Amazon now has a say in the development of a commonly used smart home standard, giving the company more power as it continues to push smart speakers, cameras, doorbells, and all other kinds of gadgets into its customers’ homes.

As of today, Amazon has a seat on the board of the Zigbee Alliance, which oversees implementation of the Zigbee wireless protocol. Zigbee isn’t nearly as popular as Bluetooth or Wi-Fi, but you can think of it a lot like them – it’s a wireless protocol for letting gadgets communicate. But unlike Bluetooth and Wi-Fi, Zigbee is particularly useful for low-power devices and can travel longer distances, making it ideal for simple smart gadgets like a light switch.

Amazon introduced a version of the Echo, called Echo Plus, with Zigbee support more than a year ago. That support allowed the speaker to directly connect to a new world of smart home gadgets, like light bulbs, power outlets, and tiny sensors that it otherwise couldn’t have reached. The home alarm system for Ring, which Amazon owns, also connects to Zigbee.

It’s a slow start, but Amazon’s ascension to Zigbee’s board suggests the company will want to make more use of the protocol in the future. Other companies on Zigbee’s board include: 1) Samsung-owned SmartThings, which makes a smart home hub; 2) Signify, the company behind the popular Philips Hue smart lights; and 3) Comcast, which uses Zigbee on its Xfinity Home security solution.

Getting onto Zigbee’s board isn’t exactly a feat for Amazon, but it is an obvious and deliberate decision. Getting on the board means becoming one of the Alliance’s highest-paying members – $75,000 per year – and it gives those companies an significant advantage: they’re able to “drive specification development, requirements, and test plans.” Or basically, define where Zigbee goes next.
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If Amazon is paying that money, it means the company wants a say in what future versions of Zigbee can do and how different Zigbee devices work together. It also shows Amazon taking an opinion on which smart home standard it’d like to see win out. Zigbee’s most direct competitor is an alternative called Z-Wave, which hardware makers have criticized for relying on proprietary chips from a single company. Amazon is likely among the many companies in the smart home industry that would rather avoid dealing with the pricey parts that could come along with that if Z-Wave were to grow in popularity.

Drivers will soon have an extra set of eyes on the road, courtesy of Google.

Google’s navigation app, Google Maps, is starting to roll out speed limit and speed trap features. 

With the speed limit feature, drivers using Google Maps will be shown the posted speed limit of the road they’re driving on in the lower left side of the app. Speed traps are designated with a small camera icon and shown on the visible area of the map. The Maps app provides an audio warning for drivers when they are approaching a speed trap.

Users have had the ability to report speed traps in Google Maps since late last year. However, until now, the app wasn’t yet making the reported speed traps visible for users in maps. 

Google Maps users have long wondered when such features were going to make their debut on the service. Crowdsource-powered navigation app, Waze, grew in popularity for providing this sort of detailed information on the road. Google acquired Waze back in 2013 for around $1 billion. 

Now, nearly five and a half years later, some of the Waze features are finally making their way to Google Maps.

Several companies demonstrated C-V2X (cellular vehicle-to-everything)communications technology developed by Qualcomm at CES 2019. But Ford may be the most aggressive in bringing C-V2X to market. The Detroit automaker will add it to every new car and truck sold in the United States by 2022, Don Butler, executive director for Ford connected vehicle platform and product, wrote in a blog post.

C-V2X is the latest incarnation of so-called vehicle-to-everything (V2X), a communications technology that allows cars to “talk” to each other and infrastructure. The claimed advantage of this technology is that it can warn a driver of things beyond his or her line of sight. If a car is stopped at an intersection with poor visibility, it could, for example, pick up signals from other V2X-equipped cars or sensors mounted on nearby buildings to tell the driver if it’s okay to go.

Vehicles could also communicate with stoplights, telling drivers when a light is about to change. Audi already offers this in the form of its Traffic Light Information system. The system gives a countdown when a light is about to turn green, but it only works in a handful of cities (Audi also offers a built-in toll transponder that relies on V2X tech). Aptiv has placed sensors on traffic lights in Las Vegas to guide its self-driving cars, even when they’re onboard cameras don’t have a direct line of sight to the light.

