“The perfect storm is brewing that will pummel our nation’s public and private critical infrastructures with wave upon wave of devastating cyber attacks,” the report notes. “The Mirai malware offers malicious cyber actors an asymmetric quantum leap in capability; not because of sophistication or any innovative DDoS code, rather it offers a powerful development platform that can be optimized and customized according to the desired outcome of a layered attack by an unsophisticated adversary.” Script kiddies and cyber criminal gangs are already drastically expanding their control over vulnerable Internet of Things (IoT) devices, which can be contracted in DDoS-for-Hire services by a virtually unlimited number of actors for use in an infinite variation of layered attack methods, the study says.
Beside big data why are we interested in autonomous driving? Well $500 billion could be saved in traffic accidents and the cost to society. And $507 billion could be saved in productivity gains. Think about if you could get that 90 mins back each day? Better traffic patterns and logistics lead to big savings. The overall auto model is changing. We don’t just want driving anymore, we want fleet, no need to own the car. And then there’s the possibilities for the media and the content that can be delivered into the vehicle. But with a 10 x increase in data from a vehicle by 2025, how do we manage that data, what can we do with it? Something has to change. ... We can speed up the innovation in automotive space, and that’s good for everybody. An autonomous vehicle is much safer than a speeding young teen driver, or an elderly person with slow reflexes. 5G will be crucial to get the speed of data up and back. A data centers to use deep learning to constantly update fleets.
We’ve entered the golden age of predictive discoveries. A frenzy of number crunching churns out a bonanza of colorful, valuable, and sometimes surprising insights Predictive analytics' aim isn’t limited to assessing human hunches by testing relationships that seem to make sense. It goes further, exploring a boundless playing field of possible truths beyond the realms of intuition. And so it drops onto your desk connections that seem to defy logic. As strange, mystifying, or unexpected as they may seem, these discoveries help predict. Welcome to the Ripley’s Believe It or Not! of data science—the Freakonomics of big data. Below are nine colorful discoveries, each pertaining to a single predictor variable—from the likes of Walmart, Uber, Harvard, Shell, Microsoft, and Wikipedia.
Nokia has already struck up a partnership with the University of Helsinki and the Helsinki University Hospital to develop remote monitoring products for neurology outpatients, saying the deal reflects "the company's intent to enter the regulated healthcare space". Is the company intending to focus more on the enterprise healthcare vertical as well as the consumer market? Nokia's digital health business aims to "bridge consumer device experience into healthcare patient solutions", Hutchings said. "One of the shared visions between Nokia and Withings is that there is no definite split or frontier between the consumer world and healthcare." ... "We'll see more and more from this common project [of Nokia and Withings] that involve what look like consumer products, but which really integrate and embed into healthcare and remote patient monitoring environments. We'll be seeing more and more of these pilots, and in the future, large-scale deployments of such solutions."
Today, after sustained stakeholder engagement, we are proud to publish a whitepaper, A Framework for FinTech, that takes our work one step further to provide that perspective. This whitepaper expresses the forward-leaning posture of this Administration to innovation and entrepreneurship, generally, and fintech in particular. This document sets forth Administration policy objectives that reflect widely-shared values and practical expectations for the financial services sector and the U.S. government entities that interact with the sector. It then provides ten overarching principles that constitute a framework policymakers and regulators can use to think about, engage with, and assess the fintech ecosystem in order to meet these policy objectives.
One of the most common misconceptions about data visualization is that you need to create amazing works of interactive art, like the cool map from Metrocosm here. Data visualization, massive graphic design budgets, and an in-depth knowledge of coding do not necessarily go hand-in-hand. According to most data experts, data visualization can be any map, chart, graph, etc. that you can make into a simple JPEG image, a video, or even a 3D model like the one above. The only criteria is that the visualization communicates data. It’s also important to point out that data visualizations are usually only visual representations of one data set; a pie chart to show different portions of a specific group, or a line chart showing growth of social media followers. An infographic, on the other hand, is a collection of multiple data sets designed to depict an overall trend, topic, or idea.
AI typically works in tandem with the Internet of Things (IOT) which includes devices like wearables and connected home gadgets. Simple put, IoT collects the information but AI is the engine that will power analytics and decision-making from that information. IoT connects disparate devices such as wearables and can scale to connect a nearly unlimited number of devices, continuously streaming data. AI processes, makes inferences about this data and ultimately enables recommendations in real-time. Let’s make some examples from the insurance industry A couple of years ago, when I was at Humana around 2012, one of the projects we worked on was understanding seniors (65+) living in their homes to better reduce the incidence of falls and predict the likely use of emergency services in real-time so we can act beforehand, improve their health status and save costs.
Generally, embracing reality involves entrepreneurs who experiment with options to confront disorder. They are always exploring and seeking opportunities to enable them to thrive; when they encounter disorder and sufficiently and reasonably struggle (that is, experience sufficient and reasonable degrees of stress), they consider their options and experiment, making small and reversible errors that cause acute stress, distributed over time, with ample recovery time, to enable them to learn and grow. ... Antifragility is beyond agility. Agility and antifragility are distinct paradigms, each with a unique mindset, worldview, values, principles, practices, and techniques. The essence of antifragility is a delicate dance --- at the antifragility edge --- between embracing reality and ensuring aliveness, where disorder or stress is at the intersection.
The current model of insurance is B2B2C. Insurance companies sell through the agencies. Some life insurers sell through the bancassurance model. So it is a B2B2C model. Now with digital disruption, they will have to deal directly with the customers. This means they will need to be more customer-centric. Digitization will shake this model and make it D2C (Direct to Consumer). This is very different from other industries that are digitalizing because they have only one dimension to deal with. They only have to interact more digitally with their customers. ... So as an industry we need to get better in explaining our products. In principle, insurance is a very simple product. We need to explain that our product is relevant and reliable and we need to be transparent about it. If people can buy shoes online, why wouldn’t they buy insurance online?
Two things change: first, filling the Solution Backlog — while still the responsibility of the Product Owner — becomes a consent-based collaboration between Product Owner and Enterprise Architecture (collaborating create&review roles, see below). And also: Enterprise Architecture can add items to the Architecture Backlog. Now, as in the Enterprise Chess approach for more classical projects, Enterprise Architecture’s role is checks & balances from the organisation-as-a-whole perspective. Hence, the Product Owner (in classic Prince2 terms, the Project Executive) is in charge of his project. But if there is no consent, then an escalation occurs to the level above the Product Owner, if need be up to the board of the organisation (after all: enterprise architecture’s checks & balances are from the perspective of the organisation-as-a-whole, for which the board is responsible).
Quote for the day:
"I believe it is important for people to create a healthy mental environment in which to accomplish daily tasks." -- Darren L. Johnson