Frost & Sullivan's Information & Communications Technology (ICT) team conducted a small-scale survey, Global Next Wave Technology Disruptors, 2018, of 112 thought leaders from around the world to seek opinions on the technologies that will have a profound transformative impact on existing industry dynamics, value chains, and business models across multiple vertical markets in the next 10 years.

In addition to providing quantitative insight, the study also provides a top-level assessment of eight emerging technologies: 5G, Artificial Intelligence (AI), Blockchain and Distributed Ledger, Human Brain-Computer Interface, Human Intelligence Augmentation, Internet of Things (IoT), Natural Language Interfaces (NLIs) and Quantum Computing.

"Numerous technologies with limited adoption/availability at present will rise in relevance over the next ten years. 5G will play an important role over the next five years as commercial deployments commence, while Quantum Computing is set to have a huge impact in the coming decade," said Adrian Drozd, Research Director, ICT. "However, thinking of these emerging technologies in isolation will limit their effectiveness. For instance, IoT cannot reach its potential without AI, and AI can be powerful only by accessing the data generated by IoT."

"Technologies will reach maturity at different times; while some are already widely used, others are still in the development phase," noted Drozd. "Technology development should be guided by the use cases and real-life deployments that the solutions promise to enable."

New technologies are emerging at an unprecedented rate, each promising to be the next transformative force that will drive fundamental shifts across industries and society. Companies looking to tap growth opportunities in their respective sectors should consider joining Frost & Sullivan's global IoT & Digital Transformation Growth Partnership Service program.

A bipartisan act designed to rein in unwanted robocalls in the U.S. passed through the House of Representatives in a decisive 429-3 vote last Wednesday, pushing the legislation one step closer to ratification.

The Stopping Bad Robocalls Act, sponsored by Energy and Commerce Committee Chairman Frank Pallone, Jr. (D-NJ), aims to put an end to spam phone calls by leveling carrier requirements and bolstering Federal Communications Commission authority to take action against offenders.

Under the bill, carriers must implement call authentication technology like STIR/SHAKEN and offer call-blocking services to customers free of charge. Further, the FCC is directed to issue rules protecting customers from unsolicited communications, enact safeguards against robocall exemption abuse and report back to Congress on program effectiveness.

A provision also grants the FCC a more robust set of punitive options when dealing with robocallers. For example, the commission can take action against an offender up to four years after an initial violation, up from the one year afforded under the current statute of limitations.

The legislation passed with immense support from members on both sides of the aisle.

"Today, the House of Representatives voted to restore Americans' confidence in the telephone system and put consumers back in charge of their phones," the bill's sponsors said in a statement. "We're proud of the strong support our bipartisan Stopping Bad Robocalls Act received this afternoon and look forward to working with our colleagues in the Senate to produce a bill that the President can sign into law. The American people are counting on us to help end the robocall epidemic, and we will deliver for them."
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Apple, too, is working on technology to slow the robocalling plague, which according to an FCC report resulted in some 48 billion unwanted calls in 2018. The Cupertino tech giant's upcoming iOS 13 operating system includes a new feature that uses artificial intelligence to identify and silence incoming calls from unknown parties.

One of the highlights of MIT’s Emtech Next Conference in June was a debate on whether we should tax robots. We heavily tax human workers, so why not the machines that replace them? Then, goes the theory, that tax money could help provide training or benefits for workers who’ve lost their jobs to automation.

Ryan Abbott, a law professor at Surrey University, presented a convincing case for such a tax– or, more precisely, for removing the tax incentives that favor automation over human labor. Many business decisions to automate processes, argued Abbott, are driven by these tax advantages, not because the robots are more productive. If automation is more efficient, suggested Abbott, let that be the reason businesses decide to use it – not some tax break.

The counter-arguments from Ryan Avent, economics columnist at the Economist, were that taxes (or ending tax breaks) would slow innovation, and, in any case, there is little economic evidence that robots are taking over jobs. While these points appear to be less convincing, a robot tax alone won’t solve the lack of good jobs. But removing the financial incentives that favor automation over humans will at least create a level playing field.