Ford could take things even further, Butler wrote. C-V2X could be integrated with driver aids, like those in Ford’s recently introduced Co-Pilot360 suite. Or it could be added to self-driving cars. Emergency vehicles could be equipped with C-V2X transmitters, allowing cars to detect their presence and move out of the way.

The difference between the C-V2X tech embraced by Ford and previous systems is that it’s based on 5G. All other V2X systems to-date have used a competing setup called Dedicated Short-Range Communications (DSRC). But that means Ford will have to rely on the smooth rollout of 5G. Even the deployment of DSRC-based V2X vehicles and infrastructure has been slow, and DSRC is based on a more familiar technology derived from Wi-Fi.

“A conducive regulatory environment must be in place for C-V2X to be deployed, which is why we are working just as much with industry and government organizations to create such a technology-neutral environment,” Butler wrote in his blog post. He also told Bloombergthat he hopes other automakers will adopt C-V2X alongside Ford. He added that C-V2X is a simpler solution because telecom companies are already spending billions on 5G cell towers and antennas, while DSRC would require a separate government investment.
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Despite the potential hurdles, Qualcomm expects C-V2X and other related technologies to become a significant part of its business. The company believes that, within five years, 75% of cars will have some form of connectivity. A critical mass of vehicles will be needed to realize the technology’s full benefit since cars that aren’t equipped with C-V2X or similar systems can’t communicate with each other. The more vehicles on the network, the more effective it is.

Google has won approval to bolster work on its Minority Report-style touchless technology, which enables electronics to be controlled by hand gestures.

The Federal Communications Commission has approved Google’s plans to use more powerful sensors for its Project Soli initiative, first unveiled in 2015. The radar-based technology is now poised to kick on to the next level after Google was given special permission to use higher frequencies for its tests.

When Google first showcased the tech in 2015, it came under the X Labs banner and was focused on smartwatches, with specific gestures replacing a physical tap on the touchscreen. For example, it was possible to rub two fingers together in the vicinity of the watch to cycle through menus or turn up the volume of media.

Now the company could expand the operation to enable the sci-fi like air gestures we’ve seen in films like Minority Report and the Iron Man franchise, on larger screens and devices. The waiver granted by the FCCcould also be highly beneficial to tech users with mobility, speech, and tactile impairments.

In a statement (via Reuters), the FCC said: “The ability to recognize users’ touchless hand gestures to control a device, such as a smartphone, could help people with mobility, speech, or tactile impairments, which in turn could lead to higher productivity and quality of life for many members of the American public.”
The regulator also said there’s little chance of Google’s Project interfering with other spectrum users and has approved the tech for use on aircraft.
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Google hasn’t commented on the news yet, but it’ll be interesting to see what the company has in mind for Project Soli moving forward. Hopefully, we’ll find out more in 2019.

 The only sure things in this life, according to Ben Franklin, are death and taxes. And a new startup called Visor has just raised $9 million in financing to make one of them as painless as possible.

Unlike Dr. Jack Kevorkian (remember “Doctor Death”), Visor won’t kill anyone, but it may ring the death knell for the high-end tax advisors that most Americans can’t even access to get help filing and paying their taxes.  It’s like having a personalized accountant for the cost of a high-end do-it-yourself tax-prep service.

The $9 million Visor raised came from the venture capital firm, Defy, with participation from Unusual Ventures, SVB Capital and existing investors like Obvious Ventures, Fika Ventures, and Boxgroup, who had put a previous $6.5 million into the company. 

The idea for the company had been percolating for co-founder and chief executive Gernot Zacke since he settled in the U.S. 

Growing up in Sweden, Zacke was exposed to a much different process for paying taxes. “The experience of filing taxes in Sweden is that you receive a message from the government that stated how much you made and how much you were withholding. That’s it,” said Zacke. “Taxes should be as easy as ordering a cab.”

That’s the service that Visor aims to provide.

“If you think about the market there are two ways to get your taxes done. There’s the DIY space, and then there are other online services, but it requires the taxpayer to fill out the forms, and it leaves the taxpayer with a little bit of anxiety,” said Zacke. “We’re delivering the CPA experience through the convenience of a web app and a mobile app.”

On average, Americans spend about 13 hours each year dealing with taxes, and the average American doesn’t have the benefits of a professional advisor who can help optimize the process. That’s what Visor wants to provide.

