The blockchain cannot be described just as a revolution. It is a tsunami-like phenomenon, slowly advancing and gradually enveloping everything along its way by the force of its progression. Plainly, it is the second significant overlay on top of the Internet, just as the Web was that first layer back in 1990. That new layer is mostly about trust, so we could call it the trust layer. Blockchains are enormous catalysts for change that affect governance, ways of life, traditional corporate models, society and global institutions. Blockchain infiltration will be met with resistance, because it is an extreme change. Blockchains defy old ideas that have been locked in our minds for decades, if not centuries. Blockchains will challenge governance and centrally controlled ways of enforcing transactions.
AWS executives have come to view the mixed legacy environment as one of the barriers to cloud adoption. Even when the IT staff wants to move to the cloud, it is expensive and time-consuming to unravel the legacy application code in order to figure out how many pieces are involved and which data sources are necessary to migrate. AWS Application Discovery Service can not only map application dependencies, it can also draw up a performance profile that indicates what resources they will need. With AWS Application Discovery Service, a customer has to install a lightweight agent on an application host, where it maps the running apps and the identity of the operating system on which they depend. The service currently will work with Ubuntu 14, Red Hat 6-7, CentOS 6-7, and Windows Server 2008 R2, Windows Server 2012, and Windows Server 2012 R2.
The future workforce is going to require more than the ability to code -- we also need people who are able to craft the next round of transformational products and services. For example, Uber’s success stems from effective use of technologies aimed at a product that is the poster child for disruption. It connected underutilized resources (drivers and cars) with users who were impatient with a locked down and highly regulated market. The Uber stack is essential, but the innovation that drives it is less the code base and more the product. When we hear people suggesting things like, “Uber for dry cleaners,” we understand that they’re suggesting a direct and flexible relationship between customer and server; they are not talking about code.
In previous versions, if Petya failed to obtain administrator privileges, it stopped the infection routine. However, in such a case, the latest variant installs another ransomware program, dubbed Mischa, that begins to encrypt users' files directly, an operation that doesn't require special privileges. "There is nothing a ransomware developer hates more than leaving money on the table and this is exactly what was happening with Petya," said Lawrence Abrams, the founder of the tech support forum BleepingComputer.com, in a blog post. "Unlike Petya, the Mischa Ransomware is your standard garden variety ransomware that encrypts your files and then demands a ransom payment to get the decryption key."
“Apache Milagro (incubating) is an opportunity to fix what ails the internet and leverage the power of the open source community to fundamentally evolve the security underpinnings of the web for how it’s used today,” says Brian Spector, CEO of cryptography and cybersecurity firm MIRACL. “The code and distributed trust model we are committing to Apache Milagro (incubating) is built for blockchain applications, cloud computing services, mobile and containerized developer applications by eliminating the need for any central trust authority.” Milagro’s M-Pin protocol, and its existing open-source MIRACL implementation on which Milagro is built, is already in use by Experian, NTT, Ingram Micro, and Gov.UK and rolled out to perform at Internet scale for zero password multi-factor authentication and certificate-less HTTPS / secure channel.
In order for CIOs to build trust for transformation, they need to get the basics under foot. This statement is non-negotiable. Fundamental functions like email, phone systems, file sharing need to work without incident. These solutions are becoming more complex, but not business differentiating for any given organization. Yet many IT organizations continue to insist on running these functions internally. Sadly, many of the reasons given for this approach no longer hold true. At the same time, mature cloud-based alternatives exist that provide greater stability, function and agility. Not only does running commodity functions create a distraction for the organization from business-differentiating functions, it also creates an incredible amount of risk to basic business functionality. Unfortunately, failures to get the basics right will continue to plague the CIO and rest of the IT organization by extension.
It seems to me that the next-generation endpoint security market represents a disconnect between supply and demand. For example, ESG found that about 75 percent to 80 percent of enterprises were purchasing new tools for advanced threat prevention, while the remaining 20 percent to 25 percent of the market opted for advanced endpoint detection and response tools (EDR). This raises an obvious question: Is this purchasing behavior a function of an immature market that will consolidate over time? If so, it would be safe to assume that future innovation will lead to next-generation endpoint security product suites that span across advanced prevention, endpoint security controls, and advanced detection and response. This aggregation is already happening, as several established vendors and startups alike offer one-stop-shop endpoint security products.
From a business perspective, companies wouldn’t simply “buy” an AI solution. Rather, they would likely leverage one or more of the subfields of AI and buy software packages like R, Python, SAS, and MATLAB for statistical analysis. But new technology is pushing beyond traditional statistics, and machines are acting more intelligently than ever — they’re not just doing the analysis, machines are now finding patterns in data and figuring out how systems “work”… often without any human intervention. Let me stop here for a quick, yet important, PSA — neither artificial intelligence nor machines will replace all of our jobs. This is perhaps the biggest misconception about AI. Everything under the AI umbrella — including machine intelligence and machine learning — is data-driven, but requires human expertise to apply answers and discoveries to solve problems.
Once in the stomach, the robot doesn't have to work its way out of the capsule it was swallowed in. The capsule itself is designed to dissolve, automatically freeing the robot. The robot, rectangular in shape, is designed with accordion-like folds with a magnet on one of the folds that responds to magnetic fields outside the body. Using that magnet, doctors could manipulate the motion of the robot, moving it to where it needs to go. So what is this robot made of? It's built of the same dried pig intestine that is used in sausage casings, according to MIT. "We spent a lot of time at Asian markets and the Chinatown market looking for materials," said Shuguang Li, a postdoc student at MIT working on the project, in a statement.
There is a lot to be said for design. Good design goes unnoticed, bad design is criticized, and great design receives awards—most often from other designers. Compromise is inevitable, it is not possible to be everything to everyone. In the past, this used to be mitigated by usability testing and focus groups, before the final product was completed and published. This was in a time when people bought software in a physical store. Those days are over—and so too, apparently, are the days of design being "complete." Seemingly everything exists in a state of permanent beta, leaving end users subject to the whims of experimenting developers.
Quote for the day:
"To be successful, you have to have your heart in your business, and your business in your heart." --Thomas Watson