Even more erroneous is the argument that a robot tax is a slippery slope: are they going to tax my Roomba or smart toaster next? Somehow, we manage to tax labor, and yet you can still mow your lawn and clean your house without paying the government.

Alas, the Emtech Next attendees disagreed, with 70% voting against the robot tax after hearing the debate.
One of the recurring themes at the conference was that businesses could better exploit automation and AI not just for their own efficiency, but to improve productivity and grow the economy as a whole. How? A pair of engineers, Meera Sampath at the State University of New York and Pramod P. Khargonekar at the University of California, Irvine, presented their plan for “socially responsible automation,” which starts with getting technologists to think harder about how their creations will actually be used and how those uses can benefit workers and society.

A shout-out to workers: Too often in these discussions of how automation and AI are affecting jobs, the voices of workers themselves are absent. MIT’s Thomas Kochan, speaking at the conference, at least provided a reminder to listen to such views, even in the early stages of product designs, and to involve them more in automation decisions. And, he argued, companies need to take the time to give their existing workforce the skills and training necessary to integrate them with changes in automation better.

Let’s admit it, every time we hear the word “co-bot” we cringe. Yes, there have been remarkable advances in robotics over the last decade that allow these machines to more safely and comfortably work alongside people and do more human-like tasks. And, yes, we know the promise is that, by taking over mundane tasks, these robots will free people up to do more interesting and, hopefully, productive ones.

But that’s a business decision that too often companies are not taking; instead, many are simply replacing their workers. If robots do 20% of the tasks that a worker was doing, then you need 20% fewer people to get the job done.

It’s become increasingly clear to economists that this one reason we’re facing a crisis: wages are flat, and job opportunities are limited for many workers.

MIT economist Daron Acemoglu blames this on what he calls “so-so” automation and technologies. Advances like automation should be a boon to productivity, but productivity growth has been sluggish for more than a decade. That, says Acemoglu, is because too often companies are automating jobs even when the machines are not more productive, because of the tax mentioned above distortions and a general enthusiasm for robots. So, you have a double whammy; not only are robots replacing workers, they’re not particularly adept at growing the economy.

The way out is to create new, productive tasks for the workers replaced by the automation. (That’s what happened in the past). And that’s where AI could be useful. Examples are not that hard to imagine. For instance, if you free up healthcare workers, such as radiologists and nurses, from routine tasks, they could use AI systems to collect and analyze far more patient data, expanding their capabilities and giving them new ways to advise and treat patients. Acemoglu cites similar examples existing in education and manufacturing.
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But, and this is key, Acemoglu warns that this won’t necessarily happen on its own. You can’t leave this up to the markets or the technologists. We need to pursue this goal deliberately.

Since Microsoft and Amazon announced plans to integrate their respective personal digital assistantslast summer, there's been almost no official update on the status of the partnership.

It seems, however, like there's finally movement happening.

An April 27 update to the Cortana support page actually mentions Alexa. "Cortana and Alexa are still getting to know each other. Soon you'll be able to ask Alexa to buy things, add items to your shopping list, access your Alexa skills, and more," says the brief update on the page. Yes, "soon" is vague. But it's something.

Typing "Alexa" into the search box in Windows 10 (on the Fall Creators Update version, at least) yields a message saying "I'll be able to connect you to Alexa soon. Stay tuned!"

Last summer, Amazon and Microsoft announced that their respective personal assistants would be able to talk to one another, so customers could opt to use the assistant most suited to a particular task. Amazon and Microsoft officials said last year that they'd make Cortana-Alexa integration available before the end of calendar 2017. Since then, there's been no update on when this might arrive.

In early March 2018, Cortana team members told Windows Insiders that the Cortana-Alexa integration was in "internal self-hosting" at Microsoftat the moment. Microsoft is working to "make sure it's (the integration) a great experience," the team said, noting that bringing together the two different speech stacks is "non-trivial."

