Hackers Want Cambridge Dictionary To Change Their Definition

June 26, 2018 by Jenny List 83 Comments

Maybe it’s the silly season of high summer, or maybe a PR bunny at a cybersecurity company has simply hit the jackpot with a story syndicated by the Press Association, but the non-tech media has been earnestly talking about a call upon the Cambridge Dictionary to remove the word “illegal” from their definition of “Hacker”. The weighty tome from the famous British university lists the word as either “a person who is skilled in the use of computer systems, often one who illegally obtains access to private computer systems:” in its learners dictionary, or as “someone who illegally uses a computer to access information stored on another computer system or to spread a computer virus” in its academic dictionary. The cybersecurity company in question argues that hackers in fact do a lot of the work that improves cybersecurity and are thus all-round Good Eggs, and not those nasty computer crooks we hear so much about in the papers.

We’re right behind them on the point about illegality, because while there are those who adopt the hacker sobriquet that wear hats of all colours including black, for us being a hacker is about having the curiosity to tinker with anything presented to us, whatever it is. It’s a word that originated among railway modelers (Internet Archived version), hardly a community that’s known for its criminal tendencies!

Popular Usage Informs Definition

It is however futile to attempt to influence a dictionary in this way. There are two types of lexicography: Prescriptive and Descriptive. With prescriptive lexicography, the dictionary instructs what something must mean or how it should be spelled, while descriptive lexicography tells you how something is used in the real world based on extensive usage research. Thus venerable lexicographers such as Samuel Johnson or Noah Webster told you a particular way to use your English, while their modern equivalents lead you towards current usage with plenty of examples.

It’s something that can cause significant discontent among some dictionary users as we can see from our consternation over the word “hacker”. The administration team at all dictionaries will be familiar with the constant stream of letters of complaint from people outraged that their pet piece of language is not reflected in the volume they regard as an authority. But while modern lexicographers admit that they sometimes walk in an uneasy balance between the two approaches, they are at heart scientists with a rigorous approach to evidence-based research, and are very proud of their efforts.

Big Data Makes for Big Dictionaries

Lexicographic research comes from huge corpora, databases of tens or hundreds of millions of words of written English, from which they can extract the subtlest of language trends to see where a word is going. These can be interesting and engrossing tools for anyone, not just linguists, so we’d urge you to have a go for yourself.

Sadly for us the corpus evidence shows the definition for “Hacker” has very firmly trended toward the tabloid newspaper meaning that associates cybercriminality. All we can do is subvert that trend by doing our best to own the word as we would prefer it to be used, re-appropriating it. At least the other weighty tome from a well-known British university has a secondary sense that we do agree with: “An enthusiastic and skilful computer programmer or user“.

Disclosure: Jenny List used to work in the dictionary business.

A Real Time Data Compression Technique

June 25, 2018 by Al Williams 41 Comments

With more and more embedded systems being connected, sending state information from one machine to another has become more common. However, sending large packets of data around on the network can be bad both for bandwidth consumption and for power usage. Sure, if you are talking between two PCs connected with a gigabit LAN and powered from the wall, just shoot that 100 Kbyte packet across the network 10 times a second. But if you want to be more efficient, you may find this trick useful.

As a thought experiment, I’m going to posit a system that has a database of state information that has 1,000 items in it. It looks like an array of RECORDs:

typedef struct
{
  short topic;
  int data;
} RECORD;

It doesn’t really matter what the topics and the data are. It doesn’t really matter if your state information looks like this at all, really. This is just an example. Given that it is state information, we are going to make an important assumption, though. Most of the data doesn’t change frequently. What most and frequently mean could be debated, of course. But the idea is that if I’m sending data every half second or whatever, that a large amount isn’t going to change between one send and the next.

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Nvidia Transforms Standard Video Into Slow Motion Using AI

June 25, 2018 by Ben James 43 Comments

Nvidia is back at it again with another awesome demo of applied machine learning: artificially transforming standard video into slow motion – they’re so good at showing off what AI can do that anyone would think they were trying to sell hardware for it.

Though most modern phones and cameras have an option to record in slow motion, it often comes at the expense of resolution, and always at the expense of storage space. For really high frame rates you’ll need a specialist camera, and you often don’t know that you should be filming in slow motion until after an event has occurred. Wouldn’t it be nice if we could just convert standard video to slow motion after it was recorded?

That’s just what Nvidia has done, all nicely documented in a paper. At its heart, the algorithm must take two frames, and artificially create one or more frames in between. This is not a manual algorithm that interpolates frames, this is a fully fledged deep-learning system. The Convolutional Neural Network (CNN) was trained on over a thousand videos – roughly 300k individual frames.

Since none of the parameters of the CNN are time-dependent, it’s possible to generate as many intermediate frames as required, something which sets this solution apart from previous approaches. In some of the shots in their demo video, 30fps video is converted to 240fps; this requires the creation of 7 additional frames for every pair of consecutive frames.

