There is more than enough evidence to support why AI cannot be left unsupervised This does not necessarily mean that AI should be shunned, but it should be handled with care, for others reasons that include massive cyber-attacks which could affect financial markets and healthcare industries, potentially resulting in loss of financial records and even death due to malfunctioning computer hardware connected to the internet.
We’re living in a time where everything from elevators to factory floors are becoming digitized and connected and businesses are using the Internet of Things (IoT) and cloud to turn their goldmine of data into insight that they can use to back better business decisions. But at the edge, those remote locations that I mentioned earlier, this data stays in the dark, untapped and unused.
insideHPC Media LLC conducted insideBIGDATA AI/Deep Learning audience survey to get readers thoughts about how they see AI, machine learning, and deep learning. When asked about what industries will see the most impact from AI, machine learning, and deep learning, respondents indicated—16% healthcare, 13% finance/insurance, 11% transportation, 11% IT, 10% energy, 10% manufacturing, 10% academic research, 9% retail, 7% government, and others.
Bblockchain technology is not limited to virtual currencies. Blockchain technology may prove to be a revolutionary way to speed up and verify many currently manual processes, as quickly as it takes to press a button on a keyboard. Many centralized processes can potentially be replaced with blockchain technology. One such area is the post-trade settlement process, where the new technology could enable the instant updating of ledgers in a synchronized and authenticated manner. This would create a real-time or near real-time clearing and settlement system that would bring it in line with the speed of trading.
Instead of an user id you get control via keys and signatures, signing transaction-addresses and with that you can prove it is yours. But with that you also have a new/different responsibility being in charge of your keys and related addresses. If you lose them, it is like losing a banknote, anyone can spend it no questions asked.
Access to information is a prime example. Data analysts don’t just focus on the 20% of the high-value, high-impact work; they are the only people doing the other 80% of analytics work that is routine and low-value, but also necessary. There’s a reason BI teams are often called report factories. All of this is about to change, fortunately. We’re starting to see the same technologies that have revolutionized the consumer space make their way into business.
Exchanging data will be primarily accommodated by a Blockchain broker that will ensure the systems are following the protocols of the new paradigm. It will be used for requesting data updates from providers and for broadcasting updates. It will be a challenge to create a new paradigm for application software development but no less challenging than rebuilding application frameworks over and over, rebuilding the same functionality in every system, or trying to integrate systems that were never designed to work together. Now is the time to seriously consider a new approach to application software.
Enterprises who adopt innovative business models enabled by advanced 4IR technologies are in a class by themselves. The very lifeblood that fuels the 4IR is a disruptive mindset enabled by accessible and cheap technology—not necessarily favourable business environments or high marks in competitiveness factors. As such, innovative 4IR enterprises seem to have the ability to outperform the national economies they function in. But with a strong business environment, this success could very well translate into national competitiveness.
Whenever we got into a discussion with a prospect, the topic that has led to an exhaustive discussion has been “customer intent/buying intent”. Often, they ask “How does your tool identify the accounts that can be targeted now and the ones to nurture?”
Machine Learning and Data Science is one of the hottest topics of all the disciplines these days. It has created a lot of interest among the people. Machine Learning has immense potential and we keep seeing a lot of jaw dropping accomplishments day by day. Here I’ll share my understanding of the field and what would it take to make a career in Machine Learning/Data Science.
Artificial Intelligence has made its way to every field possible, steamrolling the processes along its way. One such field is healthcare. They say healthcare is a field that is not very rules based and a successful doctor is the one who leverages his/her experience to deal with complex and unseen cases. However, there are many low hanging fruits that are already being plucked by AI. This trend is being fueled by increasing digitization in healthcare data and advances in new algorithms. In this piece, we intend to give you a sneak peek into how AI is leading to improved healthcare for humanity. Below are some key examples of research areas and applications.
The US House of Representatives has given the green light to the Blockchain technology, advocating that the new-era innovation be implemented as a “national policy for technology to promote consumers’ access to financial tools and online commerce to promote economic growth and consumer empowerment.”
If I had a penny for every time I’ve heard “data doesn’t lie”…
For those of us who have the ever exciting and growing task of working with Big Data to help solve some of organization’s biggest inefficiencies, questions, or problems, perpetuating bias is a way too easy-to-make mistake, and we should all be familiarized with it by now.
For everyone else, here’s what going on:
If you are new to the field, Big Data can be intimidating! With the basic concepts under your belt, let’s focus on some key terms to impress your date, your boss, your family, or whoever.
Work is not what it used to be. The very concept of work has evolved considerably over the centuries, as newer technologies have become integrated into how we function individually as well as a society.
People ask me frequently, “Please tell me, what is blockchain and how does it work?” I have been using various approaches and media answering this question, whiteboards, paper and even beer-coasters, and recently created a single page canvas combining all my scribbles and drawings to answer this question. This works very well, with great response and I like to share it including the story that goes with it. Maybe it is somewhat technical but most people follow the explanation quite well and really feel that they have learned something.
The Experfy insights provide cutting-edge perspectives on Big Data and Analytics. Experfy’s unique ability to focus on business problems enables them to provide insights that are highly relevant to each industry. With its certification for Big Data Analysis and Big Data Science, Experfy can make you a master in these fields.
Digital transformation is a comprehensive process affecting every aspect of your organization. Are CLOs ready to re-invent themselves to upskill their employees?
The blockchain is a collection of technologies, just like bricks used in a construction. You can choose different bricks to place them collectively in various forms to produce your desired construction results. Similar is the case with the blockchain technologies. Like the use cases of bricks are many, the blockchain application use cases are many.
Blockchain lately has created enormous technological excitements driving far-fetched developments in the world. It all started with the creation of Bitcoin and other cryptocurrencies, or digital currencies.
Few industries are as primed to be radically improved by Machine Learning as the Telecoms industry. About 1.5 trillion U.S. dollars is forecast to be spent globally on telecom services in 2018.
According to a new report by PwC, Artificial Intelligence will contribute as much as $15.7 trillion to the world economy by 2030. That's more than the current combined output of China and India.
Though you probably do not realize it, sophisticated algorithms are already dominating our everyday life, through traffic lights, train schedules, your Facebook newsfeed, and more. An area of algorithmic dominance that often goes unnoticed is in the stock market. These trading algorithms are reshaping the way trading is done on Wall Street. Investors are using algorithms designed for trading to bring greater efficiency to financial markets, and at the same time push us into uncharted financial territory.
By putting into practice the ideas you learn and read about, you can sharpen your technical skills, and develop a critical thinking mindset and creativity to succeed with algorithmic trading.