Tellex says robotics researchers are increasingly looking for more efficient ways of training robots to perform tasks such as manipulation. “We have powerful algorithms now—such as deep learning—that can learn from large data sets, but these algorithms require data,” she says. “Robot practice is a way to acquire the data that a robot needs for learning to robustly manipulate objects.” Tellex also notes that there are around 300 Baxter robots in various research labs around the world today. If each of those robots were to use both arms to examine new objects, she says, it would be possible for them to learn to grasp a million objects in 11 days.
Another very realistic threat that’s emerging recently is mobile botnet. Pierre-Marc Bureau, Security Intelligence Program Manager from ESET explains what we’re dealing with here: The word botnet is made up of two words: bot and net. Bot is short for robot, a name we sometimes give to a device that is infected by malicious software. Net comes from network, a group of systems that are linked together. A botnet is a network of infected devices, where the network is used by the malware to spread. One potential advance in security currently being developed as a response to the number of cyber attacks rising 100% between 2013 and 2014, is the creation of artificial intelligence (AI) platforms.
A set of tools and platforms which are ideal for Centralized Provisioning are usually terrible and completely unsuited for use within a Decentralized Analytics operating model. Critical capability essential to Embedded Analytics is very different from Governed Data Discovery. Yes there are some capabilities that cross operating models (e.g. metadata), and some that are far important than others. In general this is a truly sound way to determine where your investment in capability should be occurring – and where it is not. Along the way you will surely stumble across very clever professionals who have solved for their own operating model limitations in ways that will surprise you. And some just downright silliness; remember culture plays a real and present role in this exercise.
Costin presented the team's findings at the DefCamp security conference in Bucharest on Thursday. It was actually the second test performed on firmware images on a larger scale. Last year, some of the same researchers developed methods to automatically find backdoors and encryption issues in a large number of firmware packages. Some of the firmware versions in their latest dataset were not the latest ones, so not all of the discovered issues were zero-day vulnerabilities -- flaws that were previously unknown and are unpatched. However, their impact is still potentially large, because most users rarely update the firmware on their embedded devices. At DefCamp, attendees were also invited to try to hack four Internet-of-Things devices as part of the on-site IoT Village.
Know what you are good at and what you care about, and pursue that. So, you might be good at math, or programming, or data manipulation, or problem solving, or communications (data journalism), or whatever. You can do that flavor of data science within the context of any domain: scientific research, government, media communications, marketing, business, healthcare, finance, cybersecurity, law enforcement, manufacturing, transportation, or whatever. As a successful data scientist, your day can begin and end with you counting your blessings that you are living your dream by solving real-world problems with data. I saw a quote recently that summarizes this: "If you think your scarce data science skills could be better used elsewhere, be bold and make the move."
Two years later, Target has largely recovered from the breach in terms of both consumer trust and financial impact. But no matter how grand its remediation efforts were, Target will be forever associated with the data breach and its lasting repercussions. "Target remains the most significant breach in history because it was the fist time the CEO of a major corporation got fired because of a data breach," said John Kindervag, vice president and principal analyst on risk for research firm Forrester. "You can't underestimate that in terms of getting people's attention. People started taking credit card security seriously -- before that, it was just a pain-in-the-neck compliance issue."
I’ve spent most of the last couple of years worrying about the GEMM function because it’s the heart of deep learning calculations. The trouble is, I’m not very good at matrix math! I struggled through the courses I took in high school and college, barely getting a passing grade, confident that I’d never need anything so esoteric ever again. Right out of college I started working on 3D graphics engines where matrices were everywhere, and they’ve been an essential tool in my work ever since. I managed to develop decent intuitions for 3D transformations and their 4×4 matrix representations, but not having a solid grounding in the theory left me very prone to mistakes when I moved on to more general calculations.
It could manage mass transit for optimal efficiency based on real-time conditions. It could monitor environmental conditions and mitigate potential hotspots proactively, predict the need for government services and make sure those services are delivered efficiently, spot opportunities to streamline the supply chain and put them into effect automatically. Nanotechnology in your clothing could send environmental data to your smart phone, or charge it from electricity generated as you walk. But why carry a phone when any glass surface, from your bathroom mirror to your kitchen window, could become an interactive interface for checking your calendar, answering email, watching videos, and anything else we do today on our phones and tablets?
Rightly or wrongly, the role of Project Manager remained in place in some companies, the role was re-introduced by some others, particularly larger companies working with bigger bodies of work - programmes involving many ‘agile’ feature teams for example. Companies forgot to update the Project Management toolkit though and in lots of cases we’ve seen companies also forgot to update the people, by which I mean train, educate, inform them about the key principles of agility, how to support it and how to take advantage of it. This resulted in many Project Managers applying traditional thinking and tools into agile projects. This included things like tightly managing scope and trying to fix it down early on; managing project progress and success based only on scope and time; requesting very precise estimates; measuring just velocity or worse, effort.
Chances are the offline office suite will have been faster than the online one. In some of my tests, working offline is three to five times faster. That's mainly due to the overhead of running code in a browser. Then there's the issue of internet connections, which are rarely perfect. They should be, I know. This is 2015, after all. But we don't even have perfect video-conferencing yet, as highlighted by this humorous article (NSFW). A lost connection can be infuriating when you're halfway through updating a document using a cloud-based application. If you're outside a 20-mile radius from Silicon Valley, this will be a factor. Microsoft has the right idea here. Its office suite lets you work online if necessary, but the offline software remains the primary productivity tool. So you can work in a fast, internet-independent office suite for most of the time, only using the online version when you need to.
Quote for the day:
"Don't look for ideas to confirm your thinking, rather look for trends that will disrupt your thinking." -- Rich Simmonds