Recently, Cortana's new boss, Javier Soltero, admitted that "skills for the sake of skills won't fly." He told PC World that skills usage isn't "quite as deep as most people think it is." He also acknowledged Microsoft's in total catch-up mode on this front. (That's for sure, with Alexa at 40,000-plus third-party skillsat last count.)
Given Cortana is set to access Alexa skills via this integration partnership, maybe Cortana's skills shortage is less horrible than meets the eye.
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Soltero also declined to say whether there are any other Cortana-powered speakers in the works. Currently, there's one from Harman-Kardon. I think speakers might not be where Microsoft is focusing; perhaps it's more about conferencing systems, microphones or other more business-centric peripherals.

A new lidar sensor could equip thousands of driverless cars with the sensing abilities required to drive at high speeds on the open road.

Lidar has become the primary way most driverless cars sense the world around them, bouncing laser light off nearby objects to create 3-D maps of their surroundings.

For years, the industry leader in lidar has been Velodyne, which builds some of the most expensive, ultra-high-resolution sensors available. But the rapid growth of self-driving vehicle research prompted other firms to start making them too – among them, a startup called Luminar, which was set up by Stanford drop-out Austin Russell and came out of stealth last year.

Luminar’s technology is different to other lidar systems. It uses a longer wavelength of light to operate at higher powers, allowing it to see darker objects over longer distances. It’s also able to zoom in on areas of specific interest.

But its sensors, which use a mechanical mirror system and expensive indium gallium arsenide semiconductors, were difficult and pricey to produce. Early units cost at least tens of thousands of dollars and required an entire day of human labor to assemble.

Over the last year, Russell, who was one of MIT Technology Review’s 35 Innovators Under 35 in 2017, says the firm has taken steps to change that. It acquired a chip design firm called Black Forest Engineering, hired consumer electronics experts, and set up its manufacturing complex in Orlando – all with the aim of building its sensor at commercial scale.

As a result, Russell says that the latest version of the sensor is approaching being auto-grade, meaning it should be ready for extreme temperatures, inclement weather, and other adverse conditions a production car might be exposed to (though it’s yet to be certified as such). The careful redesign of its laser detector chip, meanwhile, has cut its cost from tens of thousands of dollars to just $3, and automation means the sensors can now be built in eight minutes.

All of that means Luminar reckons it can offer a set of sensors for “a few thousand” dollars, Russell says. At the same time, it’s also boosted the specs, so the sensor can detect objects that are 250 meters off—enough for 7 seconds of reaction time at 75mph.

Ingmar Posner, an associate professor of information engineering at the University of Oxford and founder of the university’s autonomous-driving spinoff Oxbotica, says that the specifications and price point of the sensor “sound great.” But he also points out that the price will need to fall further if the sensors are to be used in affordable consumer vehicles.

That could yet happen. Russell points out that the sensor cost is related to the scale of production, and by the end of the year Luminar plans to be building 5,000 of its sensors every quarter. That’s a lot – more than the 10,000 sensors that competitor Velodyne planned to build last year – and would give it enough, Russell claims, to equip every autonomous test car on the roads by the end of this year.

The major hurdle to that kind of market dominance is convincing other research groups and automakers to switch from their existing sensors – something that would require rewriting control software and re-mapping entire cities so cars can navigate using the new sensors. Russell likens the situation to “ripping off a Band-Aid,” because it will need to happen at some point as carmakers switch to using auto-grade, rather than experimental, sensors.
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What remains to be seen for Luminar, though, is just how soon that Band-Aid gets pulled.

Chinese researchers have developed a method using microscopic robots to kill cancerous tumors and stifle future growth.

The study published in the journal Nature Biotechnology uses nanotechnology to deliver thrombin, an enzyme that helps blood to clot.

The thrombin was placed using DNA origami, a process where DNA is folded into specific shapes. In this case, the DNA-based nanorobot was formed into a hollow tube carrying thrombin, researchers said. When the nanorobot would come in contact with the tumor, the tube automatically would open and deliver the thrombin.