“You provide the same amount of information you provide to a CPA or TurboTax… we make sure that that information is filed securely on AWS and shared between the docs and the backend,” said Zacke. 

The target customers for Zacke’s services are folks who have had a change to their tax situation – whether moving, buying a home, or any other life event; or people who have had a CPA and don’t want to pay the higher fees, he said.
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Visor currently has an operations team of around 34 people split between San Francisco and Atlanta.
“Taxpayers spend $20 billion a year to get their taxes prepared and are stuck between spending hours filling out DIY tax software and hiring an expensive CPA,” said Zacke, in a statement. “

Artificial intelligence has the potential to bring a select set of advanced techniques to the table when it comes to cyber offense, researchers say.

Last week, researchers from Darktracesaid that the current threat landscape is full of everything from opportunistic attacks from teen hackers to advanced, state-sponsored assaults, and in the latter sense, attacks continue to evolve.

However, for each sophisticated attack currently in use, there is the potential for further development through the future use of AI.

Within the report, the cybersecurity firm documented three active threats in the wild which have been detected within the past 12 months. Analysis of these attacks – and a little imagination – has led the team to create scenarios using AI which could one day become reality.

"We expect AI-driven malware to start mimicking behavior that is usually attributed to human operators by leveraging contextualization," said Max Heinemeyer, Director of Threat Hunting at Darktrace. "But we also anticipate the opposite; advanced human attacker groups utilizing AI-driven implants to improve their attacks and enable them to scale better."

Trickbot. The first attack relates to an employee at a law firm who fell victim to a phishing campaign leading to a Trickbot infection.

Trickbot is a financial Trojan which uses the Windows vulnerability EternalBluein order to target banks and other institutions. The malware continues to evolve and is currently equipped with injectors, obfuscation, data-stealing modules, and locking mechanisms.

In this example, Trickbot was able to infect a further 20 devices on the network, leading to a costly clean-up process. Empire Powershell modules were also uncovered which are typically used in remote, keyboard-based infiltration post-infection.

AI's Future Role.Darktrace believes that in the future, malware bolstered through artificial intelligence will be able to self-propagate and use every vulnerability on offer to compromise a network.

"Imagine a worm-style attack, like WannaCry, which, instead of relying on one form of lateral movement (e.g., the EternalBlue exploit), could understand the target environment and choose lateral movement techniques accordingly," the company says.

If chosen vulnerabilities are patched, for example, the malware could then switch to brute-force attacks, keylogging, and other techniques which have proven to be successful in the past in similar target environments.

As the AI could sit, learn, and 'decide' on an attack technique, no traditional command-and-control (C2) servers would be necessary.

AI's Future Role.It is possible that AI could be used to further adapt to its environment. In the same manner, as before, contextualization can be used to blend in, but AI could also be used to mimic trusted system elements, improving stealth.

"Instead of guessing during which times normal business operations are conducted, it will learn it," the report suggests. "Rather than guessing if an environment is using mostly Windows machines or Linux machines, or if Twitter or Instagram would be a better channel, it will be able to gain an understanding of what communication is dominant in the target's network and blend in with it."

Take It Slow. In the final example, Darktrace uncovered malware from a medical technology company. What made the findings special was that data was being stolen at such a slow pace and in tiny packages that it avoided triggering data volume thresholds in security tools.

Multiple connections were made to an external IP address, but each connection contained less than 1MB. Despite the small packets, it did not take long before over 15GB of information was stolen.

By fading into the background of daily network activity, the attackers behind the data breach were able to steal patient names, addresses, and medical histories.

AI's Future Role. AI could not only provide a conduit for incredibly fast attacks but also "low and slow" assaults. It can also be used as a tool to learn what data transfer rates would flag suspicion to security solutions.

Instead of relying on a hard-coded threshold, for example, AI-driven malware would be able to dynamically adapt data theft rates and times to exfiltrate information without detection.
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"Defensive cyber AI is the only chance to prepare for the next paradigm shift in the threat landscape when AI-driven malware becomes a reality," the company added. "Once the genie is out of the bottle, it cannot be put back in again."

