Ethereum isn’t just a cryptocurrency to be traded; its real value lies in its purpose. Ethereum’s purpose is to allow the owner to use the distributed world computer that several thousand nodes are powering.Ethereum is basically a huge computer! However it’s an extremely slow one — about five to 100 times slower than regular computers today — and very expensive.
As enterprises and society at large struggle to wield the massive amounts of data flowing off of devices, infrastructure, workflows, and users, two profound, but distinct technological developments are shaping the narrative. Artificial intelligence (AI) and blockchain are both poised to transform enterprise data strategies, but in very different ways.
Initial Coin Offerings have become the state of the art crowd-funding /crowd-investing method for blockchain ventures. The are conducted entirely P2P on the blockchain. Funding through pre-selling coins/tokens to investors interested in supporting the project. As opposed to traditional crowdfunding where the investment is considered to be a donation or a pre buy of a product, ICOs give the supporters the possibility of a return of investment when selling their coin later at a possibly higher price. ICOs are similar to IPOs if the token represents a stake in the project.
Predictive analytics is widely accepted in marketing for customer acquisition, retention and cross-sell for good reason. Customers with more than one policy typically have a higher retention rate. Also, a policy often does not become profitable for 2-3 years due to sales acquisition costs. Predictive analytics help target the right customers and to predict those who may leave or churn.
AI will have a complex relationship with humans that will change over time: While certain jobs will become automated, AI is more often poised to augment human labor and decision-making. Longer-term, many applications will be designed to empower humans with non-human capabilities, memory, experiences, and knowledge. Many ethical, philosophical, cultural, societal, and business norms will be forced into re-assessment.
Much of the analytics employed in the insurance industry is focused on identifying and reducing fraud; estimating and managing risk and customer retention. Reports from the insurance industry consistently highlight that the quality of customer experience remains the biggest factor driving customers to remain loyal or switch to another insurance provider. Hence, the focus should be on how to improve the quality of the customer experience rather than reducing fraud.
Cryptocurrencies such as Bitcoin have increased the awareness of distributed ledgers with their use of a particular type of ledger — blockchain — to hold the details of coin accounts among millions of users. Cryptocurrencies have certainly had their own problems with their wallets and exchanges
Leveraging the use of big data, as an insight-generating engine, has driven the demand for data scientists at enterprise-level, across all industry verticals. Whether it is to refine the process of product development, help improve customer retention, or mine through the data to find new business opportunities—organizations are increasingly relying on the expertize of data scientists to sustain, grow, and outdo their competition. Consequently, as the demand for data scientists increase, the discipline presents an enticing career path for students and existing professionals. This includes those who are not data scientists but are obsessed with data, which has left them asking:
An ICO is similar to an IPO (initial public offering) in that it offers a certain amount of ownership in a company to the public. In an IPO, a share of stock represents fractional ownership of a corporation. In an ICO, a crypto coin represents a percentage of ownership in pretty much any business endeavor
With big data, the conversing data becomes loud and noisy. You don’t hear the voice; you hear the cacophony. This is where organizations struggle.And, amidst a struggle, you look up to the leaders to see how they are rising to the challenge. You observe, you learn, you implement and you adapt. This is the first article of my “Under the Spotlight” series, where we will look at how leading organizations are leveraging big data and analytics, filtering out white noise from the cacophony in the process—to closely follow and benefit from what data has to say.
AI advancement has rapidly accelerated during the last decade. Some people say AI will augment humans and maybe even make us immortal; other pessimistic individuals say AI will lead to conflict and may even automate our society out of jobs. Despite the differences in opinion, the fact is, only a few people can identify what AI really is. Today, we are surrounded by minute forms of AI, like the voice assistants that we all hold in our smart phones, without us knowing or perceiving the efficiency of the service. From Siri to self-driving cars, a lot of promise has already been shown by AI and the benefits it can bring to our economy, personal lives and society at large. The question now turns to how enterprises will benefit from AI.
Man vs. Machine: 10 years ago, I would never have guessed that I would be writing about this topic with such serious concern. Yet, some people are predicting that machine learning technology will produce a jobless future for certain professions, including actuaries.
“An initial coin offering (ICO) is a means of crowdfunding the release of a new cryptocurrency. Generally, tokens for the new cryptocurrency are sold to raise money for technical development before the cryptocurrency is released. Unlike an initial public offering (IPO), acquisition of the tokens does not grant ownership in the company developing the new cryptocurrency. And unlike an IPO, there is little or no government regulation of an ICO.
September 1st we had the pleasure of employing a new marketing intern at Experfy. We thought it would be a good idea to introduce him, since he will be partially responsible for the digital marketing at Experfy. This post provides a sneak peak into the next 4 months.
The future of AI and what it transpires into, lies in the hands of those controlling the characteristics that bind this innovation. We can now imagine and think of ideas which might have made you a laughing stock a few years ago. From a computer system playing chess with the masters to driverless cars, the possibilities associated with AI are many. Considering the high skill levels of machines with AI, the technology can be used in numerous fields to expand human capabilities, to optimize the use of resources, and to enhance productivity.
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?”