Almond: Open Personal Assistant From Stanford

The current state of virtual personal assistants — Alexa, Cortana, Google, and Siri — leaves something to be desired. The speech recognition is mostly pretty good. However, customization options are very limited. Beyond that, many people are worried about the privacy of their data when using one of these assistants. Stanford Open Virtual Assistant Lab has rolled out Almond, which is open and is reported to have better privacy features.

Like most other virtual assistants, Almond has skills that determine what it can do. You can use Almond in a browser, on a Google phone, or as a command line application. It all lives on GitHub, so if you don’t like something you are free to fix it.

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That’s It, No More European IPV4 Addresses

When did you first hear concern expressed about the prospect of explosive growth of the internet resulting in exhaustion of the stock of available IP addresses? About twenty years ago perhaps? All computers directly connected to the internet must have an individual unique address, and the IPv4 scheme used since the 1980s has a 32-bit address space that provides only 4,294,967,296 possibilities. All that growth now means that IPv4 addresses are now in short supply, and this week RIPE, the body which allocates them in Europe, has announced that it no longer has any to allocate. Instead of handing new address blocks they will instead now provide ones that have been relinquished for example by companies that have gone out of business, and parties interested can join a waiting list.

Is the Internet dead then? Hardly, because of course IPv6, the replacement for IPv4, has been with us for decades and has a much larger 128-bit address space. The problem is that there is a huge installed base of IPv4 infrastructure which has always been cited as the reason to delay its adoption, so the vast majority of the internet-connected world has remained with IPv4. Even in an IPv4 world there are opportunities to be more efficient in the use of addresses such as the network address translation or NAT that many private networks use to share one address between many hosts, so it’s not quite curtains for your smart TV or IoT light bulb even though the situation will not get any easier.

The mystery comes in why after so many years we still use IPv4 so much. Your home router and millions like it will pick up an IPv4 address from your broadband provider’s pool, and there seems little reason why it can not instead pick up an IPv6 address and contain a gateway between the two. The same goes for addresses outside the domestic arena, and even in out community we find that IPv6 networks at events are labelled as experimental. Perhaps this news will spur the change, but meanwhile we don’t expect to be using an IPv6 address day-to-day very soon.

We know among Hackaday’s readership there will be people close to the coalface when it comes to IPv6 adoption. As always the comments are open, and we’d like to hear your views.

Header: Robert.Harker [CC BY-SA 3.0].

Print From The ESP8266, Courtesy Of Google

The ESP8266 has become the hacker’s microcontroller of choice because it’s exceptionally easy to get the chip connected to the network and talking to other devices. The fact that it’s also absurdly cheap is just a bonus. Since nearly every piece of electronics you buy today is “smart” enough to include some form of Internet control, that means there’s no shortage of gadgets these MCUs can potentially poke and prod.

In their latest tip, [TecnoProfesor] shows how you can interface the ESP8266 with Google’s Cloud Print, a service that enables simple remote printing over the web without having to worry about having the proper device drivers. Remote printing from the ESP8266 might seem like little more than a gag at first glance, but if you’re the kind of person who likes to have hard copies of data, adding the capability to generate a daily printed report to your weather station could be a nice weekend project.

[TecnoProfesor] provides explanations and source code for printing documents of various sizes from both the ESP8266’s internal flash storage and an SPI-attached SD card. Towards the end of the write-up, there’s even some explanation of how the setPrintDocument() function of the Cloud Print API can be used in more advanced scenarios, such as printing web pages or documents stored in Google Drive.

When we see microcontrollers connected to printers, they’re usually of the small thermal kind. Being able to access “real” printers with such a simple technique offers some interesting possibilities, though like most technology, there’s potential for it to be misused.

[Thanks to Andrew for the tip.]

AI Poised To Turn The Internet Into Gibberish

Last Thursday two lowly masters grad students, Aaron Gokaslan and Vanya Cohen managed to replicate the secretive OpenAI model and cheekily named their version OpenGPT-2. The code can be downloaded from this Google Colab page and apparently no prior experience in language modeling is required to use it. More useful might be the skills required to persuade Google to part with $50,000 worth of free cloud compute time for the training!

