guess the song or the movie star that you are thinking about. But the leap that The Test made with me was a lot bigger than that. I still dont know how they did it, but am very impressed with the results.

The really amazing thing is that we are really just scratching the surface about what AI can do. In the near future, even the projects highlighted here will seem trivial compared to what is possible.

John Breeden II is an award-winning journalist and reviewer with over 20 years of experience covering technology. He is the CEO of the Tech Writers Bureau, a group that creates technological thought leadership content for organizations of all sizes. Twitter: @LabGuys

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Artificial Intelligence Begins to Realize Its Potential - Nextgov

Tyler Cowen| Bloomberg Opinion

Columns share an author's personal perspective and are often based on facts in the newspaper's reporting.

For obvious reasons, 2020 will not go down as a good year. At the same time, it has brought more scientific progress than any year in recent memory and these advances will last long after COVID-19 as a major threat is gone.

Two of the most obvious and tangible signs of progress are the mRNA vaccines now being distributed across America and around the world. These vaccines appear to have very high levels of efficacy and safety, and they can be produced more quickly than more conventional vaccines. They are the main reason to have a relatively optimistic outlook for 2021. The mRNA technology also may have broader potential, for instance by helping to mend damaged hearts.

Other advances in the biosciences may prove no less stunning. A very promising vaccine candidate against malaria, perhaps the greatest killer in human history, is in the final stages of testing. Advances in vaccine technology have created the real possibility of a universal flu vaccine, and work is proceeding on that front. New CRISPR techniques appear on the verge of vanquishing sickle-cell anemia, and other CRISPR methods have allowed scientists to create a new smartphone-based diagnostic test that would detect viruses and offer diagnoses within half an hour.

It has been a good year for artificial intelligence as well. GPT-3 technology allows for the creation of remarkably human-like writing of great depth and complexity. It is a major step toward the creation of automated entities that can react in very human ways. DeepMind, meanwhile, has used computational techniques to make major advances in protein folding. This is a breakthrough in biology that may lead to the easier discovery of new pharmaceuticals.

One general precondition behind many of these advances is the decentralized access to enormous computing power, typically through cloud computing. China seems to be progressing with a photon method for quantum computing, a development that is hard to verify but could prove to be of great importance.

Computational biology, in particular, is booming. The Moderna vaccine mRNA was designed in two days, and without access to COVID-19 itself, a remarkable achievement that would not have been possible only a short while ago. This likely heralds the arrival of many other future breakthroughs from computational biology.

Internet access itself will be spreading. Starlink, for example, has a plausible plan to supply satellite-based internet connections to the entire world.

It also has been a good year for progress in transportation.

Driverless vehicles appeared to be stalled, but Walmart will be using them on some truck deliveries in 2021. Boom, a startup that is pushing to develop feasible and affordable supersonic flight, now has a valuation of over $1 billion, with prototypes expected next year. SpaceX achieved virtually every launch and rocket goal it had announced for the year. Toyota and other companies have announced major progress on batteries for electric vehicles, and the related products are expected to debut in 2021.

All this will prove a boon for the environment, as will progress in solar power, which in many settings is as cheap as any relevant alternative. China is opening a new and promising fusion reactor. Despite the absence of a coherent U.S. national energy policy, the notion of a mostly green energy future no longer appears utopian.

In previous eras, advances in energy and transportation typically have brought further technological advances, by enabling humans to conquer and reshape their physical environments in new and unexpected ways. We can hope that general trend will continue.

Finally, while not quite meeting the definition of a scientific advance, the rise of remote work is a real breakthrough. Many more Zoom meetings will be held, and many business trips will never return. Many may see this as a mixed blessing, but it will improve productivity significantly. It will be easier to hire foreign workers, easier for tech or finance workers to move to Miami, and easier to live in New Jersey and commute into Manhattan only once a week. The most productive employees will be able to work from home more easily.

Without a doubt, it has been a tragic year. Alongside the sadness and failure, however, there has been quite a bit of progress. Thats something worth keeping in mind, even if we cant quite bring ourselves to celebrate, as we look back on 2020.

Tyler Cowen is a Bloomberg Opinion columnist. He is a professor of economics at George Mason University and writes for the blog Marginal Revolution. His books include "Big Business: A Love Letter to an American Anti-Hero."

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The silver lining of 2020 - SouthCoastToday.com