The scientists behind this study tested the delivery bots by injecting them into mice with human breast cancer tumors. Within 48 hours, the bots had successfully grabbed onto vascular cells at the tumor sites, causing blood clots in the tumor’s vessels and cutting off their blood supply, leading to their death.

Remarkably, the bots did not cause clotting in other parts of the body, just the cancerous cells they’d been programmed to target, according to the paper.

The scientists were also able to demonstrate the bots did not cause clotting in the healthy tissues of Bama miniature pigs, calming fears over what might happen in larger animals.

Nanotechnology is viewed as a promising option for treating cancer. It involves work in science, engineering or tech of objects the size of nanometers. For perspective, a human hair is between 80,000 and 100,000 nanometers wide, according to the National Nanotechnology Initiative. 

"Our data show that DNA nanorobots represent a promising strategy for precise drug delivery in cancer therapy," read an excerpt from the study.

The goal, say the scientists, is to eventually prove these bots can do the same thing in humans that’s been done in animals. Of course, more work needs to be done before human trials can begin.
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Regardless, this is a huge breakthrough in cancer research. The current methods of either using chemotherapy to destroy every cell just to get at the cancer cell are barbaric in comparison. Using targeted drugs is also not as exact as merely cutting off blood supply and killing the cancer on the spot. Should this new technique gain approval for use on humans in the near future it could have impressive effects on those afflicted with the disease.

If the Department of Transportation grants GM's latest Safety Petition, the automaker will be able to deploy its no-steering-wheel, pedal-less autonomous car next year. GM has not only revealed what its level 4 self-driving vehicle would look like but also announced that it filed a Safety Petition to be able to deploy its utterly driverless version of Chevy Bolt called Cruise AV in 2019. The company describes it as "the first production-ready vehicle built from the start to operate safely on its own, with no driver, steering wheel, pedals or manual controls."

The Cruise AV is much different from the self-driving Chevy Bolts GM is testing in California. It has no controls whatsoever, not even buttons you can push. It treats you as a passenger, no matter where you sit. The car can even open and shut doors on its own. Now, autonomous cars like this don't meet the Federal Motor Vehicle's safety standards. Automakers could apply for an exemption, but the government can only exempt 2,500 vehicles every year. GM President Dan Ammann said that the company is not seeking an exemption, though – instead, it wants to "meet that standard differently."

He explained:

"What we can do is put the equivalent of the passenger side airbag on that side as well. So, it’s to meet the standards but meet them in a way that's different than what's exactly prescribed, and that's what the petition seeks to get approval for."

Several automakers and transportation companies banded together last year to call for a change to those rules. "Without changes to these regulations," GM VP Michael Abelson told a subcommittee that time, "it may be years before the promise of today's technology can be realized and thousands of preventable deaths... will happen."
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Automakers will have to see those changes come to light if they want their fully autonomous cars to hit the road. GM might beat them to the punch, but rival companies like Ford, Mercedes, and Waymo all plan to release cars with no steering wheels of their own.

Serial entrepreneur and social media expert Gary Vaynerchuk said it best: “I don't think anybody who's a major internet company can live without having a major voice strategy.” 

Voice will account for nearly 50% of search on mobile in the next three years and will be the primary way consumers search for and make purchases on their phones and voice-enabled devices. Everything we do will involve voice in some way, from shopping to ordering groceries to asking what the weather is outside. And thanks to the nearly 20 million voice-enabled smart speakers sold thus far by Amazon and Google, we’re already seeing the fight for the real estate in consumers’ homes.

The smart-speaker movement is taking the world by storm. We see some of the most significant companies in the world, like Amazon and Google, set the tone for how and where voice can impact consumers. And, why wouldn’t they? Nearly 30 million households are projected to have a voice-first device by the end of 2017. While they are essential in kick-starting the revolution, these smart devices won’t be the last stop on the voice train.

