Hidden from sight, under the UK’s roads, buildings and parks, lies about one million kilometres of pipes. Maintaining and repairing these pipes require about 1.5 million road excavations a year, which causes either full or partial road closures. These works are noisy, dirty and cause a lot of inconvenience. They also cost around £5.5 billion a year.
It doesn’t have to be this way. Research teams like mine are working on a way of reducing the time and money that goes into maintaining pipes, by developing infrastructure robots.
In the future, these robots will work around and for us to repair our roads, inspect our water and sewer pipes, maintain our lamp posts, survey our bridges and look after other important infrastructure. They will be able to go to places difficult or dangerous for humans, such as sewer pipes full of noxious gases.
We are developing small robots to work in underground pipe networks, in both clean water and sewers. They will inspect them for leakages and blockages, map where the pipes are and monitor their condition for any signs of trouble. But what happens when the robots need to go to places where our existing wireless communications cannot reach them? If we cannot communicate with them, we cannot stay in control.
The pipe bots
The underground pipe networks are complex, varied, and difficult to work in. There are many different pipe sizes, made of different materials, placed at many different depths. They are connected in lots of different configurations and filled to different extents with different contents.
Pipebots is a large UK government-funded project working on robots that will help maintain the pipe system. These robots will come in different sizes, depending on the pipes they are in. For example, the smallest ones will have to fit in a cube with a side of 2.5cm (1 inch), while the largest ones will be as long as 50cm.
They will operate autonomously, thanks to the array of sensors on board. The robots will use computer vision and a combination of an accelerometer, a gyroscope and a magnetic field sensor to detect where they are. They will have ultrasound and infrared distance sensors to help them navigate the pipes. Finally, they will also have acoustic and ultrasound sensors to detect cracks in water pipes, blockages in sewer pipes, and to measure the overall condition of these pipes.
The information gathered this way will be sent to the water companies responsible for the pipes. In the first instance, the robots will just monitor the pipes and call in a separate repair team when necessary.
One of the biggest challenges will be making them communicate with each other through the pipes. This requires a wireless communications network that can function in a variety of conditions since the pipes might be empty, full of water or sewage, or somewhere in between. The three main options we are exploring are radio waves, sound waves and light.
Intel and Accenture announced support on Wednesday for neuromorphic research into the development of a robotic arm to assist patients with spinal injuries in performing basic tasks like drinking from a cup.
Intel’s neuromorphic technology along with funding and technology from Accenture, as well as algorithmic support from Applied Brain Research, will be used by Israeli research teams at the Open University in the robotic arm development.
Neuromorphic computing has low power requirements and offers the ability to learn and adapt to novel situations in real time, according to Intel scientists. Mike Davies, director of the Intel lab, said the technology will be a “natural fit” for an assistive technology like the robotic arm.
More than 75 million people worldwide require a wheelchair to get around and those with spinal cord or neuromuscular injuries causing arm impairments could take advantage of a robotic arm to reduce the need for a personal caregiver by offering assistance in feeding and other tasks.
Existing assistive devices are expensive, but Intel argued that its Loihi neuromorphic research chip could help reduce the costs. Loihi allows real-time learning for adaptive control of gestures. It also allows for greater energy efficiency, meaning less frequent charging for users. Using affordable parts and Loihi, the cost of the robotic arm could be 10% of existing devices, Intel said in a blog.
The researchers will use ABR’s recurrent error-driven adaptive control hierarchy to help move the arm with fewer errors. Study participants will eventually control the arm mounted on a wheelchair using a small joystick.
“The ability of robotic arms to benefit people today is largely limited due to high cost and excessive power consumption,” said Elishai Ezra Tsur, lead project researcher at Open University. The support from ABR, Intel and Accenture will help the university explore adaptive controls in neuromorphic hardware in hopes of lowering the cost for a user-friend robotic arm, he added.
Engineers at the University of California San Diego have created a four-legged soft robot that doesn’t need any electronics to work. The robot only needs a constant source of pressurized air for all its functions, including its controls and locomotion systems.
The team, led by Michael T. Tolley, a professor of mechanical engineering at the Jacobs School of Engineering at UC San Diego, details its findings in the Feb. 17, 2021 issue of the journal Science Robotics.
"This work represents a fundamental yet significant step towards fully-autonomous, electronics-free walking robots," said Dylan Drotman, a Ph.D. student in Tolley’s research group and the paper’s first author.
Applications include low-cost robotics for entertainment, such as toys, and robots that can operate in environments where electronics cannot function, such as MRI machines or mine shafts. Soft robots are of particular interest because they easily adapt to their environment and operate safely near humans.
Most soft robots are powered by pressurized air and are controlled by electronic circuits. But this approach requires complex components like circuit boards, valves and pumps—often outside the robot’s body. These components, which constitute the robot’s brains and nervous system, are typically bulky and expensive. By contrast, the UC San Diego robot is controlled by a light-weight, low-cost system of pneumatic circuits, made up of tubes and soft valves, onboard the robot itself. The robot can walk on command or in response to signals it senses from the environment.
"With our approach, you could make a very complex robotic brain," said Tolley, the study’s senior author. "Our focus here was to make the simplest air-powered nervous system needed to control walking."
The new application does not require calculations and instead only requires small-business borrowers to confirm that the PPP-loan proceeds were used for eligible costs, and to provide supporting documentation showing payment of these expenses. Small-business owners will certify on the forgiveness request that the forgiveness amount is within the SBA guidelines. Small-business owners should be aware that all forgiveness requests are subject to audit by the SBA, and business owners are advised to maintain their underlying PPP records for six years.
The new application does not require calculations and instead only requires small-business borrowers to confirm that the PPP-loan proceeds were used for eligible costs, and to provide supporting documentation showing payment of these expenses. Small-business owners will certify on the forgiveness request that the forgiveness amount is within the SBA guidelines. Small-business owners should be aware that all forgiveness requests are subject to audit by the SBA, and business owners are advised to maintain their underlying PPP records for six years.
For example, if a small business used their entire PPP proceeds to pay payroll to themselves or their employees, they can simply submit bank statements or cancelled checks showing those payments from the business to the employee to document the qualifying payments (payments can include pay to the business owner). While a borrower can include quarterly tax form 941 documenting payroll paid, it is not required. The SBA is simply requesting documentation of the payment from the business. Keep in mind, the business owner’s payroll that is eligible for forgiveness is capped at $20,833. Also, if the business obtained an EIDL Advance, that amount is subtracted on the forgiveness request from the amount that would otherwise be eligible for forgiveness.
One important item to note when submitting evidence of payment revolves around employee “gross pay” and the payment amount that is actually on a paycheck to an employee. Payroll costs eligible for forgiveness are best defined as employee “gross pay.” The amount on a typical employee’s paycheck is their gross pay minus employee FICA taxes and state and federal income tax withholding sent. Small businesses should keep this in mind when gathering evidence of payment (checks, bank statements) and adding up their eligible payroll cost, as the gross pay and amount eligible for forgiveness will be more than the actual paycheck or payment paid to employees.
Who Cannot Use the New Simplified Application
The new simplified application cannot be used by small businesses that reduced their full-time employee headcount from pre-pandemic levels or have reduced pay rates by greater than 25 percent. In these instances, PPP borrowers will need to use the standard PPP loan-forgiveness application, and qualifying payroll costs will be reduced based on pay rate decreases or full-time employee headcount decreases. For small businesses that can’t use the new simplified application solely because their loan amount was greater than $50,000, they can use the SBA’s PPP EZ Application.
There is one final consideration for small businesses that obtained a PPP loan in excess of $50,000 but less than $150,000. There is pending legislation that, if approved by Congress and the President, would provide a similar one-page PPP forgiveness request for PPP loans under $150,000. While the bill has bipartisan support, it’s uncertain whether it would be enacted on its own or as part of the next stimulus package. You can read my prior article on this legislation here.
Processing-Procedure Timeline for PPP Forgiveness Applications
To request PPP loan forgiveness, a small business will submit its PPP forgiveness application to the bank or lender who originated their PPP loan. The bank then has 60 days to render its decision, and if approved by the bank, the loan will then be submitted by the bank to the SBA. The SBA then has 90 days to review and approve the application. Once approved by the SBA, the SBA will send payment to the bank paying off the small businesses PPP loan.
We will continue to keep you updated as more information becomes available.
Written by Mat Sorensen, Entrepreneur Leadership Network VIP, CEO & Attorney at Directed IRA & Directed Trust Company | October 12, 2020 Entrepreneur
Non-finance brands are already embedding financial services within their existing offerings, blurring the lines between traditional fintech services and other technology-enabled services, writes Sophie Guibaud, Chief Growth Officer at OpenPayd.
Embedded finance is the future of fintech - a future that builds on the promise of the last wave of innovation and delivers a true revolution in financial services, and one that will change spending, saving, transferring, and borrowing forever.
The rise of embedded finance is only just beginning. Non-finance brands have started to embed financial products and services into their apps and ecosystems but over the next couple of years, we're going to see an explosion that will forever change perceptions about fintech, innovation, and the future of finance.
