If you think artificial intelligence is an entirely theoretical pursuit, a quick trip to Kaggle is illuminating. Kaggle is a website that runs competitions, sometimes with serious cash prizes, between teams vying to solve real-world problems by designing algorithms that trawl through big data sets. There are currently 17 competitions up and running. The biggest prize, $100,000 (£77,435), is being offered by an investment company for the team that reveals how news reports affect stock prices. The second and third biggest – both offering around $50,000 – seek to predict when earthquakes will occur and how loyal Brazilian shoppers are.
Last year, we had the benefit of leaning on the recent findings of our inaugural Cycle of Progress digital transformation benchmark study to inform my predictions. This global survey examines global business leaders' hopes and fears about emerging technologies, and reveals which technologies they are actively implementing to drive the digital transformation of their business--versus which ones are yet to live up to the hype. Based on our findings, I see several technologies continuing to lead the way in 2019, namely Internet of Things (IoT), Artificial Intelligence (AI) and blockchain. More than half (53%) of Cycle of Progress respondents say that they have adopted IoT in some shape or form so far. Already well established in many businesses, IoT applications and services are leading the pack in having the greatest positive impact.
The combination of artificial intelligence (AI) and blockchain is transforming various industries by implementing new applications. AI is driving computers by complex computational tasks with autonomy. The blockchain is enabling groups of computers to connect together resources to perform heavy computational tasks. The combination of these two technologies is able to eliminate shortcomings and transforms all the industries. Healthcare: AI and blockchain drive the healthcare platform by introducing various advanced technologies, and managing electronic medical and health records (EMR and EHR).
I have over 25 years of experience in senior technology roles in payments and capital markets space, where I have developed and launched innovative, award winning digital payment and stock trading solutions. I won TD Bank Group's "Inventor of the year" 2017 award, and I lead TD's Enterprise Payments Technology Innovation team. I have a master's degree in Electrical Engineering with major in Computer Science from the University Of Belgrade. The very definition of machine learning is that it is a software system which is able to adapt to new circumstances and to detect and extrapolate patterns, based on previously observed data (learning), without need to change the rules encoded inside the software. As such, it has significant potential in being applied to monitoring transactions – in payments, capital markets and insurance as well.
Artificial Intelligence has supplanted blockchain and cryptocurrency as the startup industry tech workers are most interested in joining, according to a new report from AngelList, a U.S.-based platform that connects startups with investors. Machine Learning & Artificial Intelligence was the top industry coveted in 2018 by the 8 million job seekers registered on the platform's job board, AngelList Talent, the company announced Thursday. "The amount of users searching for positions in AI was one of the biggest surprises of the year," says Amit Matani, AngelList Talent's CEO. "Another surprise was the decline of the Crypto Boom." Though excitement about blockchain and cryptocurrency skyrocketed in 2017 as it minted a number of overnight billionaires from their investments, "it's definitely died down significantly," Matani told Forbes.
The Internet of Things (IoT) is set to spread into every area of the enterprise over the next year, in order for that to happen it will need to start employing some of the newer, emerging technologies. This will be particularly true of Industrial IoT (IIoT) as more and more organizations start using the opportunities it offers to achieve business goals. Frank Vella, COO of Information Builder, points out that with the emergence of smart cities and new manufacturing processes, for example, there is a growing need for large pools of data. This data will be used to build more efficient, broader ecosystems that provide proactive insights in verticals like manufacturing, health and safety. "AI [artificial intelligence], predictive analytics, IoT and blockchain are all technologies that require strong data capture and use. Consequently, the way data is accessed will change to enable broader visibility and create cohesive ecosystems that support a convergence of data access and provides better operational and predictive capabilities," Vella said.
Government shutdown or not, plaintiffs' lawyers haven't stopped filing new crypto lawsuits. This week we look at three new complaints, one involving lost crypto and a demand for a fork (the software kind), another that says that pre-sold mining hardware contracts were actually securities, and last but not least artificial intelligence on the blockchain (but not so much, it turns out). Disclaimer: These summaries are provided for educational purposes only by Nelson Rosario [twitter: @nelsonmrosario] and Stephen Palley [twitter: @stephendpalley]. They are not legal advice. These are our opinions only, aren't authorized by any past, present or future client or employer.
International Data Corporation (IDC) has published a framework designed to guide business and IT decision makers faced with planning and investment decisions related to artificial intelligence (AI) for automation. The framework defines the expected levels of human-machine interaction and the hierarchy of automation scope, which can then serve as a basis for assessing data, algorithm, IT, staffing requirements, and potential risks at the intersection of AI capabilities and use cases. IDC has published a framework designed to guide planning and investment decisions related to artificial intelligence (AI) for automation. "IDC's AI-based automation evolution framework was developed based on global market research that highlighted two lessons," said Dan Vesset, group vice president, Analytics and Information Management Research at IDC. "First is the need to understand the components of the evolving relationship between humans and machines. Second is to understand the scope of AI-based automation. Once these two dimensions are brought into focus, the planning and investment decisions associated with AI-based automation will be much clearer."
"In 2019, blockchain technology will continue advancing innovative applications across all industries to distribute and secure transactions of almost any kind," says Red Hat chief technologist Ian Hood. "Increasing amounts of our business and personal lives will be transacted electronically over public networks and clouds. We all want to be comfortable that our personal data (financial, health, and legal) records are kept safe and to ensure that any of these transactions may not be modified in flight. With that in mind, we have seen that no application trusts any network. Determined attackers can compromise any perimeter. End-end encryption mechanisms will evolve to secure delivery across networks with blockchain technology as a key element across multiple industries."
The first industrial revolution began in the 18th century with water and steam power, the second with electricity, and the beginning of the third with the internet, both happened in the 20th century. The past few decades we have been living in the third industrial revolution in technological development. You might be asking, when will the fourth industrial revolution begin? The answer is it already has. The World Economic Forum (WEF) concludes we have likely already entered the transition phase into a new era of economy, politics, and society.