While the adoption of smart speakers has risen rapidly, the usage of third-party applications, or “skills,” has been less than impressive. Less than 3% of skills built on top of Alexa are actually getting used, which is in most cases a result of the limited functionality of these applications. For example, Domino’s users want more than just their “easy order” or something they order over and over again. Reviews of the Starbucks integration with Alexa note that many orders never make it to the barista, only to bring more users back to the mobile app instead. And those that want flowers for that special someone are limited to seasonality or occasion with the 1-800 Flowers integration, without a way to actually see the flowers or gifts they’re ordering. Voice is capable of so much more.

The large platform companies have focused their energies on developing voice assistants that offer broad yet shallow integrations with third parties. As a result, “skills” just scratch the surface of what’s possible with voice. As the examples above demonstrate, while it’s relatively simple to build and launch an application for these platforms, you’re limited by what’s possible from a functional point of view.

To realize voice's full potential, companies need a more deeply integrated voice experience that is brand specific and is all knowing about their business. In retail, for example, the art of the consumer experience lies in discovery and personalization. Very rarely do you know the exact product you’re looking for when you go to a website or browse the “most popular” products section. That’s why companies invest millions in their mobile apps and websites, helping guide you through an experience to find exactly what you want. Voice is going through an evolution of its own, assisting companies to understand how to build much more meaningful customer experiences. It could be as simple as knowing that when you want a new sweatshirt, ordering your last order just won’t do. You want to see it in front of you, most likely on a mobile device and will ask a series of questions around color, price, size, material, and reviews. 

Imagine a voice experience where you can search for flowers for your mother, or someone special, watching the results on the screen in front of you change based on your budget, your color preference or type of flower. Imagine a fall selection of coffee flavors coming out in your favorite chain coffee shop, empowering you to add pumpkin spice, a shot of vanilla, and change from cold to hot once you’ve stepped outside. 
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There’s no question that Google and Amazon have birthed a genuinely revolutionary time in technology, conditioning us to be comfortable using a voice-powered device or experience, but we’re just at the precipice of the potential of voice. Voice, just like the introduction of the mobile device before it, will fundamentally change how we interact with the world around us. Only when you understand that, will you see how powerful voice will be.

Robots are taking our jobs, no doubt about it. Just in the past year, we’ve seen barista robots, fast-food robots, and even pizza delivery robots. But robots can’t replace journalists, right? The dogged reporters, members of the vaunted Fourth Estate, the men and women who bring us the news stories we read every day?

Think again. It’s happening, and the odds are that you’ve been reading stories created by artificial intelligence in local and world news already.

A year ago, the Washington Post introduced Heliograf, an in-house program that automatically generates short reports for their live blog. It was first used during the Rio Olympics to provide information such as the results of medal events for services like Alexa. At that time Sam Han, engineering director of data science, said, “The next challenge is to broaden the subjects covered, deepen the kind of analysis possible and identify potential stories for our newsroom.”

It looks like that day has arrived. Over the past year, the Post has published 850 stories from Heliograf, expanding its reach to include reporting on subjects like congressional races and high-school football games.
Other outlets like the Associated Press have also begun to rely on automated software to create content for readers. Executives are quick to point out that the AI is not meant to replace reporters, but instead allow them extra time to develop and relate more important and relevant stories. “Heliograf will free up Post reporters and editors to add analysis, color from the scene and real insight to stories in ways only they can,” said Jeremy Gilbert, director of strategic initiatives at the Post.

Not to mention the fact that machines don’t make typos and provide more accurate reporting. As Francesco Marconi, AP’s strategy manager put it, “In the case of automated financial news coverage by AP, the error rate in the copy decreased even as the volume of the output increased more than tenfold.”
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What robotics means for the future of reporting is an open question. Many of today’s biggest names in journalism got their start covering local news or high school sports. In the end, it all comes down to ad revenue. Although the Post can appraise the clicks and pageviews Heliograf generates, evaluating how much it impacts the bottom line is a more difficult task. In any event, it seems like reporters and robots will be working side-by-side for the foreseeable future.