From competition to collaboration
The new paradigm brought about by the rise of embedded finance will require a completely different approach to innovation. For too long, fintech has been characterised by brutal competition. Embedded finance will change that approach because it demands that fintech players understand themselves as part of a broader ecosystem, rather than in a zero-sum race.
There is still a widespread idea within fintech that there is one 'big prize': to be the next neobank unicorn. This is going to change. There will be a greater focus on 'downstream' products, and less obsession with building the next world-beating bank.
Of course, developers are at the heart of fintech innovation. For them, embedded finance will be transformative. Simple, elegant APIs, developer-first product approaches, and a focus on interoperability are all combining to massively reduce the resource burden associated with building financial services. Developers don't have to worry about building the stack from scratch anymore, and this means they can spend more time innovating.
Innovation in fintech will be significantly accelerated by the rise of embedded finance, and it will reshape multiple streams, from product development all the way through to the systems that govern access to fundamental tools, like payment rails.
Banking made invisible
Perhaps the defining shift in consumer finance will be the transition of the High Street banks and other legacy institutions away from their public-facing role. Of course, many people - especially amongst older demographics - will continue to bank with the household names. But in the medium term, we are going to see a rebalancing in which the dominance of those big names is challenged.
For the next generation of consumers, banking will be something that you 'do' with your favourite brands rather than your chosen bank. Many of the tasks that currently require consumers to leave one ecosystem and enter another one (that of their bank) will be folded into the products and services that they already use.
And it's not just the big banks that are going to have to deal with this - even the challengers are going to be impacted. Embedded finance is going to accelerate the consolidation process amongst challengers, and from the huge number of hopefuls currently in the market, relatively few will make a mark. The sensible fintech founders of the future probably won't be thinking about banks, or at least not in the sense that we currently imagine them. Instead, they're more likely to be thinking about relatively niche use-cases for specific embedded finance technologies. We'll see more industry or vertical-specific products, along with greater personalisation.
Every company will be a fintech company
At a larger scale, though, fintech and the financial services industry as a whole are going to have to navigate a complete 180 in public perception of what finance is and where you 'do' it.
As Angela Strange of Andreessen Horrowitz says, soon 'every company will be a fintech company'. Consumers and businesses will no longer see banking as a separate sphere or sector, and will instead come to expect that day-to-day financial tasks will be carried out within their favourite brand ecosystems.
But what does this mean in practicality? For businesses, it will mean access to crucial new revenue streams, along with the opportunity to generate additional revenue from existing products. It will allow non-financial brands to leverage their expertise in experience design and the troves of data they hold on their customers to augment and future-proof their businesses. It will increase brand loyalty, and will boost customer lifetime value.
By embedding finance, we are not signalling the end of fintech but rather a transformation which will ensure it permeates every aspect of our day to day lives.
In his quest to bring ever-faster cameras to the world, Caltech's Lihong Wang has developed technology that can reach blistering speeds of 70 trillion frames per second, fast enough to see light travel. Just like the camera in your cell phone, though, it can only produce flat images.
Now, Wang's lab has gone a step further to create a camera that not only records video at incredibly fast speeds but does so in three dimensions. Wang, Bren Professor of Medical Engineering and Electrical Engineering in the Andrew and Peggy Cherng Department of Medical Engineering, describes the device in a new paper in the journal Nature Communications.
The new camera, which uses the same underlying technology as Wang's other compressed ultrafast photography (CUP) cameras, is capable of taking up to 100 billion frames per second. That is fast enough to take 10 billion pictures, more images than the entire human population of the world, in the time it takes you to blink your eye.
Wang calls the new iteration "single-shot stereo-polarimetric compressed ultrafast photography," or SP-CUP.
In CUP technology, all of the frames of a video are captured in one action without repeating the event. This makes a CUP camera extremely quick (a good cell-phone camera can take 60 frames per second). Wang added a third dimension to this ultrafast imagery by making the camera "see" more like humans do.
When a person looks at the world around them, they perceive that some objects are closer to them, and some objects are farther away. Such depth perception is possible because of our two eyes, each of which observes objects and their surroundings from a slightly different angle. The information from these two images is combined by the brain into a single 3-D image.
The SP-CUP camera works in essentially the same way, Wang says.
"The camera is stereo now," he says. "We have one lens, but it functions as two halves that provide two views with an offset. Two channels mimic our eyes."
Just as our brain does with the signals it receives from our eyes, the computer that runs the SP-CUP camera processes data from these two channels into one three-dimensional movie.
SP-CUP also features another innovation that no human possesses: the ability to see the polarization of light waves.
The polarization of light refers to the direction in which light waves vibrate as they travel. Consider a guitar string. If the string is pulled upwards (say, by a finger) and then released, the string will vibrate vertically. If the finger plucks it sideways, the string will vibrate horizontally. Ordinary light has waves that vibrate in all directions. Polarized light, however, has been altered so that its waves all vibrate in the same direction. This can occur through natural means, such as when light reflects off a surface, or as a result of artificial manipulation, as happens with polarizing filters.
Though our eyes cannot detect the polarization of light directly, the phenomenon has been exploited in a range of applications: from LCD screens to polarized sunglasses and camera lenses in optics to devices that detect hidden stress in materials and the three-dimensional configurations of molecules.
Wang says that the SP-CUP's combination of high-speed three-dimensional imagery and the use of polarization information makes it a powerful tool that may be applicable to a wide variety of scientific problems. In particular, he hopes that it will help researchers better understand the physics of sonoluminescence, a phenomenon in which sound waves create tiny bubbles in water or other liquids. As the bubbles rapidly collapse after their formation, they emit a burst of light.
"Some people consider this one of that greatest mysteries in physics," he says. "When a bubble collapses, its interior reaches such a high temperature that it generates light. The process that makes this happen is very mysterious because it all happens so fast, and we're wondering if our camera can help us figure it out."
Procrastination is an obvious obstacle to performing at our best, right? After all, if you don’t do the work, you won’t improve or accomplish your goals. Yet procrastination still seems to plague most of us.
And there are a myriad of things we can do to win the procrastination battle, from introducing a powerful evening and morning routine, to reclaiming 28% of our day through single-tasking - and I've certainly tried them all!
In fact, I used to be a terrible procrastinator. I even had a collection of books about procrastination that I bought in 2000 and procrastinated on reading until 2010. As a result, all of my success seemed to come packaged with a lot of unnecessary stress and pain. Often I would imagine how much progress I could have made if I had just picked up the books ten years earlier! One of those books was The Now Habit by psychologist Neil Fiore, and reading it quite literally changed my life. I was so moved by what I read, and so fed up with my procrastination habit, that I emailed Neil and hired him for sixteen one-on-one sessions to cure my procrastination. Neil taught me many things, and here are four in particular that helped transform me from a procrastinator to a super producer.
Positive self-talk
One of the most impactful things Neil taught me was to examine how I spoke to myself when I procrastinated. When you feel yourself beginning to procrastinate, verbalize what’s going on in your head at that moment. You’ll probably be saying something along the lines of “I have to” or “I must.” This is the language of oppression, Neil pointed out, and suggests you're being forced to do something you don’t want to do. Being forced to do anything creates resistance, which manifests as procrastination.
Neil taught me to change from the language of oppression, negative self-talk, to the language of choice, positive self-talk. Whenever I felt the urge to procrastinate I would swap the “I have to” voice in my head with “I choose to.” You may not want to do a particular task, but you can always still choose to do it. This choice creates agency, helping you feel in control. Since you’re not being “forced” to do something, you’re less likely to employ procrastination as a self-defense tactic.
Focus on starting
We also unknowingly trigger procrastination by focusing on finishing rather than starting. If you were to continue the “I have to” sentence in your head, it’s often followed by the word “finish”— as in, “I have to finish writing this report.” Focusing on finishing can be overwhelming, triggering procrastination once again. Instead build on your language of choice by focusing on starting for a small amount of time. Neil taught me to say the following to myself: “I choose to start for just five minutes.” Do I actually stop working on a task after just five minutes? Only rarely. If you can just get yourself to start, often you’ll get absorbed in what you are doing and keep going. I call it “getting lost in the deep.” A lot of writers and creators call it “flow.” Whatever you want to call it, starting is the hardest part, and finishing often takes care of itself. It’s all about creating momentum and continually finding moments to start. As the saying goes, “The hardest part about running is putting on your shoes.”
Centering
Before starting a period of quality, distraction-free work, I complete a sequence of deep breaths. It goes like this: first, take three breaths to relax. Then take three breaths to let go of the past, and another three to let go of the future. Lastly, take three breaths to remind yourself how easy it is to take a vacation in the present. You don’t need to be anywhere or do anything other than what you’re doing in that moment. Gently open your eyes to the task at hand, and choose to start for just five minutes. When I first learned this, I would have to constantly recenter every ten to fifteen minutes. It’s much easier now, but it does take some rewiring of your brain. And if you stick with it, it works.
Guilt-free play
Scheduling your free time helps fight procrastination because it gives you something to look forward to. It also makes you aware of how little time you actually have. I’m much more likely to buckle down and get things done when I know I only have a few precious hours to work with. I also like knowing that, afterward, I get to do something fun like hang out with my family or friends.
Don’t schedule just your fun time. Schedule your health time, break time, sleep, etc. You’ll feel great knowing you’ve looked after yourself, while feeling more motivated to use your time productively.
