While companies commonly use these databases to store tempting troves of customer and financial data, they often do so with outdated and weak default security configurations. And while any type of database can be left open or unprotected, a string of breaches over the last few years have all centered around one type in particular: open-source “NoSQL” databases, particularly those using the popular MongoDB database program.
” A MacBook is a business-class laptop, and of course carries a higher price tag. However, Apple’s latest hardware release was underwhelming and overpriced. If you’re looking for a new laptop, you would do well to consider other brands. To that end, here’s a buyer’s guide to ThinkPads, currently the second most popular laptop I’ve seen with the dev/hacker/code cracker crowd.”
Double Helix is based on concept called structured diversity. It creates a number of functionally equivalent versions of a mission-critical system, but adjusts the binary code of some of these clones – the equivalent to changing their four-letter DNA code – so that properties needed for successful attacks are missing. When a cyberattack occurs, the behavior of the unprotected clones diverges from the protected ones. At this point, Double Helix will take action to recover from the attack by modifying the affected clones.
Artificial neural networks are famously based on biological ones. So not only do Lin and Tegmark’s ideas explain why deep learning machines work so well, they also explain why human brains can make sense of the universe. Evolution has somehow settled on a brain structure that is ideally suited to teasing apart the complexity of the universe.
This work opens the way for significant progress in artificial intelligence. Now that we finally understand why deep neural networks work so well, mathematicians can get to work exploring the specific mathematical properties that allow them to perform so well. “Strengthening the analytic understanding of deep learning may suggest ways of improving it,” say Lin and Tegmark.
Deep learning has taken giant strides in recent years. With this improved understanding, the rate of advancement is bound to accelerate.
“While suitable for kids eight and older, PocketBlock is by no means restricted to kids. Troutman said it’s also suitable for professional developers who want to deepen their understanding of the way cryptographic algorithms work, given that they’re often implementing them.”
“On Wednesday, researchers at the Joint Quantum Institute at the University of Maryland unveiled a first-of-its-kind fully programmable and reconfigurable quantum computer. The five-qubit machine, which is described in the journal Nature, represents a dramatic step toward general-purpose quantum computing—and, with it, an upending of what we can even consider to be computable.”
“[…] the future of computing seems to be about a set of platform and device-independent services. Specifically, voice-based interactions, driven by large installations of cloud-based servers running deep learning-based algorithms are what’s hot these days. This kind of computing model doesn’t necessarily need the kind of local horsepower that traditional computing devices have had. Indeed, these types of services can be accessed by the simplest of devices, with little more than an audio input, an audio output, and a wireless connection.”
What’s needed for AI’s wide adoption is an understanding of how to build interfaces that put the power of these systems in the hands of their human users. What’s needed is a new hybrid design discipline, one whose practitioners understand AI systems well enough to know what affordances they offer for interaction and understand humans well enough to know how they might use, misuse, and abuse these affordances.
“We have to keep as little [information] as possible so that even if the government or some other entity wanted access to it, we’d be able to say that we don’t have it,” said Gadea, founder and chief executive of Envoy. The 30-person company enables businesses to register visitors using iPads instead of handwritten visitor logs. The technology tracks who works at a firm, who visits the firm, and their contact information.
In Silicon Valley, there’s a new emphasis on putting up barriers to governmentrequests for data. The Apple-FBI case and its aftermath have tech firms racing to employ a variety of tools that would place customer information beyond the reach of a government-ordered search.
Agile is not the enemy, but what happened was some tech got easy, and management started treating software developers like labor, rather than say, creative geniuses.
There was a feeling that project management was “over” software developers, that developers were things that were “managed”, rather than creators. Before, it really felt like we were treated more like the lifeblood of a tech company – and somehow, tech companies became marketing companies that employed tech because, well, that is what you had to do.