Economy


Three Questions To ID If Your Business is Ready for AI

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The truth is somewhere in-between; while it is unlikely to entirely eliminate many occupations over the next ten years, AI and machine learning will impact almost all industries, jobs and business to varying degrees. These systems dramatically improving performance, save time, and free up your expensive human talent to focus on strategic tasks. McKinsey estimates that 59 percent of all manufacturing activities could be automated, while a whopping 73 percent percent of the activities that food service workers perform have the potential for automation. Forrester Research expects "enterprise interest in, and use of, AI to increase as software vendors roll out AI platforms and build AI capabilities into applications," as "enterprises that plan to invest in AI expect to improve customer experiences, improve products and services, and disrupt their industry with new business models."


Automation and anxiety

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In a test against three expert human radiologists working together, Enlitic's system was 50% better at classifying malignant tumours and had a false-negative rate (where a cancer is missed) of zero, compared with 7% for the humans. In a widely noted study published in 2013, Carl Benedikt Frey and Michael Osborne examined the probability of computerisation for 702 occupations and found that 47% of workers in America had jobs at high risk of potential automation. Rather than destroying jobs, ATMs changed bank employees' work mix, away from routine tasks and towards things like sales and customer service that machines could not do. Computers thus reallocate rather than displace jobs, requiring workers to learn new skills.


China's Cryptocurrency NEO Will Change the World As We Know It

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Antshares, the first open-source blockchain platform developed in China, announced a complete rebranding of its blockchain solution into NEO. If you recall at the beginning of this year, China's central bank PBOC (People's Bank of China) announced it was developing an Ethereum-based digital currency to replace the Yuan. The Beijing-Shanghai network that is currently under construction is set to host the world's longest land-based quantum communication channels, stretching over 2,000km with Jinan as its hub. Will Be Uploading Onto the NEO Platform Alex Norta announced that his startup Agrello will be partnering with NEO to develop smart contracts for automation, self-execution, accuracy and transparency.


The Collapse of the Human Labor Force - Eanfar.org

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In 1994, immediately after NAFTA was implemented, the U.S. Bureau of Labor Statistics ("BLS") arbitrarily stopped counting "long-term discouraged workers" in the official unemployment rate. For the victims of Broken Capitalism today--including nearly 25% of the unemployed and under-employed American labor force and over 90% of Americans who have no retirement savings and are drowning in debt just to survive--a Depression-level unemployment rate is not surprising. If you want to learn more about the socioeconomic and political consequences of Artificial Intelligence and what is destroying Capitalism worldwide today and how to fix it, please read Broken Capitalism: This Is How We Fix It. So, my definition of the "Civilian Labor Force" reasonably counts a significant portion of those 90 million erased humans, including significant subsets of the long-term discouraged/displaced population, college student population, over-age-65 population, non-severe disabled population, all of which are able to perform many jobs.


Keep Learning in the Era of Automation

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This along with factors like growing youth population (the total youth population of India has increased from 168 million in 1971 to 422 million in 2011), millions of engineering graduates passing out of Indian universities every year (approximately 1.5 million graduates), decline in new job creation rate, stagnant salaries in leading industries like IT services, cost-cutting pressures, rising inflation rate has all lead to a threat of a jobless future. One need to be aware of the automation taking place in various processes in one's domain and get an understanding of which skill sets will be in demand in the era of automation, artificial intelligence (AI) and machine learning. The advent of automation saw the ushering of a new era, where automated trading & quantitative trading became the norm of the day. Many trading firms moved to automated trading; it led to new lucrative job opportunities for thousands of financial graduates, engineers, and programmers.


Disruptive technologies: from Blockchain to Artificial Intelligence. An interview with Jennifer Zhu Scott - Expert Keynote and Motivational Speakers Chartwell Speakers

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In a traditional financial system, central banks and banks act as centralized trust institutions to allow people who don't know each other to make transactions. So in a society where the traditional financial system isn't working, a decentralized system would enable people to freely trade and transfer value without knowing each other or centralized trust. Artificial intelligence is a general term that represents a set of technologies, which individually but often collectively have very wide applications.


The evolution of employment and skills in the age of AI

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As artificial intelligence alters work done in all manner of industries, companies and governments can help workers transition by supporting incomes and facilitating skills training. Zoƫ Baird: One hundred years ago we invented the high school, but today we haven't really invented the paths to be part of this digital economy. Our labor market now is increasingly going in the direction of requiring a bachelor's degree, a four-year degree, for most growth jobs. James Fallows: Finding ways to support people's income as they make this transition from jobs that are inevitably coming under pressure, whether it's mining or retail or things involving transportation, as auto-driving vehicles come up, so that they can feel both the economic security and the psychic security to be ready for the new jobs that our economy should keep producing.


When AI dominates, what will we do for a crust?

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Future of work experts (yes, it's a thing now) and AI scientists who spoke to Lateline variously described a future in which there were fewer full-time, traditional jobs requiring one skill set; fewer routine administrative tasks; fewer repetitive manual tasks; and more jobs working for and with "thinking" machines. "We don't make computers that have a lot of emotional intelligence," Professor Walsh says. "We are social people, so the jobs that require lots of emotional intelligence -- being a nurse, marketing jobs, being a psychologist, any job that involves interacting with people -- those will be the safe jobs. Jobs growth is already strong in the caring economy with unmet demand in child care, aged care, health care and education -- although many of those jobs are poorly paid.


How 'Noise' can help Businesses Close the Last Mile in Artificial Intelligence

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Third Generation Artificial Intelligence The 21st Century is presently transitioning into the Era of Deep Learning, where leaders like Google are using deep learning algorithms in neural networks find out impacting member from data and use that data to predict a model. The technique uses recurrent neural networks (RNN) to allow the system to auto-correlate historical data and live feeds. For example, if a company took historical data from the top 10 countries by Gross Domestic Product (GDP) with employment ratios, inflation data, gold prices, and stock exchange data and put it all into a historical system, along with live feeds, the neural network would auto-correlate the data. As with any system, the analysis will only be as good as the data; how ever, the challenge with deep learning AI systems is that in most cases, the historical data was not collected with AI systems in mind.


How 'Noise' can help Businesses Close the Last Mile in Artificial Intelligence

#artificialintelligence

Third Generation Artificial Intelligence The 21st Century is presently transitioning into the Era of Deep Learning, where leaders like Google are using deep learning algorithms in neural networks find out impacting member from data and use that data to predict a model. The technique uses recurrent neural networks (RNN) to allow the system to auto-correlate historical data and live feeds. For example, if a company took historical data from the top 10 countries by Gross Domestic Product (GDP) with employment ratios, inflation data, gold prices, and stock exchange data and put it all into a historical system, along with live feeds, the neural network would auto-correlate the data. As with any system, the analysis will only be as good as the data; how ever, the challenge with deep learning AI systems is that in most cases, the historical data was not collected with AI systems in mind.