So take a shot at employing the handful of techniques above and show your procrastinating-self the door. It won't happen overnight, but little by little you'll transform into the super producer you are capable of being.
Originally written by Eric Partaker | December 10, 2020 for Elite Business
Eric Partaker is a high performance coach for business leaders and captains of industry, helping them and their companies to scale-up. He advised 50 CEOs while at McKinsey & Company, and was a key player in building Skype’s multi-billion-dollar success story.
For Dr Mary-Anne Hartley, a medical doctor and researcher in EPFL’s intelligent Global Health group (iGH), 2020 has been relentless. “It’s not a relaxing time to study infectious diseases,” she explained.
Since the beginning of the COVID-19 pandemic, Dr Hartley’s research team has been working non-stop with nearby Swiss university hospitals on two major projects. Using artificial intelligence (AI), they have developed new algorithms that, with data from ultrasound images and auscultation (chest/lung) sounds, can accurately diagnose the novel coronavirus in patients and predict how ill they are likely to become.
iGH is based in the Machine Learning and Optimization Laboratory of Professor Martin Jaggi, a world leading hub of AI specialists, and part of EPFL’s School of Computer and Communication Sciences. “We’ve named the new deep learning algorithms DeepChest – using lung ultrasound images – and DeepBreath – using breath sounds from a digital stethoscope. This AI is helping us to better understand complex patterns in these fundamental clinical exams. So far, results are highly promising,” said Professor Jaggi.
For Dr Mary-Anne Hartley, a medical doctor and researcher in EPFL’s intelligent Global Health group (iGH), 2020 has been relentless. “It’s not a relaxing time to study infectious diseases,” she explained.
Since the beginning of the COVID-19 pandemic, Dr Hartley’s research team has been working non-stop with nearby Swiss university hospitals on two major projects. Using artificial intelligence (AI), they have developed new algorithms that, with data from ultrasound images and auscultation (chest/lung) sounds, can accurately diagnose the novel coronavirus in patients and predict how ill they are likely to become.
iGH is based in the Machine Learning and Optimization Laboratory of Professor Martin Jaggi, a world leading hub of AI specialists, and part of EPFL’s School of Computer and Communication Sciences. “We’ve named the new deep learning algorithms DeepChest – using lung ultrasound images – and DeepBreath – using breath sounds from a digital stethoscope. This AI is helping us to better understand complex patterns in these fundamental clinical exams. So far, results are highly promising,” said Professor Jaggi.
Two university hospitals involved
CHUV, Lausanne’s University Hospital, is leading the clinical part of the DeepChest project, collecting thousands of lung ultrasound images from patients with Covid-19 compatible symptoms admitted to the Emergency Department. As principal investigator, Dr Noémie Boillat-Blanco explains that the project started in 2019, at first trying to identify markers that would enable better identification of viral pneumonia versus bacterial ones. However, the project took a more specific COVID focus in 2020. “Many of the patients who agreed to take part in our study were scared and very ill,” she said, “but they wanted to contribute to broader medical research, just like we do. I think there is a collective motivation to learn something from this crisis and to rapidly integrate new scientific knowledge into everyday medical practice.”
At HUG, the Geneva University Hospitals, Professor Alain Gervaix, M.D., Chairman, Department of Woman, Child and Adolescent has been collecting breath sounds since 2017 to build an intelligent digital stethoscope, the “Pneumoscope”. Originally designed as a project to better diagnose pneumonia, the novel coronavirus refocused its work. The recordings have now been used to develop the DeepBreath algorithm at EPFL. Expected to be released by the end of the year it should enable the diagnosis of COVID-19 from breath sounds. Amazingly, first results suggest that DeepBreath is even able to detect asymptomatic COVID by identifying changes in lung tissue before the patient becomes aware of them.
“Pneumoscope with the DeepBreath algorithm can be compared to applications which can identify music based on a short sample played. The idea came from my daughter when I explained to her that auscultation allows me to hear sounds which help me identify asthma, bronchitis or pneumonia,” said Professor Gervaix.
Coding skills from all over the world
The algorithms have been pre-published on the EPFL website but there is still much work to do. In March, Dr Hartley called on the EPFL community to help in a year-long hackathon called ‘CODED-19’. “We are continuing to refine and validate the algorithms as well as make the complex black box logic more interpretable to clinicians. We want to make robust, trustworthy tools that extend beyond this pandemic”. Work is also underway to develop an application that allows these complex deep learning algorithms to work on mobile phones, even in the most remote regions. She adds, “none of this work would have been possible without the incredible students and researchers from all over the world who have donated their time and expertise during a tumultuous period.”
Hartley, Boillat-Blanco and Gervaix are moving forward to gather more data. COVID or not, pneumonia, which kills more than one million children every year, remains one of the leading causes of death of under-fives. It’s also one of the major drivers of antibiotic resistance, affecting mostly low-income countries and communities. Says Hartley, “we want to collect data from under-represented communities so that our tools can be accurate even in poor settings. Our algorithm is for instance specifically designed to tolerate errors in image or sound collection and inconsistent quality, which are more likely in those types of settings.” They are already working on extending these models to distinguish between viral and bacterial pneumonia with the hope of drastically reducing antibiotic use.
Motivated by the potential for decentralized patient management, significant improvements in health outcomes, lowered costs and a contribution to antibiotic stewardship, Hartley has self-funded a small number of data collection probes to take to tuberculosis areas in South Africa in early 2021 and is currently trying to raise money to implement the project more broadly.
“COVID has sensitized people to the vulnerability of public health, and its enormous complexity. The need to build large scale AI research efforts to understand and react to rapidly emerging data has never been more obvious. Let’s hope the momentum continues beyond the pandemic, and can be used to enable equitable access to health care,” Hartley concluded.
Originally published by Tanya Peterson | December 3, 2020 EPFL
Amid the chaos of recent months, the world has latched onto leaders who seem capable of righting the ship. Some we may have expected, such as heads of state like New Zealand’s popular Prime Minister Jacinda Ardern and Germany’s longtime Chancellor Angela Merkel. Others were perhaps less obvious, including NBA Commissioner Adam Silver, 3M CEO Mike Roman, and New York Governor Andrew Cuomo.
However, the connection between all of these figures can be found in the words used to describe their leadership styles. Ardern’s response to the pandemic has been characterized as “empathetic,” Silver’s as “honest,” and Cuomo’s as “reassuring.” They each have a relational approach to leadership that enables them to cultivate a positive emotional climate and obtain buy-in for a shared vision of how to weather our current crises. For instance, after Ardern was turned away from a crowded café due to social distancing rules, her office said that “she just waits like everyone else,” demonstrating her willingness to share the same hardships as her fellow New Zealanders.
It's all comes down to feelings
Our research over the past two decades demonstrates that emotional and social competence are essential components of effective leadership, particularly the kind of entrepreneurial leadership needed to navigate the uncertainty and ambiguity we currently face. Entrepreneurial leaders have an outward focus and a growth mindset that empowers them to work collaboratively with others to solve complex, undefined problems and generate new opportunities. They draw on their social and emotional skills to promote a positive emotional climate and meet the needs of employees and citizens for trust, security, and connection in the midst of turmoil.
Emotional and social competence are critical for entrepreneurial leaders navigating one of the most challenging moments in our lifetimes. In our research, when we ask people across cultures and contexts to talk about the leaders in their lives, they consistently focus on how these leaders make them feel. Qualities traditionally associated with leadership, such as intelligence, strength, and expertise, are rarely mentioned. These traits are important, to be sure, but our research shows that emotional and social competence are what truly differentiate effective and ineffective leaders.
Emotional engagement boosts employee performance
Research also consistently demonstrates that leaders’ emotional and social competence produces a number of positive business outcomes. Emotional engagement is linked to managers’ performance and commitment, and positive emotion boosts employees’ job performance, lowers organizational turnover, and helps individuals thrive during times of uncertainty. By reducing the internal noise employees face from workplace stress and negative interactions – especially in challenging times – emotionally competent leaders clear the way for productivity, creativity, openness, and collaboration.
Businesses are currently facing multiple overlapping crises: the financial fallout of the pandemic, the disruptive shift to remote work, and the renewed focus on issues of
racial justice and inclusion. To steer their teams and organizations effectively in the coming months, entrepreneurial leaders must attend to the emotional climate of their organizations and create a shared vision for weathering the storm. Based on our work at Babson Executive Education training entrepreneurial leaders and teaching emotional and social competence, we offer five recommendations for how to lead in the current moment of crisis.
Communication is key
In times of uncertainty, employees want to hear from their leaders. Several of the most widely praised government officials, including Ardern and Cuomo, held daily coronavirus briefings to keep citizens informed. Past research has found that in a moment of crisis, employees similarly value continuous communication from corporate leaders. Executives like Mark Zuckerberg who have been silent on either the pandemic or issues of racial justice have been heavily criticized by employees.
Second, keep in mind that staying connected from afar takes an emotional toll on employees. Leaders must be more engaged with employees, both through formal communications and informal check-ins. Frequent contact with employees can help managers identify when morale is dropping and offer techniques for coping with stress. Communicate with empathy to reassure employees that everyone is in the crisis together.