Today’s connected car is not so much a smartphone on wheels; with so many microprocessors chatting with one another across and beyond the vehicle, it is now more aptly described as a data center on wheels.
A tremendous influx of software content, connectivity, entertainment services and autonomy functionality is transforming vehicles. We are rapidly approaching a point in which the automobile will be built around the software, as opposed to the other way around.

Tesla recently made the first deliveries of its mass market “Model 3” electric vehicle. Controls are focused around a large touch screen and the shifter adds “Autopilot” to the traditional “Park”, “Reverse”, “Neutral” and “Drive” options. Full self-driving capability is promised for a later date with simply an Over-the-Air software update.

This generalized shift to software, in turn, means the opportunity for a cyber-attack is growing rapidly. Even with the larger potential attack surface, and while cybersecurity threats will never be eliminated altogether, it is also true that substantial work is taking place to engineer tomorrow’s vehicles to be systematically more able to deal with those threats in a safe and predictable manner.

Vehicle manufacturers have announced these important vehicle cybersecurity enhancements:
     •  Building-in security features to protect safety critical systems,
     •  Isolation of control systems from communications systems,
     •  Leveraging security techniques to limit unauthorized access to software and updates,
     •  Use of threat modeling and simulated attacks to inform design decisions and
   • Creation of the  Auto ISAC (Automotive Information Sharing and Analysis Center) to enhance cybersecurity awareness and collaboration across the industry.

Cybersecurity is being moved to the vehicle’s design foundation, thanks to increased coordination across the broadening, diversifying automotive ecosystem. We are seeing the industry move away from the traditional point-to-point approach to self-healing systems.

The effect is the emergence of a holistic, systems-level approach to building organically secure vehicles that are ultimately capable of self-healing. Self-healing means responding to the inevitable cybersecurity threats in a safe and predictable manner. For example, in detecting and suppressing the introduction of malware or anomalous instructions in the auto ecosystem from manufacturers and suppliers, to communication and control systems throughout vehicle lifetimes.

Security by Design. Security simply can no longer be an afterthought. Security must be a foundational consideration throughout the entire software-development flow for automobiles, from design to delivery. Original equipment manufacturers (OEMs), Tier 1 suppliers and other industry stakeholders must all start wearing their Chief Security Officer hat.

The industry has always had a strong emphasis on physical security; security processes for brakes, steering and other physical components have long been intensely codified. So sudden has been the surge toward software in vehicles, however, that it has somewhat crept up on the industry. Cybersecurity has effectively been stapled on top of more and more sophisticated services leveraging increased Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications. 

There have been some limited-in-scope efforts to move toward an approach of security by design and establish shared guidelines. For example, the U.S. Department of Transportation (DoT) set up the Public Key Infrastructure (PKI) and its certification process that ensures trust and security in the building of V2V and V2I systems.

There is now recognition growing across the industry that the collaboration must be significantly more inclusive in order to sufficiently address the challenges. In the last two years, cybersecurity incidents have been reported broadly across the industry at Chrysler, Ford, GM and Tesla, as well as in commercial vehicles. High tech car thieves today are leveraging laptops and potentially even smartphone apps to steal vehicles.
Risk Management. There is a bit of sensational hysteria growing around the global security conversation with automobiles becoming more and more connected and autonomous. The truth is that the global, increasingly broad automotive ecosystem is working more collaboratively to architect vehicles with cybersecurity at their foundation.

Risk based approaches such as NIST’s Cybersecurity Framework (CsF) are already mandatory for government agencies and recommended for critical infrastructure such as transportation.

Reporting, Sharing and Training. While the automotive industry has a very mature approach to reporting, information sharing and training when it comes to physical issues with the car—well-defined reporting and recall processes around a problem with the brake or accelerator, etc.—the model around software and cybersecurity is not nearly as formalized.
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The good news is that new technologies such as automotive Intrusion Prevention Systems (IPS) and Runtime App Self Protection (RASP) are emerging to limit the scale of harm that can be unleashed by any single attack, to reduce attack surfaces and to harden cybersecurity capabilities. Because coordination is increasing, the ecosystem is moving toward a system-of-systems approach to automotive security.