Financial traders rely heavily on computer financial simulations for making buying and selling decisions. Specifically, “Monte Carlo” simulations are used to assess risk and simulate prices for a wide range of financial instruments. These simulations also can be used in corporate finance and for portfolio management.

But in a digital world where other industries routinely leverage real-time data, financial traders are working with the digital equivalent of the Pony Express. That’s because Monte Carlo simulations involve such an insanely large number of complex calculations that they consume more time and computational resources than a 14-team, two-quarterback online fantasy football league with Superflex position.

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The National Science Foundation (NSF) is not inclined to wait for next-generation (NextG) networks. And who can blame it? NextG promises faster cellular, Wi-Fi, and satellite networks, all of which can be used to enhance data streaming, wireless communications, analytics, and automation.

For the NSF, this translates into improved national defense, education, public health and safety, transportation, and digital infrastructure. For enterprises, NextG means greater efficiency, flexibility, business insights, and more opportunities to replace human workers with robots. (I’m just sayin’.)

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The U.S. military is devoting time and resources into research on improving the signal quality and security of 5G--efforts that, if history is any indication, eventually will result in technologies that are available to commercial enterprises.

As Breaking Defense reports, the Defense Advanced Research Projects Agency (DARPA) has awarded roughly $500,000 in “exploratory” funding to wireless startup MixComm to demonstrate whether silicon-based millimeter wave (mmWave) power amplifiers can economically boost radio signals so the Department of Defense (DoD) can leverage 5G wireless connectivity globally.

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Quantum computers can learn to reason, even when burdened with uncertainty and incomplete data, concludes a team of scientists from U.K.-based quantum software developer Cambridge Quantum Computing (CQC).

This ability is similar to intuitive human reasoning, which allows people to draw conclusions and make decisions despite a lack of comprehensive information. CQC’s research confirms a belief among many scientists that quantum computers have a natural propensity for reasoning.

In a paper published on the open-access scholarly archive arXiv, CQC scientists detail how they developed methods that demonstrated how quantum machines can learn to infer hidden information from general probabilistic reasoning models. If replicable, these methods could improve a broad range of applications for quantum computing, including medical diagnoses, fault-detection in mission-critical machines, and financial forecasting for investment management.

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I know what you’re thinking. “6G? He wants to blather on about 6G, when we barely have 5G?”

Point taken. But 5G’s seemingly interminable rollout should not preclude wildly premature and breathless anticipation over its successor. Let’s face it, the time will come when we’ll all be complaining about the limitations of puny little 5G. Plus, isn’t wildly premature and breathless anticipation the essence of technology publishing?

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As IT professionals know, enterprise server farms are huge energy consumers, and the larger they are, the more voracious their appetite.

Quantum computing could help because it is not only supposed to solve complex problems exponentially faster than classical computing, it’s also supposed to do so while consuming less energy. However major barriers—such as creating the extremely low temperatures required to enable superconductivity that is used in quantum-computing components—stand in the way.

Now researchers at MIT are working on a tiny device that could help enable quantum computing and drastically reduce server-farm costs. The roots of this device—made from a superconducting nanowire—stretch back to a similar concept developed in the mid-1950s by an MIT electrical engineer who died tragically young before his vision could become reality.

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You will have more connected devices than ever on your network in 2021, especially if you’re in healthcare, retail, or logistics, industries that are among the early adopters of the Internet of Things (IoT). You’ll have devices on your network edge, in your headquarters, on vehicles, in machinery, in your stores, in employees’ homes, and on public property.

And there’s a good chance that some or many of these IoT devices have built-in security vulnerabilities that can endanger your network. In trying to capitalize on the voracious global appetite for connected commercial devices, many IoT manufacturers and developers are shoveling out enterprise IoT devices with, shall we say, varying levels of regard for security.

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The pro-Trump rioters who invaded the Capitol on January 6 came with smartphones to record and celebrate what they thought was a righteous effort to prevent president-elect Joe Biden from taking office two weeks later.

Now those electronic devices, along with the GPS data they generated, are being used to track the location of rioters within the building as federal law enforcement officials continue to make arrests and build criminal cases.

Among the acts being investigated: breaking through police barriers, smashing windows, and assaulting police officers and media members. Five people died including a Capitol Hill police officer who was bludgeoned with a fire extinguisher.

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