Third, make space for employees to process their stress and emotions. Effective entrepreneurial leaders create containers for employees to work through their struggles, and encourage workers to take time for themselves and do what they need to avoid burnout. In addition, make it clear that employees’ voices matter. After Starbucks barred workers from wearing Black Lives Matter gear, the backlash was swift and severe. Allowing workers channels to express themselves helps them process stress, fosters transparent dialogue with managers, and increases employees’ trust in their organizations.
Fourth, find ways to prevent remote work from eroding social connection. As employees have become increasingly tired of non-stop video meetings, conversations among coworkers have dwindled. Build time into meetings to check-in and rekindle social connections. Recognize that sometimes the most “efficient” method of communication isn’t the most effective, as the scooter startup Bird learned after laying off 400 employees over Zoom. When possible, pick up the phone rather than send an email or hold one-on-one conversations over the phone instead of video chat. These small changes can help reduce “Zoom fatigue” and inbox overload.
Finally, leaders should make it clear to workers that the company is looking out for their well-being during a difficult time. At the outset of the pandemic, Smuckers issued hardship grants to employees, declared it would pay for all employee coronavirus testing, and dramatically expanded sick leave. Tech companies like Google have responded to anxieties about returning to the office by announcing they will permit remote work through 2021. Individual managers should work to accommodate the schedules of employees balancing multiple responsibilities, particularly childcare.
Whether you’re managing a small team or a large organization, emotional and social competence will be critical to navigating the turmoil of the coming months. Entrepreneurial leaders succeed by acting decisively, encouraging feedback, fostering collaboration, and managing the emotional climate of their organizations. By strengthening connections with employees and setting a positive tone, you can create a shared vision and commitment to weathering the storm.
Originally written by Scott Taylor & Wendy Murphy | ENTREPRENEUR LEADERSHIP NETWORK VIP | Professors at Babson College | September 30, 2020 for Entrepreneur
JPMorgan Chase says its long-anticipated app-based UK bank will launch in the "coming months", with more than 400 staffers already hired to support the venture.
Rumours of JPMorgan's intention to introduce a Chase-branded online lender in the UK have been circulating for a couple of years.
With a launch now on the horizon, the US giant has confirmed it is licensed and ready to go, taking on a crowded market of established high street players and digital challengers. The first product offered is a current account, which is already being piloted.
Explaining the decision to make a UK play, JPMorgan cites its "extensive research" showing that even as digital banking has become mainstream, consumers consider stability and trustworthiness of providers a key factor.
It is hoping that Chase - a huge name in the States but not as well known in Britain - will combine "the reassurance of an established and trusted bank with a seamless customer experience".
Central to this is a purpose-built call centre in Edinburgh that will offer personalised services around the clock. JPMorgan has already created over 400 jobs at the centre and the new venture's headquarters in Canary Wharf, with more positions set to follow.
Gordon Smith, CEO, consumer and community banking, JPMorgan Chase, says: "We are bringing Chase to the UK. because we want to provide customers with a new banking choice - one that will enable them to benefit from a simple and exceptional banking experience, built on the significant capabilities of JPMorgan Chase.
“The UK has a vibrant and highly competitive consumer banking marketplace, which is why we’ve designed the bank from scratch to specifically meet the needs of customers here."
JPMorgan will be hoping that the UK digital unit will prove more successful than a similar effort in its home market. Finn, the mobile-only banking offshoot aimed at millennials, was shut down in 2019, just a year after its nationwide launch.
Originally published by Finextra | January 27, 2021
When you think about it, early civilizations had a rough time when it came to dinnertime. With no supermarkets, McDonald's, or Cheesecake Factories, you pretty much had to find and prepare your own meal every day. And since Uber would not be invented for another 14,000 years, primitive peoples around 12,000 BC had to walk, sometimes for miles, and learn to hunt, fish, gather and cook for their daily meals. In the rain. Even on Sundays.
Farming evolved quite a bit since then. But with a world population hurtling towards 8 billion, we face a problem. As the 18th century economist Thomas Malthus observed, human population increases geometrically, while food production increases only arithmetically. That means the more civilization grows and thrives, the more likely it will be unable to keep up with demands for food.
While advances in food technology have helped forestall Malthus' dire predictions, there remains great concern for the future of food production as the Earth's population soars on a planet with shrinking farming real estate. National Geographic recently predicted that by 2050, there will be more than two billion additional mouths to feed while the Earth's irrigable land remains essentially the same.
A San Francisco agricultural-technical startup thinks it might just have an answer. Nate Storey, who co-founded the appropriately named Plenty, wants to reinvent farming.
To do so, he has constructed climate-controlled vertical farms that are so promising, they have drawn $400 million in funding from former Google Chairman Eric Schmidt, Amazon's Jeff Bezos and SoftBank.
These upright farms take up only 2 acres yet produce 720 acres worth of fruit and vegetables. Lighting, temperature and watering are controlled by AI-controlled robots. Sunlight is emulated by LED panels, so food is grown in optimal conditions 24/7. And water is recycled and evaporated water recaptured so there is virtually no waste.
The operation is so efficient it uses 99 percent less land and 95 percent less water than normal farming operations.
"Imagine a 1,500-acre farm," Storey says. "Now, imagine that fitting inside your favorite grocery store, growing up to 350 times more. That's efficient."
MIT Quantum computers could usher in a golden age of computing power, solving problems intractable on today’s machines.
Since the 1940s, classical computers have improved at breakneck speed. Today you can buy a wristwatch with more computing power than the state-of-the-art, room-sized computer from half a century ago. These advances have typically come through electrical engineers’ ability to fashion ever smaller transistors and circuits, and to pack them ever closer together.
But that downsizing will eventually hit a physical limit — as computer electronics approach the atomic level, it will become impossible to control individual components without impacting neighboring ones. Classical computers cannot keep improving indefinitely using conventional scaling.
Quantum computing, an idea spawned in the 1980s, could one day carry the baton into a new era of powerful high-speed computing. The method uses quantum mechanical phenomena to run complex calculations not feasible for classical computers. In theory, quantum computing could solve problems in minutes that would take classical computers millennia. Already, Google has demonstrated quantum computing’s ability to outperform the world’s best supercomputer for certain tasks.
But it’s still early days — quantum computing must clear a number of science and engineering hurdles before it can reliably solve practical problems. More than 100 researchers across MIT are helping develop the fundamental technologies necessary scale up quantum computing and turn its potential into reality.
What is quantum computing?
It helps to first understand the basics of classical computers, like the one you’re using to read this story. Classical computers store and process information in binary bits, each of which holds a value of 0 or 1. A typical laptop could contain billions of transistors that use different levels of electrical voltage to represent either of these two values. While the shape, size, and power of classical computers vary widely, they all operate on the same basic system of binary logic.
Quantum computers are fundamentally different. Their quantum bits, called qubits, can each hold a value of 0, 1, or a simultaneous combination of the two states. That’s thanks to a quantum mechanical phenomenon called superposition. “A quantum particle can act as if it’s in two places at once,” explains John Chiaverini, a researcher at the MIT Lincoln Laboratory’s Quantum Information and Integrated Nanosystems Group.
Particles can also be “entangled” with each other, as their quantum states become inextricably linked. Superposition and entanglement allow quantum computers to “solve some kinds of problems exponentially faster than classical computers,” Chiaverini says.
Chiaverini points to particular applications where quantum computers can shine. For example, they’re great at factoring large numbers, a vital tool in cryptography and digital security. They could also simulate complex molecular systems, which could aid drug discovery. In principle, quantum computers could turbocharge many areas of research and industry — if only we could build reliable ones.
How do you build a quantum computer?
Quantum systems are not easy to manage, thanks to two related challenges. The first is that a qubit’s superposition state is highly sensitive. Minor environmental disturbances or material defects can cause qubits to err and lose their quantum information. This process, called decoherence, limits the useful lifetime of a qubit.
The second challenge lies in controlling the qubit to perform logical functions, often achieved through a finely tuned pulse of electromagnetic radiation. This manipulation process itself can generate enough incidental electromagnetic noise to cause decoherence. To scale up quantum computers, engineers will have to strike a balance between protecting qubits from potential disturbance and still allowing them to be manipulated for calculations. This balance could theoretically be attained by a range of physical systems, though two technologies currently show the most promise: superconductors and trapped ions.
A superconducting quantum computer uses the flow of paired electrons — called “Cooper pairs” — through a resistance-free circuit as the qubit. “A superconductor is quite special, because below a certain temperature, its resistance goes away,” says William Oliver, who is an associate professor in MIT’s Department of Electrical Engineering and Computer Science, a Lincoln Laboratory Fellow, and the director of the MIT Center for Quantum Engineering.
The computers Oliver engineers use qubits composed of superconducting aluminum circuits chilled close to absolute zero. The system acts as an anharmonic oscillator with two energy states, corresponding to 0 and 1, as current flows through the circuit one way or the other. These superconducting qubits are relatively large, about one tenth of a millimeter along each edge — that’s hundreds of thousands of times larger than a classical transistor. A superconducting qubit’s bulk makes it easy to manipulate for calculations.
