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Why Cell Phones Make Speakers Go "Blip Blip Blip Buzz"

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When I first got a cell phone (an early Sidekick), a new noise entered my life. When I put on my big crazy headphones while the phone was in my shirt pocket, I'd hear a very distinctive "blip ba da blip ba da blip ba da buzzzzzzz" noise right before my phone rang, so loud that I'd have to wrench the headphones from my poor ears -- which was handy, because then I'd hear the phone ringing. It took me a long time to figure out that this noise was coming from the phone, because I'm kind of slow. I also heard it when the phone was near mostly any speakers (even my TV set), including when I received text messages or used other data features on the phone. I recently saw a discussion of these noises on a fellow _flosser's blog post. So what causes this noise?

Basically, it's the cell phone talking to the tower, and nearby speakers picking up that radio transmission. There are several Metafilter articles on the subject, which make for good background reading. The best technical explanation I've seen of the phenonemon I've seen is on this WiFi-Forum post:

The type of interference can occur if the following things happen
1) a pulsing radio transmitter,
2) with relatively strong power,
3) in very close proximity,
4) to a non-linear circuit element.

The non-linear circuit element is usually some sort of solid state
device such as a transistor or diode. If the non-linear element is
subjected to a strong pulsing radio signal, it will act as a rectifier
and "detect" the pulsating waveform, i.e., convert the pulsations from
a radio frequency to an audio frequency (if the pulsation rate is in
the pass-band of audio frequencies.) For example, a hearing aid
consists of a microphone, an audio amplifier and a small speaker. If
a strong pulsating radio signal impinges upon the first transistor
amplifier stage, the transistor will be driven into its non-linear
range and detect the pulsations. If the pulsation rate is in the
audio frequency range, the rest of the hearing aid amplifier will
amplify this and deliver it to the speaker, to the great annoyance of
the hearing aid wearer.

This annoyance is endemic to certain digital cellular technologies (including ones used in music devices like the iPhone, eek). The only ways I've found to mitigate the sound are: move the phone and the speakers father apart (this only seems to reduce the noise a bit...), turn off the cellular portion of the phone (the iPhone, for example, has an "airplane mode" that makes it practical to play music in the car -- without this turned on, the car sounds like it's being ripped apart by buzz-saws), or introduce electromagnetic shielding (good luck building your Faraday cage).

If you've got tips on how to reduce this noise, or a story of how annoying it is, please share in the comments.

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Google's AI Can Make Its Own AI Now
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Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]

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Courtesy Umbrellium
These LED Crosswalks Adapt to Whoever Is Crossing
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Courtesy Umbrellium

Crosswalks are an often-neglected part of urban design; they’re usually just white stripes on dark asphalt. But recently, they’re getting more exciting—and safer—makeovers. In the Netherlands, there is a glow-in-the-dark crosswalk. In western India, there is a 3D crosswalk. And now, in London, there’s an interactive LED crosswalk that changes its configuration based on the situation, as Fast Company reports.

Created by the London-based design studio Umbrellium, the Starling Crossing (short for the much more tongue-twisting STigmergic Adaptive Responsive LearnING Crossing) changes its layout, size, configuration, and other design factors based on who’s waiting to cross and where they’re going.

“The Starling Crossing is a pedestrian crossing, built on today’s technology, that puts people first, enabling them to cross safely the way they want to cross, rather than one that tells them they can only cross in one place or a fixed way,” the company writes. That means that the system—which relies on cameras and artificial intelligence to monitor both pedestrian and vehicle traffic—adapts based on road conditions and where it thinks a pedestrian is going to go.

Starling Crossing - overview from Umbrellium on Vimeo.

If a bike is coming down the street, for example, it will project a place for the cyclist to wait for the light in the crosswalk. If the person is veering left like they’re going to cross diagonally, it will move the light-up crosswalk that way. During rush hour, when there are more pedestrians trying to get across the street, it will widen to accommodate them. It can also detect wet or dark conditions, making the crosswalk path wider to give pedestrians more of a buffer zone. Though the neural network can calculate people’s trajectories and velocity, it can also trigger a pattern of warning lights to alert people that they’re about to walk right into an oncoming bike or other unexpected hazard.

All this is to say that the system adapts to the reality of the road and traffic patterns, rather than forcing pedestrians to stay within the confines of a crosswalk system that was designed for car traffic.

The prototype is currently installed on a TV studio set in London, not a real road, and it still has plenty of safety testing to go through before it will appear on a road near you. But hopefully this is the kind of road infrastructure we’ll soon be able to see out in the real world.

[h/t Fast Company]


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