Want to Follow Elon Musk’s Roadster Through Space? There’s a Website for That.

Mars and Beyond

It’s been barely two weeks since SpaceX successfully launched the first Falcon Heavy into orbit, and many are curious as to where it and its unconventional passenger are right now. Instead of sending something boring as the Heavy’s first payload, SpaceX CEO and founder Elon Musk launched his own Tesla Roadster. On board is a mannequin affectionately called “Starman.”

Starman, who is dressed in a SpaceX suit, was supposedly en route towards the orbit of Mars and then towards the asteroid belt, to the tune of David Bowie’s music. In any case, Musk has said that Starman’s trajectory after launch had gone a bit off from its intended path.

It turns out, it might not have veered off that far, at least according to NASA’s Jet Propulsion Laboratory, which released information as to the Roadster’s whereabouts. Now, you can keep track of the Roadster and Starman using NASA’s data, which engineer Ben Pearson has wonderfully put into a website called Whereisroadster.com.

A Lonely Starman

Pearson was so fascinated by the Falcon Heavy launch that he made his own calculations for Starman’s trajectory, partially because he’s always been a fan of the SpaceX CEO. “I like that he’s willing to take risks and do cool stuff that people just keep saying it’s not possible and he figures out a way to make it possible,” Pearson told The Verge

However, Pearson noticed his results were different from what Musk announced. This made Pearson unease, but NASA’s data ended up showing that he was right.

Image credit: Whereisroadster.com
Where Starman as of Feb. 18. Image credit: Whereisroadster.com

“I was just relieved to know that I wasn’t doing anything critically wrong,” Pearson said in his interview with The Verge. “Elon Musk is a visionary man, incredibly far forward, but there’s a reality distortion field when it comes to him.”

In case you’re wondering, Pearson’s website shows that Starman is now 3,609,979 km (2,243,136 miles) from Earth, moving away from Earth at a speed of 10,844 km/h (6,738 mph), as of writing. It’ll continue to move in orbit around the Sun, making a close pass to the Earth on 2091, said Pearson. That is, of course, assuming that Starman’s Roadster survives in space for that long.

At any rate, at least we know where it is, which is more than what we can say for the Falcon Heavy’s Center Core. For now, SpaceX is barreling ahead with their other projects, including their latest Falcon 9 mission that will launch two of their first internet satellites into space.

The post Want to Follow Elon Musk’s Roadster Through Space? There’s a Website for That. appeared first on Futurism.

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Qualcomm may follow up its 7nm modem with a 7nm chipset: the Snapdragon 855

Qualcomm unveiled its first 7nm chips yesterday. But there’s more to the story – Qualcomm contractors may be gearing up to build the Snapdragon 855 on a 7nm process as well. Qualcomm won’t say it, but their contractors do. Snapdragon 855 (SDM855) is the first 7nm SoC. (probably the one the X24 modem ends up in) pic.twitter.com/Ot1J34fQoG— Roland Quandt (@rquandt) February 15, 2018 The upcoming 845 chip is being built on a 10nm Low Power Plus process, an incremental upgrade over the 10nm Low Power Early process used in the 835. Samsung (which is fabbing the chips) claims 10% higher…

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Brains on a battery: Low-power neural net developed, phones could follow

Low-power neural network developed

Researchers at MIT have paved the way to low-power neural networks that can run on devices such as smartphones and household appliances. Andrew Hobbs explains why this could be so important for connected applications and businesses.

Many scientific breakthroughs are built on concepts found in nature – so-called bio-inspiration – such as the use of synthetic muscle in soft-robotics.

Neural networks are one example of this. They depart from standard approaches to computing by mimicking the human brain. Usually, a large network of neurons is developed, without task-specific programming. This can learn from labelled training data, and apply those lessons to future data sets, gradually improving in performance.

For example, a neural network may be fed a set of images labelled ‘cats’ and from that be able to identify cats in other images, without being told what the defining traits of a cat might be.

But there’s a problem. The neurons are linked to one another, much like synapses in our own brains. These nodes and connections typically have a weight associated with them that adjusts as the network learns, affecting the strength of the signal output and, by extension, the final sum.

As a result, constantly transmitting a signal and passing data across this huge network of nodes requires large amounts of energy, making neural nets unsuited to battery-powered devices, such as smartphones.

As a result, neural network applications such as speech- and face-recognition programs have long relied on external servers to process the data that has been relayed to them, which is itself an energy-intensive process. Even in humanoid robotics, the only route to satisfactory natural language processing has been via services such as IBM’s Watson in the cloud.

A new neural network

All that is set to change, however. Researchers at Massachusetts Institute of Technology (MITT) have developed a chip that increases the speed of neural network computations by three to seven times, while cutting power consumption by up to 95 percent.

This opens up the potential for smart home and mobile devices to host neural networks natively.

“The general processor model is that there is a memory in some part of the chip, and there is a processor in another part of the chip, and you move the data back and forth between them when you do these computations,” MIT News reports, in an interview with Avishek Biswas, MIT graduate student in electrical engineering and computer science, who led the chip’s development.

Traditionally, neural networks consist of layers of nodes that pass data upwards, one to the next. Each node will multiply the data it receives by the weight of the relevant connection. The outcome of this process is known as a dot product.