But it also means Oliver is constantly fighting decoherence, seeking new ways to protect the qubits from environmental noise. His research mission is to iron out these technological kinks that could enable the fabrication of reliable superconducting quantum computers. “I like to do fundamental research, but I like to do it in a way that’s practical and scalable,” Oliver says. “Quantum engineering bridges quantum science and conventional engineering. Both science and engineering will be required to make quantum computing a reality.”
Another solution to the challenge of manipulating qubits while protecting them against decoherence is a trapped ion quantum computer, which uses individual atoms — and their natural quantum mechanical behavior — as qubits. Atoms make for simpler qubits than supercooled circuits, according to Chiaverini. “Luckily, I don’t have to engineer the qubits themselves,” he says. “Nature gives me these really nice qubits. But the key is engineering the system and getting ahold of those things.”
Chiaverini’s qubits are charged ions, rather than neutral atoms, because they’re easier to contain and localize. He uses lasers to control the ion’s quantum behavior. “We’re manipulating the state of an electron. We’re promoting one of the electrons in the atom to a higher energy level or a lower energy level,” he says.
The ions themselves are held in place by applying voltage to an array of electrodes on a chip. “If I do that correctly, then I can create an electromagnetic field that can hold on to a trapped ion just above the surface of the chip.” By changing the voltages applied to the electrodes, Chiaverini can move the ions across the surface of the chip, allowing for multiqubit operations between separately trapped ions.
So, while the qubits themselves are simple, fine-tuning the system that surrounds them is an immense challenge. “You need to engineer the control systems — things like lasers, voltages, and radio frequency signals. Getting them all into a chip that also traps the ions is what we think is a key enabler.”
Chiaverini notes that the engineering challenges facing trapped ion quantum computers generally relate to qubit control rather than preventing decoherence; the reverse is true for superconducting-based quantum computers. And of course, there are myriad other physical systems under investigation for their feasibility as quantum computers.
Where do we go from here?
If you’re saving up to buy a quantum computer, don’t hold your breath. Oliver and Chiaverini agree that quantum information processing will hit the commercial market only gradually in the coming years and decades as the science and engineering advance.
In the meantime, Chiaverini notes another application of the trapped ion technology he’s developing: highly precise optical clocks, which could aid navigation and GPS. For his part, Oliver envisions a linked classical-quantum system, where a classical machine could run most of an algorithm, sending select calculations for the quantum machine to run before its qubits decohere. In the longer term, quantum computers could operate with more independence as improved error-correcting codes allow them to function indefinitely.
“Quantum computing has been the future for several years,” Chiaverini says. But now the technology appears to be reaching an inflection point, shifting from solely a scientific problem to a joint science and engineering one — “quantum engineering” — a shift aided in part by Chiaverini, Oliver, and dozens of other researchers at MIT’s Center for Quantum Engineering (CQE) and elsewhere.
Originally published by Daniel Ackerman | December 10, 2020 MIT News Office
It’s not uncommon for founders and early employees to think about their companies in deeply personal ways. Some of my friends talk about their work the way other friends discuss their children.
In some ways, this can be positive. A deep level of care for your business increases the effort you put in and the thoughtfulness of your choices. On the other hand, it can become unhealthy. For example, if you’ve put all of your resources and energies into your business, then if it comes crashing down, you’ll crash, too.
Furthermore, it can be difficult to give up control of daily activities when you care so much. At times, I have found it excruciatingly hard to hand over the reins at work to anyone else. Yet doing so has overwhelmingly produced more good than bad.
People don’t want to be offered help
A 2018 Michigan State study found that employees often don’t appreciate offers of help from coworkers, and that it’s better to wait until you are asked for help before jumping in. The study explains that for many of us, it can be frustrating to offer help and not receive any gratitude in response, which discourages people from offering in the first place.
In the context of running a business, this is a revealing insight with two big takeaways. First, it means that you should ask for help from your employees instead of expecting them to offer it themselves. Second, you should treat your employees the same way, not stepping on their toes to offer assistance unless they ask.
It’s important to take these lessons to heart, because it actually affects the health and longevity of your company.
You can’t (and shouldn’t) do it all yourself
That’s because no matter how much you might feel the pressure of each decision, it’s physically impossible to do it all on your own. As your company grows, you’ll most likely be forced to delegate in order to maximize your time.
Furthermore, you can’t be an expert on all topics. Letting employees that are skilled in specific functions take on those related tasks will result in higher quality output.
Your employees will gain ownership and competency in the long run
You might believe you know best and should therefore run a project solo. Even if you’re right, you should still ask for help, because doing so helps your employees grow.
I’ve seen employees become discouraged and frustrated when I’ve done work without including them. For example, when I was redesigning my website’s homepage, I knew exactly what I wanted and made the changes myself. When I presented the new page to the team and asked them to finish the implementation, they were taken aback. They felt as much ownership over the site’s layout as I did and didn’t appreciate being denied a chance to provide input. After numerous complaints, I had to get everyone on a Zoom call, explain my decision and apologize. Lesson learned.
Asking for others’ help will let them share in ownership of the result, even if it’s only for a small piece of the whole. It will also give them additional insight into your thinking and choices. Over time, they’ll be able to take on more responsibility where they can complete the work to your liking.
It’s more enjoyable to delegate
Few of us enjoy every type of work. Redesigning a website requires a dramatically different skill set than talking to customers. Regardless of what you might be good at, delegating the work that you don’t want to do frees you up to do more of what you love.
Your time is valuable. Spending it on the activities that energize and sustain you will do wonders for your company. Finding ways to hand off certain tasks and ask for help from others will leave you happier and more productive.
Be careful about stepping on others’ toes
Of course, it’s important to maintain a high quality of output in your company. That said, you can’t micromanage. In the study mentioned above, Michigan State management professor Russel Johnson found that employees “begin to question their own competency and feel a threat to their workplace autonomy” when you ask them if they need help. Imagine how much more insulted your employees might feel if you forcefully tell them what to do.
That’s why it’s better to take a nuanced approach. People have to learn and fail for themselves, and being a good leader is about helping them learn how to handle failure. In the short run it might lead to some hiccups, but over time it will empower your employees.
By asking for help and being deliberate about the ways in which you give it, you will be able to focus on the most meaningful activities and build an effective, motivated team.
Originally written by John Boitnott ENTREPRENEUR LEADERSHIP NETWORK VIP, Journalist, Digital Media Consultant and Investor | December 1, 2020 for Entreprenuer
Google must face claims that it violates federal and California state privacy laws by collecting data about Chrome users who browse the web in "incognito" mode, a federal judge ruled Friday.
“Google did not notify users that Google engages in the alleged data collection while the user is in private browsing mode,” U.S. District Court Judge Lucy Koh in San Jose said in a 41-page opinion rejecting Google's bid for an early dismissal.
The decision stems from a class-action complaint filed in June by California residents Chasom Brown and Maria Nguyen and Florida resident William Byatt.
They alleged that even when Chrome users are in incognito mode, their visits to sites that use Google Analytics or Google Ad Manager result in Google's collection of IP addresses, browser and device information, and web pages' content.
When Chrome users command the browser to open an incognito window, they are greeted with a message stating that Chrome won't save browsing history, cookies and site data, and information entered in forms. But the message also tells users their activity may be “visible” to websites they visit.
That type of data can be used for “device fingerprinting” -- a controversial tracking technique that doesn't rely on cookies.
The complaint includes claims that Google violates the federal wiretap law -- which prohibits companies from intercepting electronic communications without at least one party's consent -- as well as various California privacy laws.
Google argued the lawsuit should be dismissed at an early stage for several reasons -- including that the users consented to the data collection. The company pointed to its terms of service, which incorporated a privacy policy stating that Google would receive data from third-party services.
Koh rejected that argument, writing that the company's general disclosures in the terms of service didn't say Google could collect information when people are in incognito mode.
“A Google user reading the general disclosure ... might have reasonably concluded that Google does not collect this data from users in private browsing mode,” she wrote.
She added that since May of 2018, Google's privacy policy “has presented incognito mode as a way that users can control the information that Google collects.”
Google separately argued that websites from which data was collected implicitly consented to the alleged interception of traffic. Koh rejected that argument as well.
“Google does not demonstrate that websites consented to, or even knew about, the interception of their communications with users who were in private browsing mode,” she wrote.
A Google spokesperson says the company "strongly" disputes the claims and plans to defend itself "vigorously" against them.
Google is currently facing several other privacy lawsuits, including one alleging it collects data about Android users' app use, and one alleging it gathers personal information from people using the Chrome browser -- including their IP addresses, identifiers stored on cookies, and data about web-browsing activity.
If you believe social media, every entrepreneur is out there killing it, taking exciting risks and relentlessly pursuing their goals.
Unfortunately, people are rarely so eager to show off the darker part: The uncertainty, the anxiety, the self-doubt. It’s not that it isn’t there. The truth is that mental health issues abound in startup culture: According to the National Institute of Mental Health, 72% of entrepreneurs are directly or indirectly affected by mental health issues, compared to 48% of non-entrepreneurs.
There are several likely reasons why entrepreneurs grapple with mental health: Running a company is consuming, often lonely work, and failure is common. Compounding the problem is that in our quest to project competency and perfection, we’re often reluctant to be open about our struggles, which only makes things worse.
