Category: Uncategorized

Dec 05, 2019 (Heraldkeepers) — A talent-driven economy has become a key requirement for the growth and development of the modern economy. The workforce can generate innovatively, and new ideas surpass all other drivers of economic development. The future success of an economy depends on the quality of talent retained. Some of the main reasons why the modern economy should focus on talents include:

1. Maximize Productivity

With the talent economy, the chance of growth of the modern economy is high. The human capabilities are considered to be the fundamental drivers of economic development. By focusing on the talents and brains, the modern economy will be able to retain the best skills and knowledge. The fresh talents can utilize their innovative ideas and maximize the productivity of individuals, organizations, as well as the entire community, which ultimately leads to the growth and success of the overall economy.

2. Better Development

Focusing on talents can help the modern economy in gaining better development opportunities. The quality of the workforce is of paramount importance for the development of the economy. The availability of skilled talents helps in increasing investments and enhancing the returns on investment for better development of the economy.

3. Expand Capabilities

By giving importance to talent economy, the modern economy can expand its capabilities much easily. The talents acquired can help in overcoming the potential challenges with the use of their innovative and new ideas. The growing demand of the talented workforce across the globe allows the modern economy to expand successfully.

Effect of Intellectual Property Rights and Patents on Economy

Intellectual property rights and patents have a significant impact on the global economy. Apart from a talent economy, intellectual property rights and patents can also help in stimulating the growth and development of the modern economy.

Intellectual property rights play an important role in encouraging innovation, technical change, as well as product development. An IPRS system that favors the diffusion of information through the low-cost imitation of foreign technologies and products is likely to impact the economy of a country positively.

The intellectual property rights also help in rewarding the risk-taking and creativity of the new entrepreneurs and enterprises, thereby leading to the growth of the economy. The IPRs can also help in stimulating dissemination and acquisition of new information. The new information gained paves the way for further inventions.

The patent also provides the firms with certainty that they will face fewer threats of uncompensated appropriation. It helps the firms induce products and technologies more readily, enabling the enhancement of the economy. By strengthening intellectual property rights, the developing countries tend to attract more inflows of technology.

IPRs also encourage the growth and development of interregional as well as international marketing networks that help in achieving economies of scale. A strengthened intellectual property enables inducing greater R & D that helps in meeting the needs of the developing countries.

Focusing on talent as well as intellectual property rights and patents can help in the successful growth and development of the modern economy.

Author : Manahel Thabet

Source: https://www.marketwatch.com/press-release/the-growing-importance-of-talent-base-economy-2019-12-05

Electric scooters dominate the streets of our cities, used for nearly 40 million trips across the country just last year alone. Bitcoin and other cryptocurrencies continue to emerge as formidable alternatives to cash and credit, with companies like Square boasting nearly $125 million in sales. And autonomous cars are making their debut as soon as this month in New York City and California.

These are just a few examples of how disruptive technologies are reaching into all corners of society and reshaping contemporary life; from how we pay for goods and services to how we commute and engage with co-workers and peers from across the globe.

Yet, as disruptive technologies continue to make headlines, they also prompt the need for specialized regulations that protect people and preserve existing infrastructure. This leaves many local and state governments with a daunting challenge: how to reconcile seemingly competing impulses of safety with innovation.

Cities across the nation have banned scooters, citing rises in accidents and fears of fatalities. U.S. Department of the Treasury officials, in the wake of Facebook’s Libra, have recently argued that cryptocurrencies represent threats to national security. And widespread distrust in autonomous cars has driven automakers to halt the once-breakneck pace of development for this technology.

Rather than propel innovators to work to improve these new technologies, history tells us that stringent regulatory legislation or even outright bans have, more often than not, caused innovators to abandon them. In 1865, for example, the British Parliament responded to the advent of steam-powered vehicles — and the fear that they would endanger other users of public roadways — with a law requiring that such vehicles be preceded by a pedestrian waving a red flag as a warning signal. Unsurprisingly, this law discouraged further development of “horseless carriages” in Britain, effectively smothering a nascent industry and creating opportunity for more forward-looking nations. Just 15 years later, the first internal-combustion vehicles were introduced in Germany.

In the face of rapid change, experimentation, and the “failing forward” that defines the current era of disruptive innovation, regulators struggle to keep pace because they continue to adopt a reactive posture, developing rules in response to new technologies on a fixed timeline. Such a standpoint, though, fails to account for the rapid cycles of iterative development that innovations will undergo. And so, to catch up, regulators are often tempted to implement bans or strict precautionary regulations that stifle new technologies from achieving their potentially transformative potential.

In turn, the United States runs the same risk of falling behind other nations at the forefront of this technological revolution.