Ever since the beginning of the artificial intelligence (AI) boom in the early 2010s, there’s been a corresponding drought in talented AI developers and researchers. The way to fix this is to educate more of them, and last week, MIT announced a $1 billion initiativeto do exactly that: it will establish a new college of computing to train the next generation of machine learning mavens. 

Importantly, the college isn’t just about training AI skills. Instead, it will focus on what MIT president L. Rafael Reif calls “the bilinguals of the future.” By that, he means students in fields like biology, chemistry, physics, politics, history, and linguistics who also know how to apply machine learning to these disciplines.

Two-thirds of the planned $1 billion commitment has been raised so far, with $350 million coming from Stephen A. Schwarzman, CEO of the private equity firm Blackstone. The new college will be named after Schwarzman, and it will include 50 new faculty positions, half of which will focus solely on computer science, while the rest are jointly appointed by the college and other MIT departments. The college is scheduled to open in September 2019, and its new building is planned to be completed in 2022. 

MIT is also angling the college as an ethically minded enterprise; one of its stated aims is to research “ethical considerations relevant to computing and AI.” It’s a frequent criticism of contemporary AI efforts that researchers sometimes ignore the history and lessons of the fields they are trying to “disrupt.” More collaboration should help. 
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“As computing reshapes our world, MIT intends to help make sure it does so for the good of all,” said Reif in a press statement. “The MIT Schwarzman College of Computing will constitute both a global center for computing research and education and an intellectual foundry for powerful new AI tools. Just as important, the College will equip students and researchers in any discipline to use computing and AI to advance their disciplines and vice-versa, as well as to think critically about the human impact of their work.”

 Moore's law – the number of transistors in a dense integrated circuit doubles about every two years while the costs are halved. 
          Gordon Moore, Fairchild Semiconductor (1965)
 
"Moore's Law is over," says Mike Muller, chief technology officer at chip designer Arm, the Japanese-owned company whose processor cores are found inside most mobile phones.

Given Moore's Law has been the engine driving the breakneck pace at which computers have advanced over the past 50 years this statement might seem worrying.

"On one level it's true, but I'd say, certainly from my perspective and Arm's perspective, we don't care," he says.

Muller and his colleagues have good reasons for their indifference to the end of Moore's Law.

For one, the bulk of Arm-based processors are sold into the embedded computing market, where there is still plenty of scope for transistors to get smaller and chips to get faster.

But more importantly, Arm believes the regular boosts to computing performance that used to come from Moore's Law will continue and will instead stem from changes to how chips are designed.

Here are three ways that Arm expects processor design will evolve and advance.
 
1. 3D chips will continue to improve processor performance. Muller believes chip designers will continue to squeeze more power from processors by stacking more transistors and processor dies on top of each other.

"There's a whole bunch of stuff happening in 3D, whether that's within the silicon and 3D transistors stacking within a die, [or] stacking dies together," he said.

2. Computers will rely on increasingly specialized chips. Today's systems offload workloads to processors tailored to accelerate tasks. For example, offloading 3D rendering to GPUs or running trained machine-learning models on Google's TPUs, Muller predicts future systems will have an even more full range of specialized chips.

Greg Yeric, director of Future Silicon Technology for Arm Research, says there's plenty of runway to continue improving accelerators.

"For the next three to five years there's a lot to be gained just by making better CMOS-based machine learning," he says.

3. Computers will move beyond silicon chips. Soon, it's possible we will reach the limits of conventional materials and technologies used to build processors, such as the CMOS (Complementary metal-oxide-semiconductor) chips used today, says Yeric.

At this point, the chips inside systems will become more diverse, with traditional CMOS chips sitting alongside more exotic forms of information processors.

"We're going to start to see accelerators that are hardware differentiated," says Yeric.

"So, you can have a special kind of transistor that does one thing really well, [which] doesn't necessarily do all [computing] well, and you can have a chip that bolts onto a regular CMOS chip.

"We have widgets that vastly outperform CMOS on certain things. It could be photonics; it could be spintronics; it could be new memory.

"Architecting those systems is going to be a bit more of a challenge. However, I really don't see that we're going to have a slowdown at the system level, it's just that the systems won't look like a big monolithic piece of CMOS."

Muller says to expect the likes of neuromorphic, spintronics, and even quantum photonic chips to find their way inside systems.