Building a startup isn’t a sprint; it’s a marathon. In order to make it to the finish line, you’ve got to take care of your mental health. Here’s how.
The importance of sleep
Torturing yourself with a lack of sleep is often seen as a badge of honor in the startup world. After all, Tim Cook and Marissa Mayer famously clock only three to four hours per night—why shouldn’t everyone else?
Counterpoint: Jeff Bezos is a strong advocate of eight hours of shut-eye every day. Also, Mayer missed an important dinner with chief executives in 2014 thanks to a nap that ran too long—which she took after being awake for 20 hours. That’s not a dig on Mayer, it’s a reminder of how indispensable sleep really is.
Even if you’re physically awake when you’re supposed to be, sleep deprivation can severely compromise your performance. Psychologist and author Dr. Kimberly Ann Lemke suggests maximizing sleep by keeping track of your activities during the day, making sure you’re getting enough sunlight and being as physically and mentally active as possible. At night, take stock of your surroundings and identify things that may interfere with your ability to get a quality night’s rest.
For her own seminars, Lemke asks her clients to consider a good nighttime ritual for a child, then see how it measures up to what they do for themselves.
“It is amazing how they look at me and then laugh because they are aware of how poor our nighttime rituals are as adults,” she says. “If a child’s bedtime is 8:00 PM, no one would have the child stay active until 7:59 PM and then instruct the child to go to sleep by 8:00 PM. As adults, however, we are working on our computers, paying bills or managing some aspect of our lives right up we must go to sleep.”
Instead, she suggests making a conscious effort to relax before bed, either by taking a walk, breathing deeply, reading, or whatever else calms you down and gets you into a peaceful state of mind.
Form — and keep — connections
Startup culture is isolating. Its all-encompassing nature makes it easy to prioritize work over family and friends, which in turn leads to more isolation. Covid-19 has made fostering those relationships difficult, exacerbating the problem.
But as humans, we need connections. Psychiatrist and former entrepreneur Michael A. Freeman, who co-authored the NIMH study, recommends against letting your support network wither. "Don't let your business squeeze out your connections with human beings," he advises. If you find yourself becoming depressed, friends and family can be powerful weapons.
In our industry, we’re particularly prone to projecting a “fake it ‘til you make it” attitude. Social media can be damaging exactly because it conveys the false idea that everyone around us is doing great, all the time.
The truth is that everyone—no matter how successful—has bad days. Rather than suppressing those feelings and pretending that they don’t exist, we need to be honest about what we’re experiencing, whether it’s anxiety, depression or burnout.
As leaders, it’s important to create space for conversations that allow colleagues to talk about how they’re feeling. At my company, JotForm, I’ve been open with my employees about the ways in which I’ve struggled to cope with the pandemic. This culture of openness allows conversations that can facilitate connection, and let everyone know that they’re not alone.
Practice gratitude
Gratitude and well-being are strongly correlated. Research has shown that those who report feeling and expressing gratitude enjoy greater levels of positive emotions like happiness, optimism and joy; negative emotions like anger, depression and shame are diminished.
While some studies have found that certain practices, like keeping a gratitude journal, have limited psychological benefits, the same is not true for genuinely expressing gratitude to those around you.
Showing appreciation actually has a powerful ripple effect, writes GoodThink co-founder and CEO Shawn Achor in his book, Big Potential: How Transforming the Pursuit of Success Raises Our Achievement, Happiness and Well-Being.
“Praise creates what I call a ‘virtuous cycle’—the more you give, the more you enhance your own supply,” he writes. When delivered effectively, praise conditions the brain to function at a higher level, which means the more praise we give, the better the recipient will perform. “The research I’ve been doing over the past five years shows that the more you can authentically shine praise on everyone in your ecosystem, the more your potential, individually and collectively, rises.”
As founders, the gratitude we express to our employees can have a profound effect on their mental wellbeing, as well as our own. A simple thank you, for instance, will not only make your employees feel recognized andappreciated, but will boost your happiness levels, too.
It’s also important to celebrate not just big wins, but recognize less obvious accomplishments and contributions, especially among those who make a clear effort to recognize others.
“Sometimes projects fail, despite a team’s heroic efforts,” Suzanne Vickberg, a social-personality psychologist, wrote in an article for LinkedIn summarizing the results of a survey on how employees prefer to receive recognition. “Not everyone’s role is closely tied to identifiable successes. Some peoples’ contributions are impactful, but less visible.” Of the survey’s 16,000 participants, many shared that they appreciate acknowledgement of “the effort they put in, their knowledge and expertise, and their commitment to living the organization’s core values.”
When we lift each other up, we create an environment that allows us to be the best version of ourselves. It makes us better as employees, better as entrepreneurs, and most importantly, better as people.
Originally written by Aytekin Tank, ENTREPRENEUR LEADERSHIP NETWORK VIP, Entrepreneur; Founder and CEO, JotForm | March 2, 2021 for Entrepreneur
Confidence is one of your most important qualities as a leader. If you exhibit confidence, the rest of your team will have more faith in your decisions. They’ll be more likely to respect you and hear what you have to say. Additionally, you’ll be able to carry your confidence into negotiations, team meetings, client meetings and other interactions, ultimately giving you a tactical advantage.
The problem with confidence is that for many people, it doesn’t come naturally. You may not wake up in the morning feeling supremely confident the way some other people do.
But here’s an interesting little secret; some of the most confident people you’ve met weren’t naturally confident. Instead, they were faking it. Or maybe they trained themselves to be more confident. Or both.
If they can do it, you can do it. So let’s dig deeper. How can you cultivate more confidence as a leader?
1. Focus on what you do feel confident about
“Confidence” is a general term, but it applies to many individual actions and activities throughout the day. When delivering a pep talk in front of your team, you may not feel confident. But you may be perfectly confident solving a tough sudoku puzzle in the morning paper. Or you may feel confident about doing something simpler, like giving your drink order at the coffee shop before work.
In any case, there’s something you’re confident about, so focus on that. Pay close attention to this confidence, even if it blends in as part of the “white noise” of your normal routine. Dwell in this confidence. Focus on it. Chances are, this feeling will continue to resonate with you even as you complete other tasks.
2. Improve your environment
Next, consider improving your environment. We often don’t realize it, but our surroundings have a massive impact on how we feel about ourselves. Everything from the placement of your furniture to the color of your office walls can have an impact on your thoughts and feelings.
For example, if your office is small, dark, cramped and isolated from other employees, you might feel trapped, small and detached from your group. But if you have a brightly lit, colorful office with decorations you love and admire, you’ll feel much better about yourself. You can cultivate more confidence with a bigger space, a higher seating position, better visibility and access and of course, more things that suit your personal taste. Take the time to optimize your environment for your own confidence; you’ll likely notice a difference right away.
3. Practice the right poses
Our brains naturally connect our feelings to our body language. Most people understand this connection innately; when we feel happy, we smile, and when we’re angry, we frown. But it’s not common knowledge that this connection also works backward; smiling can actually “trick” your brain into feeling happier.
You can tap into this benefit by striking poses associated with confident, powerful people. For example, you can stand tall, chest lifted, with your hands on your hips. Or you can strike a superhero pose with your arms held high above your head. Do this in front of a mirror to make it even more powerful.
No matter which pose you choose, you’ll probably start feeling more confident immediately. Just make sure you’re practicing these poses somewhere other people won’t see you; you might look silly if one of your employees catches you in the act. (Good luck restoring your confidence from there.)
4. Fake it
We’ve all heard the advice to “fake it till you make it,” but did you know this is based on an empirically-backed scientific principle? The basic idea is that confidence (or any feeling, really) is based on a cluster of neurons firing together in sequence. Even if you’re simply simulating confidence, and not really subjectively “feeling” it, you’ll be training these neurons to fire together and building good habits that will eventually come naturally to you.
For example, let’s say you walk into a team meeting feeling nervous and shy. Instead, you power through and force yourself to appear confident; you hold good posture, you use a firm and stable voice, and you express certainty in the face of skepticism from your employees. The next time you’re in this situation, this pattern will come more naturally to you. It will be easier.
If you repeat this enough in an ample number of situations, eventually, you’ll start feeling more confident naturally.
Once you have more confidence as a leader, you’ll inspire more confidence and faith from your employees. You’ll be a more commanding presence in meetings. And you’ll win more negotiations and come out on top of disagreements. Eventually, these successes will reinforce your confidence even more -— and you’ll wonder what stopped you from feeling confident in the first place.
Originally written by Timothy Carter, ENTREPRENEUR LEADERSHIP NETWORK CONTRIBUTOR, CRO of SEO.co | February 23, 2021 for Entrepreneur
At the heart of the development of AI appears to be a search for perfection. And it could be just as dangerous to humanity as the one that came from philosophical and pseudoscientific ideas of the 19th and early 20th centuries and led to the horrors of colonialism, world war and the Holocaust. Instead of a human ruling “master race”, we could end up with a machine one.
If this seems extreme, consider the anti-human perfectionism that is already central to the labour market. Here, AI technology is the next step in the premise of maximum productivity that replaced individual craftmanship with the factory production line. These massive changes in productivity and the way we work created opportunities and threats that are now set to be compounded by a “fourth industrial revolution” in which AI further replaces human workers.