However, history also illustrates that when regulators strike that right balance in their policies and guidelines, they can encourage innovators and businesses to improve their technologies in ways that reflect needed protections. While federal anti-pollution laws enacted in the late 1970s didn’t ban gasoline-powered automobiles, they did require automakers to reduce emissions to a certain level. Although General Motors initially resisted the new legislation, GM eventually turned to scientists at Corning Incorporated to develop the materials essential for catalytic converters, which made those necessary reductions in emissions possible.

By taking a more adaptive approach to regulation, characterized by a similar cycle of trial and error for the very technologies that they are monitoring, regulators can more effectively respond to new developments, jettison rules that no longer work well, and quickly implement new, more effective policies.

Regulatory spaces, sometimes referred to as “sandboxes,” are emerging as promising incubators for adaptive regulations, encouraging innovators to develop safer or better technology through waivers, close partnerships across sectors, and testing opportunities with small cohorts of customers. These spaces not only allow for technological improvements, but enable the collaborative creation of regulations that benefit both businesses and society. The United Kingdom, for instance, has already put this vision into practice for two dozen companies at the forefront of financial technology — and other countries have followed suit.

Why not extend the same approach to autonomous cars, scooters, and other emerging technologies ranging from 5G to artificial intelligence? We can encourage rapid prototyping and real-time monitoring that surfaces necessary adjustments in the interest of safety and aligned regulations — and all in a low-stakes testing environment.

As we step over yet another electric scooter splayed across the sidewalk or read about problems with another form of cryptocurrency, we should not just gripe about the inconvenience, danger or aesthetic demerits of the technology — or call for the technology to be banned outright.

Instead, let’s facilitate conversations between government officials and private companies to regulate them better. Let’s structure opportunities for innovators and entrepreneurs to pilot their products under close oversight and consultation. If we want these companies to behave better, and technologies to be safer, let’s create a framework that balances their interests with those of the public.

Source: https://www.govtech.com/analysis/Realizing-the-Potential-of-Disruptive-Technologies-Contributed.html

Hundreds of millions of patients are affected by chronic diseases globally, often suffering from several of them. Despite such a huge opportunity, the coverage of chronic conditions with digital solutions is still below the acceptable level. Today, more than twenty common chronic conditions have its own specificity and are currently at its digital development stage, yet all of them face the same challenges in the digital health market, according to a recent Research2Guidance report.

1.  Lack of Consumer Capital

All chronic conditions, apart from digital diabetes, still lack the consumer focus in digital offerings. The main goal of the consumer-oriented approach is to provide and promote a solution that empowers patients to better manage their disease.

2.  Low add value

The existing chronic disease apps often create little added value for end users. Most of the currently available solutions offer either basic educational advice or simple tracking based on manual or automated data input.

3.  Missing business models for consumers and payers

In the digital health market, payer organizations are now pushing digital services to their member base; however, in the majority of chronic conditions, the reimbursement of digital services is still an issue. Apart from the digital diabetes market, consumer bundle subscription offers or payer models (implemented on the pay-per-member-per-month basis) hardly exist. Digital solution providers should pay more attention to creating reimbursement-oriented packages, which can potentially bundle services, digital content, medical products, and accessories.

4.  Insufficient cost-saving evidence for payers

There are many clinical studies across all major chronic conditions that have generated evidence to support efficiency and efficacy of digital solutions in assisting chronic disease patients. What is currently missing is the link to cost savings, which hinders a larger engagement of payer organizations.

5.  Unfavorable demographic and behavioral characteristics of patient populations

Patient population characteristics can have significant implications for digitalizing disease management. Solution providers have to find appropriate strategies to increase patient control despite these demographic and behavioral barriers. The development of caregiver solutions is one of the possible responses to this problem. Currently, nearly all of the available solutions are designed for patients or doctors, whereas the role of caregivers in patient management is still underestimated.

6.  Non-regular use of digital solutions

Chronic conditions are rather different in terms of usage regularity. In conditions with a limited necessity of regular measurements, the creation of passive monitoring solutions, such as wearable-based measurements, could be one of the means to ensure a constant use of digital solutions.

7. Low connectivity level

Although the use of digital apps in managing chronic conditions is increasing, it is not accompanied by significant growth in the use of connected medical devices, such as blood glucose meters, spirometers, blood pressure meters, etc.

8. Missing services for comorbidities

All chronic conditions have numerous comorbidities, which affect patients no less than diagnosed chronic disease. In many cases, patients suffer from several closely-related chronic conditions at a time. However, solution providers currently focus on primary chronic diseases, offering no services for such conditions as anxiety, depression, obesity, etc. As a result, many chronic condition offerings remain single use case solutions, which do not fully address patients’ needs. Weight-loss, hypertension, and diabetes solution providers are already expanding their primary use cases to other conditions, whereas respiratory conditions still lag behind them

9. Low communication support between medical professionals and patients

Communication between healthcare professionals and patients is seen as the most valuable feature within digital health solutions to drive user engagement and retention. Current digital respiratory solutions offer population management features for HCPs or PDF report generation but do not support direct HCP-patient interaction via chat, email or video call.