“Since these machine-learning algorithms need so many computations, this transferring back and forth of data is the dominant portion of the energy consumption,” said MIT Biswas.

“But the computation these algorithms do can be simplified to one specific operation, the dot product. Our approach was, can we implement this dot-product functionality inside the memory, so that you don’t need to transfer this data back and forth?”

A mind for maths

This process will sometimes occur across millions of nodes. Given that each node weight is stored in memory, this amounts to enormous quantities of data to transfer.

In a human brain, synapses connect whole bundles of neurons, rather than individual nodes. The electrochemical signals that pass across these synapses are modulated to alter the information transmitted.

The MIT chip mimics this process more closely by calculating dot products for 16 nodes at a time. These combined voltages are then converted to a digital signal and stored for further processing, drastically reducing the number of data calls on the memory.

While many networks have numerous possible weights, this new system operates with just two: 1 and -1. This binary system act as a switch within the memory itself, simply closing or opening a circuit. While this seemingly reduces the accuracy of the network, the reality is just a two to three percent loss – perfectly acceptable for many workloads.

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At a time when edge computing is gaining traction, the ability to bring neural network computation out of the cloud and into everyday devices is an exciting prospect.

We’re still uncovering the vast potential of neural networks, but they’re undoubtedly relevant to mobile devices. We’ve recently seen their ability to predict health risks in fitness trackers, such as Fitbit and Apple Watch.

By allowing this kind of work to take place on mobile devices and wearables – as well as other tasks, such as image classification and language processing – there is huge scope to reduce energy usage.

MIT’s findings also open the door to more complex networks in the future, without having to worry so much about spiralling computational and energy costs.

However, the far-reaching power of abstraction inherent in neural networks comes at the cost of transparency. Their methods may be opaque – so called black box solutions – and we expose ourselves to both the prejudices and the restrictions that may come with limited machine learning models. Not to mention any training data that replicates human bias.

Of course, the same problems, lack of transparency, and bias be found in people too, and we audit companies without having to understand how any individual’s synapses are firing.

But the lesson here is that, when the outcome has significant implications, neural networks should be used alongside more transparent models, where methods can be held to account. Just as critical human decision-making processes must adhere to rules and regulations.

The post Brains on a battery: Low-power neural net developed, phones could follow appeared first on Internet of Business.

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Project Treble compatibility unofficially ported to Xiaomi Redmi Note 4, more devices likely to follow

One of Android’s biggest criticisms over the years has been how fragmented its version distribution is at any given time. At Google I/O in May last year, Google unveiled a plan to modularize the OS and make it easier to update. Project Treble, in short, separates out the base-level Android framework from the vendor implementation so OEMs are able to release OS updates without having to wait for chipmakers to update drivers.

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Project Treble compatibility unofficially ported to Xiaomi Redmi Note 4, more devices likely to follow was written by the awesome team at Android Police.

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Conflicting Reports Follow SpaceX’s Secret Zuma Mission

What Happened?

Conflicting reports are surfacing after SpaceX’s seemingly successful launch of a Falcon 9 rocket with a secret government payload, code-named Zuma. While it appeared that the launch went off without a hitch, the full launch and separation of the nose cone, which surrounded the secret satellite, was not streamed as it normally is, due to the classified nature of the mission.

Reports coming from the Wall Street Journal and Bloomberg are claiming that Zuma burned up upon reentry into the Earth’s atmosphere. These reports are partially based upon a briefing supposedly given to lawmakers and congressional staffers indicating that the satellite did not separate from the rocket as planned.

SpaceX did not report any problems with the launch; however, while the company usually announces a successful launch regardless of the classification of the payload, no confirmation was given by SpaceX or Northrup Grumman, the company that manufactured the secret satellite.

Futurism reached out to SpaceX and obtained the following statement from Gwynne Shotwell, President and COO of SpaceX, “For clarity: after review of all data to date, Falcon 9 did everything correctly on Sunday night. If we or others find otherwise based on further review, we will report it immediately. Information published that is contrary to this statement is categorically false. Due to the classified nature of the payload, no further comment is possible.”

Sticking the Landing

To confuse matters further, the Falcon 9’s first stage was able to successfully land back on Earth, indicating that the rocket was still fully operational.

Even more so, the US Strategic Command added an entry to its Space-Track catalog of artificial objects orbiting the planet, indicating that the new satellite was able to make at least one orbit. That was before another confusing piece was added: their spokesman Navy Captain Brook DeWalt stated that Strategic Command had “nothing to add to the satellite catalog at this time.” This could either indicate that there is nothing to add in addition to the new satellite entry, or that the Zuma satellite is no longer in orbit.

The conflicting reports, coupled with the seemingly incongruous aftermath, are adding a rocket-load of mystery to an already mysterious launch. 

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Yet SpaceX seems confident that it played its part in the Zuma mission well, and the company does not foresee this mission disrupting its schedule. According to Shotwell, “Since the data reviewed so far indicates that no design, operational or other changes are needed, we do not anticipate any impact on the upcoming launch schedule.”

She continued: “Falcon Heavy has been rolled out to launchpad LC-39A for a static fire later this week, to be followed shortly thereafter by its maiden flight. We are also preparing for an F9 launch for SES and the Luxembourg Government from SLC-40 in three weeks.”

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