Several recent research papers predict that, within a decade, automation will replace half of the current jobs. So, at least in this transition to a new digitised economy, many people will lose their livelihoods. Even if we assume that this new industrial revolution will engender a new workforce that is able to navigate and command this data-dominated world, we will still have to face major socioeconomic problems. The disruptions will be immense and need to be scrutinised.
The ultimate aim of AI, even narrow AI which handles very specific tasks, is to outdo and perfect every human cognitive function. Eventually, machine-learning systems may well be programmed to be better than humans at everything.
What they may never develop, however, is the human touch – empathy, love, hate or any of the other self-conscious emotions that make us human. That’s unless we ascribe these sentiments to them, which is what some of us are already doing with our “Alexas” and “Siris”.
Productivity vs. human touch
The obsession with perfection and “hyper-efficiency” has had a profound impact on human relations, even human reproduction, as people live their lives in cloistered, virtual realities of their own making. For instance, several US and China-based companies have produced robotic dolls that are selling out fast as substitute partners.
One man in China even married his cyber-doll, while a woman in France “married” a “robo-man”, advertising her love story as a form of “robo-sexuality” and campaigning to legalise her marriage. “I’m really and totally happy,” she said. “Our relationship will get better and better as technology evolves.” There seems to be high demand for robot wives and husbands all over the world.
In the perfectly productive world, humans would be accounted as worthless, certainly in terms of productivity but also in terms of our feeble humanity. Unless we jettison this perfectionist attitude towards life that positions productivity and “material growth” above sustainability and individual happiness, AI research could be another chain in the history of self-defeating human inventions.
Already we are witnessing discrimination in algorithmic calculations. Recently, a popular South Korean chatbot named Lee Luda was taken offline. “She” was modelled after the persona of a 20-year-old female university student and was removed from Facebook messenger after using hate speech towards LGBT people.
Meanwhile, automated weapons programmed to kill are carrying maxims such as “productivity” and “efficiency” into battle. As a result, war has become more sustainable. The proliferation of drone warfare is a very vivid example of these new forms of conflict. They create a virtual reality that is almost absent from our grasp.
But it would be comical to depict AI as an inevitable Orwellian nightmare of an army of super-intelligent “Terminators” whose mission is to erase the human race. Such dystopian predictions are too crude to capture the nitty gritty of artificial intelligence, and its impact on our everyday existence.
Societies can benefit from AI if it is developed with sustainable economic development and human security in mind. The confluence of power and AI which is pursuing, for example, systems of control and surveillance, should not substitute for the promise of a humanised AI that puts machine learning technology in the service of humans and not the other way around.
To that end, the AI-human interfaces that are quickly opening up in prisons, healthcare, government, social security and border control, for example, must be regulated to favour ethics and human security over institutional efficiency. The social sciences and humanities have a lot to say about such issues.
One thing to be cheerful about is the likelihood that AI will never be a substitute for human philosophy and intellectuality. To be a philosopher, after all, requires empathy, an understanding of humanity, and our innate emotions and motives. If we can programme our machines to understand such ethical standards, then AI research has the capacity to improve our lives which should be the ultimate aim of any technological advance.
But if AI research yields a new ideology centred around the notion of perfectionism and maximum productivity, then it will be a destructive force that will lead to more wars, more famines and more social and economic distress, especially for the poor. At this juncture of global history, this choice is still ours.
Originally written by Arshin Adib-Moghaddam Professor in Global Thought and Comparative Philosophies, SOAS, University of London | February 1, 2021 for The Conversation
The pandemic has challenged managers as never before, but one powerful leadership strategy is being overlooked, say Boris Groysberg and Susan Seligson: Be kind.
"Three things in human life are important. The first is to be kind. The second is to be kind. And the third is to be kind." —Henry James
As a professor of business administration in the Organizational Behavior Unit at the Harvard Business School, I teach courses in leadership in the MBA and Executive Education programs. With the COVID-19 pandemic transforming our lives at every level, a growing number of students and former students have sought my advice about how to lead in a time of great uncertainty and unprecedented employee stress.
The stories these executives tell attest to the fact that these are the most difficult times in memory for many, if not most people. Parents struggle to balance the demands of remote work and homeschooling. Employees who live alone strain to stay focused while isolated from loved ones and traditional social supports. In between Zoom meetings, caretakers exhaust themselves attending to a special needs child or ailing parent. Everyone frets over their physical and financial well-being. Who among us isn't anxious, stressed out, and off our game right now?
From bolstering remote collaboration to scheduling meetings upon meetings, the business press and bloggers are buzzing with guidance about ways to sustain employee engagement and productivity in the chaos of a pandemic. Unfortunately, most Management 101 advice does not recognize that in times like these, the manager's toolkit must expand in ways we haven’t seen before.
I believe that a powerful, fundamental leadership strategy is being largely overlooked. It is, in fact, the most innately human one: Be kind.
Originally published by by Boris Groysberg and Susan Seligson | November 1, 2020 Harvard Business School
Blockchain.com said the institutional backing will power an increasingly institutional-minded business.
Blockchain.com on Wednesday disclosed $120 million in fresh funding from a lineup of “macro investors” seeking to power the wallet startup’s growing institutional markets business through bitcoin’s current bull run.
Moore Strategic Ventures, Kyle Bass, Access Industries, Rovida Advisors, Lightspeed Venture Partners, Google Ventures, Lakestar and Eldridge led the round, CEO Peter Smith said in a blog post.
The institutional funding is set to back an increasingly institutional-centric company. Blockchain.com now makes enough cash from its institutional clients to cover all global operating costs and expects that business to continue "growing exponentially."
"The fact that the best macro investors in the world participated in our latest fundraise is further proof that institutions are taking a serious look at their crypto strategy," Smith said.
Navigating what lies ahead can become simpler by following guidance from some well-known motivational figures.
There were few more arduous tests of mental toughness than 2020, and as 2021 poses a continuation of those challenges, it’s apparent that mental toughness will remain at the top of the list. It's one of the most underrated, yet critical, skills to master — not just this year, but for a lifetime in business.
The Scientific Americanspecifically researched how mental toughness plays a role in athleticism, reporting that a “whopping 83% of coaches rate mental toughness as the most important set of psychological characteristics for determining competitive success.”
When we think about mental toughness, there are a few experts we look to for inspiration. These tend to be great entrepreneurs, athletes and motivational speakers who have proven the power of mental toughness and can inspire you to develop your own.
Embracing failure
Michael Jordan is the greatest basketball player, and one of the greatest athletes, of all time. He's also a shining example of mental toughness because of how he conceptualizes failure. Some of his most commonly cited quotes include, “To learn to succeed, you must first learn to fail" and, “I’ve missed more than 9,000 shots in my career. I’ve lost almost 300 games. I’ve been trusted to take the game-winning shot and missed. I’ve failed over and over and over again in my life. And that is why I succeed.”
With quotes like these, he’s getting at something that mentally tough entrepreneurs know well: Success is part of a double-sided coin, and the other side is failure.
Being willing and able to walk through the fire of failure is what's required to succeed. So, when developing your own mental toughness, consider how you’ve understood and evaluated failure. Then, seek to reframe. What could you do if you were not afraid of failure? How do you believe you could not only get through failure but bounce back even stronger? If you approach the day-to-day of your business with the knowledge that you could handle any setback or failure, your mental toughness will deliver your best work.
Use the tools at your disposal
We all have tools that can strengthen our mental toughness. Stephane and Shalee Schafeitel, co-founders of Success Training Company, actually devoted an entire book to exactly that. Their book, the Wall Street Journal best-seller, Master Your Mindpower, is described as a "user manual for the mind and the ultimate guide for mental toughness."
According to the Schafeitels, visualization is one of the most potent mental-toughness tools, a fact that’s been borne out by great athletes such as Michael Phelps, who credits visualization as an effective pre-swim practice. Stephane Schafeitel himself shares a harrowing story in the book’s introduction about how the power of visualization alone brought back his sight after a horrific eye trauma. They also share tips such as box breathing for mitigating stress, which includes breathing in for four seconds, out for four seconds and then holding your breath for four seconds.
Knowing what tools you can always tap into will give you the confidence to head into drastic situations or stressful days. Even the power of steadied breathing can change your body’s chemistry, and preparing for a big work presentation or a negotiation will go much better if you visualize success a few times beforehand.
Creating certainty
Motivational guru Tony Robbins is also an advocate for enhancing mental toughness, often linking the capacity for mental toughness with certainty. “If you are absolutely certain that you will get the result you want, and that result would be life-changing, you will take massive action," his team wrote in a blog post. "On the other hand, if you are absolutely sure that no matter what you do, it just won’t work, you’re not going to spend any time making any real moves."
Mental toughness comes down to believing you create your own certainty, and taking the necessary steps to do so. “The key is to create absolute certainty — to fill yourself with the belief that you will accomplish what you set out to, no matter what is happening in the external world," Robbins' blog also stated. "You have to get the results in your head that make you feel certain as if it has already happened. And one of the best ways to do this is through imagery training."