The video after the break is seriously impressive, though if you look carefully you can see the odd imperfection, like the hockey player’s skate or dancer’s arm. Deep learning is as much an art as a science, and if you understood all of the research paper then you’re doing pretty darn well. For the rest of us, get up to speed by wrapping your head around neural networks, and trying out the simplest Tensorflow example.

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A Cleverly Concealed Magnetic Loop Antenna

June 23, 2018 by Jenny List 39 Comments

We’re sure all radio amateurs must have encountered the problem faced by [Alexandre Grimberg PY1AHD] frequently enough that they nod their heads sagely. There you are, relaxing in the sun on the lounger next to the crystal-blue pool, and you fancy working a bit of DX. But the sheer horror of it all, a tower, rotator, and HF Yagi would ruin the aesthetic, so what can be done?

[Alexandre]’s solution is simple and elegant: conceal a circular magnetic loop antenna beneath the rim of a circular plastic poolside table. Construction is the usual copper pipe with a co-axial coupling loop and a large air-gapped variable capacitor, and tuning comes via a long plastic rod that emerges as a discreet knob on the opposite side of the table. It has a 10 MHz to 30 MHz bandwidth, and should provide a decent antenna for such a small space. We can’t help some concern about how easy to access that capacitor is, on these antennas there is induced a surprisingly large RF voltage across its vanes, and anyone unwary enough to sit at the table to enjoy a poolside drink might suffer a nasty RF burn to the knee. Perhaps we’d go for a remotely tuned model instead, for this reason.

[Alexandre] has many unusual loop projects under his belt, as well as producing commercial loops. Most interesting to us on his YouTube feed is this one with a capacitor formed from co-axial soft drink cans.

Thanks [Geekabit] for the tip.

Linux Fu: The Great Power Of Make

June 22, 2018 by Al Williams 76 Comments

Over the years, Linux (well, the operating system that is commonly known as Linux which is the Linux kernel and the GNU tools) has become much more complicated than its Unix roots. That’s inevitable, of course. However, it means old-timers get to slowly grow into new features while new people have to learn all in one gulp. A good example of this is how software is typically built on a Linux system. Fundamentally, most projects use make — a program that tries to be smart about running compiles. This was especially important when your 100 MHz CPU connected to a very slow disk drive would take a day to build a significant piece of software. On the face of it, make is pretty simple. But today, looking at a typical makefile will give you a headache, and many projects use an abstraction over make that further obscures things.

In this article, I want to show you how simple a makefile can be. If you can build a simple makefile, you’ll find they have more uses than you might think. I’m going to focus on C, but only because that’s sort of the least common denominator. A make file can build just about anything from a shell prompt.

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Federico Faggin: The Real Silicon Man

June 19, 2018 by Steven Dufresne 47 Comments

While doing research for our articles about inventing the integrated circuit, the calculator, and the microprocessor, one name kept popping which was new to me, Federico Faggin. Yet this was a name I should have known just as well as his famous contemporaries Kilby, Noyce, and Moore.

Faggin seems to have been at the heart of many of the early advances in microprocessors. He played a big part in the development of MOS processors during the transition from TTL to CMOS. He was co-creator of the first commercially available processor, the 4004, as well as the 8080. And he was a co-founder of Zilog, which brought out the much-loved Z80 CPU. From there he moved on to neural networking chips, image sensors, and is active today in the scientific study of consciousness. It’s time then that we had a closer look at a man who’s very core must surely be made of silicon.

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Lawn From Hell Saved By Mower From Heaven

June 19, 2018 by Kristina Panos 94 Comments

It’s that time of year again, at least in the northern hemisphere. Everything is alive and growing, especially that narrow-leafed non-commodity that so many of us farm without tangible reward. [sonofdodie] has a particularly hard row to hoe—his backyard is one big, 30° slope of knee-ruining agony. After 30 years of trudging up and down the hill, his body was telling him to find a better way. But no lawn service would touch it, so he waited for divine inspiration.

And lo, the answer came to [sonofdodie] in a trio of string trimmers. These Whirling Dervishes of grass grazing are mounted on a wheeled plywood base so that their strings overlap slightly for full coverage. Now he can sit in the shade and sip lemonade as he mows via rope and extension cord using a mower that cost about $100 to build.

These heavenly trimmers have been modified to use heavy nylon line, which means they can whip two weeks’ worth of rain-fueled growth with no problem. You can watch the mower shimmy down what looks like the world’s greatest Slip ‘n Slide hill after the break.

Yeah, this video is two years old, but somehow we missed it back then. Ideas this fresh that tackle age-old problems are evergreen, unlike these plots of grass we must maintain. There’s more than one way to skin this ecological cat, and we’ve seen everything from solar mowers to robotic mowers to mowers tied up to wind themselves around a stake like an enthusiastic dog.

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