"There is going to be in the 10-15-year timeframe new technology to take us beyond CMOS," he says.
"Products, as bought by people like you and me, are just going to keep getting better and better.
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"Our jobs [chip designers] might be getting harder and harder, but from a consumer's perspective there isn't going to be a slowing down," he says.

Thirty years ago, it was a big deal when schools got their first computers. Today, it's a big deal when students get their own laptops.

According to Thomas Frey, the senior futurist at the DaVinci Institute think tank, “In 14 years it'll be a big deal when students learn from robot teachers over the Internet.”

It's not just because the technology will be that sophisticated, Frey says, but because the company responsible for it will be the largest of its kind.

"I've been predicting that by 2030 the largest company on the Internet is going to be an education-based company that we haven't heard of yet," Frey said.

Frey's prediction comes amid a boom in artificial intelligence research. Google is developing DeepMind; a complex piece of machine-learning software and IBM is developing Watson-powered robots.

"Nobody has quite cracked the code for the future of education," Frey contends.

His vision for 2030 includes a massively enhanced version of today's open online courses – the kind of instruction you may find with Khan Academy, Coursera, or MIT OpenCourseWare. Only, the instructors won't be humans beamed through videos. They'll be bots, and they'll be smart enough to personalize each lesson plan to the student sitting in front of the screen.

Frey suspects that a new kind of efficiency will allow students to learn at much faster rates than if they had to compete with 19 other students for the teacher's attention. Students will breeze through their material at four or 10 times the speed, completing an undergraduate education in less than half a year.

"It learns what your proclivities are, it learns what your idiosyncrasies are," Frey explains. "It learns what your interests are, your reference points. And it figures out how to teach you in a faster way over time."

He uses the example of Google's DeepMindlearning to play the Atari video game "Breakout." Not only did it quickly pick up on the rules, but within a half hour it figured out a way to achieve incredibly high scores – all with little human input.

Machine learning will accelerate similarly in the education space, Frey says. Online bots will pick up on a student's strengths and weaknesses and use a series of algorithms to tailor the lessons accordingly. Research suggeststhis personalized method is among the most effective at raising kids' overall achievement.
Frey doesn't go so far as to argue education bots will replace traditional schooling outright. He sees them more as a supplement or a kind of tutor. If a child struggles with algebra, a bot may be able to offer some help during homework time or over the weekend.

It's up for debate whether AI can master the subtleties of language, thought, and reason all within the next 14 years. One of the most significant hurdles for machine learning is grasping social interactions. Many AI systems today are still less capable cognitively than a 6-year-old.

Frey trusts 14 years isn't too generous a timeline for the technology to ramp up, given how quickly technology innovation builds on itself. The Internet was beginning to enter a lot of people's homes 14 years ago. But by 2007 people were already surfing the Web on their iPhones, and today the Internet is almost omnipresent in daily life.
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Frey predicts that artificial intelligence will have the same trajectory in the education space. By 2030, DeepMind's ability to master "Breakout" could seem as quaint as dial-up modems do today, and what seemed like a massive library of online content in 2016 could look to future students like a skimpy collection that hardly does anything.

Potholes are a nuisance pretty much everywhere, and the methods traditionally used to keep track of them aren't efficient. Whether it be driving around to visually inspect roads or watching videos of streets to spot and prioritize the repair of pavement damage, strategies typically used by towns and cities require a fair amount of time and labor. But AI could make that process a bit easier and quite a bit faster. One group exploring the use of AI to support the municipal officials in charge of road maintenance has been developing a software system that could not only aid in road repairs but also bridge and building maintenance as well.

The group, led by John Zelek at the University of Waterloo, has been using road images sourced from Google Street View to develop its system, which automatically analyzes photos of roads to spot potholes, cracks, and other damage. In theory, municipal officials could use the software to analyze images taken via vehicle-mounted phone cameras when employees are driving as part of their day-to-day work. "If governments have that information, they can better plan when to repair a particular road and do it at a lower cost," Zelek said in a statement. "Essentially, it could mean lower taxes for residents."
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The researchers are also looking to apply the system to drone images taken of bridges, buildings, and other infrastructure as well as images of construction projects. "If the parts of a new building aren't coming together properly, it would be very beneficial to flag problems before the next 30 stories have been put up," said Zelek.