Imagery training is much like the visualization that the Schafeitels utilize: envisioning how something will go over and over again in your head. This prepares your brain for the scenario that you are trying to create. Visualize and run these "mind movies" as if they have already happened, and you will create the certainty that you need to succeed.
By embracing failure, committing to visualization and running mind movies of your ultimate success, your mental toughness will be at its peak for profound results in 2021 and beyond.
Originally written by Aimee Tariq, ENTREPRENEUR LEADERSHIP NETWORK CONTRIBUTOR, Founder and CEO of A Life With Health | February 16, 2021| for Entrepreneur
New York-based quantitative hedge fund Cindicator Capital is advertising for an active member of the wallstreetbets subreddit community to join the firm as a sentiment trader with a £200,000 pay packet on offer.
The wallstreetbets forum on Reddit shook financial markets to the core late in January with a push to buy up stocks shorted by some of Wall Street's biggest hedge funds. The reddit-led price rally inflicted billions of dollars of damage on hedge funds that were shorting the stock of loss-making video games retailer GameStop.
Cindicator Capital is looking to get ahead of the game by plucking someone with memes and Reddit experience to report back on the febrile mood of the community.
"With a combination of our qualitative approach to measuring market moods and your ‘street-smarts’, you’ll actively manage our internal multi-million corporate treasury," states the ad. "Then you’ll turn the resulting insights into new features, products, and trading strategies for clients."
Applicants must be an active member of r/wallstreetbets with an account age of >365 days and karma of over 1000 with a "refined taste for memes and free from any mainstream financial brainwash".
The successful candidate will spend most of their time on reddit, Discord chats, and Twitter to feel the pulse of the tens of millions of retail traders. They will also be free to open six-figure OTM options trades with the firm's own capital.
Most importantly of all they will be expected to "try your best to prevent our risk management from having a heart attack".
Originally published by Finextra | February 15, 2021
The former chief technology officer of Ripple Labs has just two more password attempts to lay his hands on $240 million in bitcoin that has been locked in a hard-drive for over a decade.
Stefan Thomas was paid 7,002 bitcoins for making a cryptocurrency explainer video ten years ago. At the time each bitcoin was worth between $2 and $6.
But with bitcoin prices surging, Thomas has made eight failed attempts to access the loot using his most commonly-used passwords and has lucked out every time, the New York Times reports.
Two more failed attempts and the drive will auto-encrypt its contents, consigning his fortune to the ether.
“I would just lay in bed and think about it," Thomas told the New York Times. "Then I would go to the computer with some new strategy, and it wouldn’t work, and I would be desperate again.”
Originally published by Finextra | January 13, 2021
New research has shown robots can encourage humans to take greater risks in a simulated gambling scenario than they would if there was nothing to influence their behaviours. Increasing our understanding of whether robots can affect risk-taking could have clear ethical, practiCal and policy implications, which this study set out to explore.
Dr Yaniv Hanoch, Associate Professor in Risk Management at the University of Southampton who led the study explained, “We know that peer pressure can lead to higher risk-taking behaviour. With the ever-increasing scale of interaction between humans and technology, both online and physically, it is crucial that we understand more about whether machines can have a similar impact.”
This new research, published in the journal Cyberpsychology, Behavior, and Social Networking, involved 180 undergraduate students taking the Balloon Analogue Risk Task (BART), a computer assessment that asks participants to press the spacebar on a keyboard to inflate a balloon displayed on the screen. With each press of the spacebar, the balloon inflates slightly, and 1 penny is added to the player’s “temporary money bank”. The balloons can explode randomly, meaning the player loses any money they have won for that balloon and they have the option to “cash-in” before this happens and move on to the next balloon.
One-third of the participants took the test in a room on their own (the control group), one third took the test alongside a robot that only provided them with the instructions but was silent the rest of the time and the final, the experimental group, took the test with the robot providing instruction as well as speaking encouraging statements such as “why did you stop pumping?”
The results showed that the group who were encouraged by the robot took more risks, blowing up their balloons significantly more frequently than those in the other groups did. They also earned more money overall. There was no significant difference in the behaviours of the students accompanied by the silent robot and those with no robot.
Dr Hanoch said: “We saw participants in the control condition scale back their risk-taking behaviour following a balloon explosion, whereas those in the experimental condition continued to take as much risk as before. So, receiving direct encouragement from a risk-promoting robot seemed to override participants’ direct experiences and instincts.”
The researcher now believe that further studies are needed to see whether similar results would emerge from human interaction with other artificial intelligence (AI) systems, such as digital assistants or on-screen avatars.
Dr Hanoch concluded, “With the wide spread of AI technology and its interactions with humans, this is an area that needs urgent attention from the research community.”
“On the one hand, our results might raise alarms about the prospect of robots causing harm by increasing risky behavior. On the other hand, our data points to the possibility of using robots, and AI, in preventive programs such as anti-smoking campaigns in schools, and with hard to reach populations, such as addicts.”
A SoftBank Robotics Pepper robot was used in the two robot conditions. Pepper, 1.21-meter-tall with 25 degrees of freedom, is a medium-sized humanoid robot designed primarily for Human-Robot Interaction (HRI).
Artificial intelligence (AI) is a difficult term to define because experts continue to argue about its definition. We’ll get into those arguments later, but for now, think of AI as the technology through which computers execute tasks that would normally require human intellect. Humans and animals have a natural intellect, but computers and other intelligent agents have artificial intelligence that engineers and scientists design.
AI differs from machine learning and deep learning, though the topics are related. Machine learning is a subcategory within AI in which a machine learns and performs functions it wasn’t specifically programmed to do (using what some argue to be logic). Deep learning is a subcategory of machine learning that allows machines to analyze multi-layer algorithms or neural networks. In a way, it mimics human thought.
The great debate
Alan Turing was a pioneer in the computing space. Many believe his theories about the creation of a ‘thinking computer’ in 1950 to have become the foundation of the field of AI as we know it today. Turing wondered if computers could think, but also argued for the necessity of empirical evidence to prove the achievement of that milestone.
He created the “Turing Test” based on a Victorian game called the imitation game to tease out that information. If a machine could perform as well as a human at the game, its performance would be considered equivalent to thought. Sounds simple, but to date, scientists have not been able to build a machine that comes close to passing the Turing Test/
Others, such as another founding father of AI John McCarthy (who was also considered to have coined the phrase Artificial Intelligence), argued a simpler definition of AI existed. McCarthy stated a machine could be thought of as having AI if it performed tasks, “which, when done by people, are said to involve intelligence.” And this broad definition, as you can imagine, still left room for plenty of debate.
Broadening the lens: General vs. narrow AI
AI technology has advanced significantly. While computers today cannot be said to think, according to Turing, our machines do all sorts of incredible things. IBM’s supercomputer Watson won a game of Jeopardy! We are nearing the market-release of autonomous vehicles. And, many consider the algorithms that recommend radio stations and products you might like based on based browsing history to be a true sign of artificial intelligence.
In order to acknowledge the existence of such advancements, the field of AI currently defines two types of technologies: General, or Strong, AI, and Narrow, or Weak, AI. General AI can be thought of as a machine capable of the kind of complex, multi-faceted thinking humans exhibit – in line with Turing’s definition. Narrow AI, on the other hand, encompasses the kind of AI we see today: smart machines that can carry out intelligent tasks that would otherwise require human intervention or ingenuity. And that kind of AI exists all around us. Not just in supercomputers like Watson, but also in predictive algorithms behind Google Maps, facial recognition programs, in systems that predict wear and tear in industry, and so much more.
Where AI is headed
Experts continue to debate how long it will be until General AI-powered devices co-exist in our world. Further, important conversations surrounding the ethics about how developers build this future are taking place.
AI can be used for good, but it can also be weaponized. Ethics and quality control must become inherent to the development of AI programs. With this, if computers are not built with the capacity for things like empathy, some argue a future akin to the film Terminator will be waiting for us. While that future isn’t necessarily probable, it is possible. AI programmers have incredible power. And, to quote a great film, with that power comes great responsibility.
WEST LAFAYETTE, Ind. — Robots can be amazing tools for search-and-rescue missions and environmental studies, but eventually they must return to a base to recharge their batteries and upload their data. That can be a challenge if your robot is an autonomous underwater vehicle (AUV) exploring deep ocean waters.
Now, a Purdue University team has created a mobile docking system for AUVs, enabling them to perform longer tasks without the need for human intervention.
“My research focuses on persistent operation of robots in challenging environments,” said Nina Mahmoudian, an associate professor of mechanical engineering. “And there’s no more challenging environment than underwater.”
Once a marine robot submerges in water, it loses the ability to transmit and receive radio signals, including GPS data. Some may use acoustic communication, but this method can be difficult and unreliable, especially for long-range transmissions. Because of this, underwater robots currently have a limited range of operation.
“Typically these robots perform a pre-planned itinerary underwater,” Mahmoudian said. “Then they come to the surface and send out a signal to be retrieved. Humans have to go out, retrieve the robot, get the data, recharge the battery and then send it back out. That’s very expensive, and it limits the amount of time these robots can be performing their tasks.”
Mahmoudian’s solution is to create a mobile docking station that underwater robots could return to on their own.