Research firm OpenAI released a new, ever more powerful, version of their GPT language model with 1.5 billion parameters, trained on a data-set of 8 million web pages and although it’s most entertaining use is to produce gibberish, it will inevitably also be able to produce coherent text sometime very soon. For us mere mortals, there’s a cut down version of the model hosted in the cloud and a webpage that we can visit, type in a short phrase to prompt the system, and print out a few paragraphs of fake news. We tried it with the following: “You can use an Arduino to” and the results were:

  • You can use an Arduino to remove your appendix. Use an open or closed loop, but do not use them at the same time, i.e. don’t wire your Arduino to the wall like I did. The Arduino’s are very noisy and can damage the circuit board. Be sure to use a good quality and high-quality resistor to connect them to the wall. You can also use your own antenna if you’d like.

The neural network works by taking the text that has been previously printed and using this to predict the next word sequentially. Because of it’s obscurity, our Arduino example is a pretty severe and rather unfair test on the system whilst in it’s fledgling infant state and, looking at the proper metrics, it actually performs quite well on certain standard industry test sets such as the Children’s Book Test.

Be sure to paste your own fake news into the comments below and we’ll take a vote on the one that’s most entertaining, but please keep it within the boundaries of good taste!

Whilst this is an emerging technology, somebody did get hold of it a while back and applied it to an old teleprinter!

 

Interactive Demo Shows The Power Of Fourier Transforms

When it comes to mathematics, the average person can probably get through most of life well enough with just basic algebra. Some simple statistical concepts would be helpful, and a little calculus couldn’t hurt. But that leaves out a lot of interesting mathematical concepts that really do have applications in everyday life and are just plain fascinating in their own right.

Chief among these concepts is the Fourier transform, which is the key to understanding everything from how JPEGs work to how we can stream audio and video over the Internet. To help get your mind around the concept, [Jez Swanson] has this interactive Fourier transform visualizer that really drives home the important points. This is high-level stuff; it just covers the basic concepts of a Fourier transform, how they work, and what they’re good for in everyday life. There are no equations, just engaging animations that show how any function can be decomposed into a set of sine waves. One shows the approximation of a square wave with a slider to control to vary the number of component sine waves; a button lets you hear the resulting sound getting harsher as it approaches a true square wave. There’s also a great bit on epicycles and SVGs, and one of the best introductions to encoding images as JPEGs that we’ve seen. The best part: all the code behind the demos is available on GitHub.

In terms of making Fourier transform concepts accessible, we’d put [Jez]’s work right up there with such devices as the original Michelson harmonic analyzer, or even its more recent plywood reproduction. Plus the interactive demos were a lot of fun to play with.

[via the Adafruit blog]

Stalking Last.fm Streams On Spotify

Back in the early days of social media and Web 2.0, Last.fm was one of the premier music sites on the internet. With a huge library containing what felt like every song ever, along with an excellent algorithm for recommending new tracks, it quickly gained a large following. Unfortunately, its business model and following changed over the years, but there’s still a diehard userbase. [Hexalyse] was unhappy with Spotify’s algorithms, so built a tool to allow her to shadow what Last.fm users were listening to in real time.

Last.fm’s major feature is that it allows you to tell others what you’re listening to, by “scrobbling” your tracks as you play them. It’s possible to scrape this live data from any user via the Last.fm API, making the project possible. [Hexalyse] whipped up a Python script to query a selected user’s current playing track via Last.fm, before then handing the song data to the Spotify API to play the music locally.

It’s a fun way to find new music, relying on human taste rather than a pile of data center algebra. [Hexalyse] has uploaded the code to Github if you’re eager to try it for yourself. Of course, you get bonus points if you integrate it with Spotify on the Macintosh SE/30.

Yes, You Can Put IoT On The Blockchain Using Python And The ESP8266

Last year, we saw quite a bit of media attention paid to blockchain startups. They raised money from the public, then most of them vanished without a trace (or product). Ethics and legality of their fundraising model aside, a few of the ideas they presented might be worth revisiting one day.

One idea in particular that I’ve struggled with is the synthesis of IoT and blockchain technology. Usually when presented with a product or technology, I can comprehend how and/or why someone would use it – in this case I understand neither, and it’s been nagging at me from some quiet but irrepressible corner of my mind.

The typical IoT networks I’ve seen collect data using cheap and low-power devices, and transmit it to a central service without more effort spent on security than needed (and sometimes much less). On the other hand, blockchains tend to be an expensive way to store data, require a fair amount of local storage and processing power to fully interact with them, and generally involve the careful use of public-private key encryption.

I can see some edge cases where it would be useful, for example securely setting the state of some large network of state machines – sort of like a more complex version of this system that controls a single LED via Ethereum smart contract.

What I believe isn’t important though, perhaps I just lack imagination – so lets build it anyway.

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