10. Dependency on slow regulatory processes

Many digital disease management solutions are treated as medical devices under local regulations, if they include regulated components, such as devices and/or medical products. To avoid extensively long time-to-market, services and/or connected devices can be split into regulated (such as a bolus calculator in diabetes solutions) and a non-regulated (such as behavior change features) components.

Research2Guidance states these barriers is the prerequisite for the success of digital health solutions designed for managing chronic conditions. The market has already seen several successful cases when digital solution providers went beyond the obstacles that were perceived as “natural”.

Source:
https://hitconsultant.net/2019/04/15/barriers-digitalization-chronic-conditions/#.XMQB5ujHxPY

There’s no doubt that artificial intelligence (AI) is a transformative technology – perhaps even the most transformative technology available today. But if you think the transformative nature of AI is limited to global tech giants and blue-chip companies, think again. AI is ultimately going to transform every business, in every industry. 

Perhaps you read that last sentence and thought to yourself, well, not my business. My retail business [or HR consultancy, B2B service provider, fashion design business, disaster relief charity, football club or whatever] has nothing to do with AI. I repeat, think again. Even if you can’t yet imagine how AI will impact your organisation, trust that, in the not-too-distant future, it most definitely will.  

That’s why every company needs an AI strategy.  

Like any business transformation, if you want to get the most out of AI, it all starts with strategy. Your AI strategy will help you to focus on your core business objectives and prioritise ways that AI can help deliver those business goals. 

In general, there are two ways businesses are using AI to drive success: 

• Creating intelligent products and services 
• Designing intelligent business processes  

Let’s look at these two uses in a little more detail.  

Intelligent products and services  

AI is, at heart, about making machines smarter, so that they can think and act like humans (or even better). We need only look at the popularity of devices like smart phones, smart fitness trackers and smart thermostats to see how consumers wholeheartedly embrace products and services that can make their life easier, smarter, more streamlined, more connected.  

Source: https://www.forbes.com/sites/bernardmarr/2019/03/21/why-every-company-needs-an-artificial-intelligence-ai-strategy-for-2019/#2a0311c868ea

In theory, that is of hundreds of AI start-ups examined over the past few years, ‘very few companies are building unambiguously labour-replacing technologies’

Microsoft has unveiled the results of a survey of business leaders on the topic of artificial intelligence (AI). The findings are surprising: German and Russian entrepreneurs and executives appear to come out ahead of those from the US and other advanced European economies when it comes to adopting the technology.

Mostly, however, this and several other studies confirm a frustrating problem: the AI hype is making it impossible to figure out how much businesses really need it and are using it.

The 800 respondents in the study came from seven countries — the US, Germany, France, the UK, Italy, the Netherlands and Switzerland. It’s not a globe-spanning data-set and it doesn’t include the potential AI leader, China, nor one of the leaders in AI research, Canada. But the study’s scope is respectable. It shows that the US isn’t among the leaders of the AI race, though a 2018 study by Capgemini Consulting, for example, puts it out ahead and Russia far behind.

The problem with this survey — and a similar one by McKinsey — is that when people say they are using AI in their business, they may not all mean the same thing; they may not even be describing uses that fall under the rather broad definition of AI; and they may simply be boasting because the technology is fashionable.

In a new report, “The State of AI: Divergence, 2019,” the UK venture capital fund MMC Ventures claims that “one in seven large companies has adopted AI; in 24 months, two thirds of large companies will have live AI initiatives. In 2019, AI ‘crosses the chasm’ from early adopters to the early majority.”

Read more: https://www.businesslive.co.za/bd/opinion/2019-03-10-business-leaders-love-ai-in-theory-that-is/

Hebbian Learning

In 1949, Canadian psychologist Donald Hebb proposed the theory of Hebbian learning to explain how a learning task is transformed into a long-term memory. In this way, healthy habits become automatically retained after their continual repetition.

Learning and memory are a consequence of how our brain cells (neurons) communicate with each other. When we learn, neurons communicate through molecular transmissions which hop across synapses producing a memory circuit. Known as long-term potentiation(LTP), the more often a learning task is repeated, the more often transmission continues and the stronger a memory circuit becomes. It is this unique ability of neurons to create and strengthen synaptic connections by repeated activation that leads to Hebbian learning.

Memory and the hippocampus

Understanding the brain requires investigation through different approaches and from a variety of specialities. The field of cognitive neuroscience initially developed through a small number of pioneers. Their experimental designs and observations led to the foundation for how we understand learning and memory today.

Donald Hebb’s contributions at McGill University remain the driving force to explain memory. Under his supervision, neuropsychologist Brenda Milner studied a patient with impaired memory following a lobectomy. Further studies with neurosurgeon Wilder Penfield enabled Milner to expand her study of memory and learning in patients following brain surgery.

Read more: https://theconversation.com/a-memory-pill-cognitive-neurosciences-contributions-to-the-study-of-memory-109707