Are you imbibing enough caffeine for peak performance? Military researchers may have the answer.

Caffeine isn't always as magical as we hope. 

We drink cup after cup of coffee to try to finish an important project or remain conscious during perhaps the most tedious meeting ever. Yet it doesn't always turn us into the superheroes of stamina we wish it did.  

Leave it to scientists working for the US Army to figure out how to get the most out of our caffeine intake. 

In a study published Monday in the Journal of Sleep Research, Department of Defense researcher Jaques Reifman outlined how a newly created algorithm can determine the best dosage of caffeine to take at the right time. 

Reifman, who researches high-performance biotechnology software for the military, said the algorithm can identify safe, effective caffeine-dosing solutions that result in the kind of alertness that makes us more productive. 

Because caffeine affects everyone differently, Reifman performed psychomotor vigilance task (PVT) tests that fed data to the algorithms to figure out the best caffeine strategy and maximize alertness at specific times.

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"We found that by using our algorithm, which determines when and how much caffeine a subject should consume, we can improve alertness by up to 64 percent, while consuming the same total amount of caffeine," Reifman told Science Daily on Monday. "Alternatively, a subject can reduce caffeine consumption by up to 65 percent and still achieve equivalent improvements in alertness."

The Army is using the new algorithm with soldiers in training and plans to license the algorithm.

New Safari privacy features on MacOS Mojave and iOS 12 crack down on nosy websites

When Apple announced a new Safari privacy feature last year called intelligent tracking protection, advertisers accustomed to tracking your behavior online squealed. Get ready for some more squealing.

9 Revolutionary Ways Machine Learning Is Changing Marketing

AI and machine learning have a lot to offer to the marketing arena. In addition to simplifying many mundane tasks, this technology might finally help marketers achieve relevance at scale. Here are nine areas where machine learning is making marketers' lives easier.

Artificial intelligence (AI) and machine learning have a lot to offer to marketers. In addition to simplifying several mundane tasks, this technology might finally help marketers achieve relevance at scale and ensure "the most pertinent content reaches the most promising customers at the moments of greatest influence across multiple channels and markets."

Many marketers have faith in AI's contribution to their field, but not many are implementing it. Eighty-five percent of executives believe that AI technologies will help their companies gain more competitive advantages, yet only 10 percent are using AI today.

If you are among the majority of companies not using AI and you're not sure where to start, here are nine areas where machine learning is making the life of marketers easier.

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Cybersecurity FBI Declaws Russian Fancy Bear Botnet

The FBI has disrupted a network of half a million routers compromised by the group of Russian hackers believed to have penetrated the Democratic National Committee and the Hillary Clinton campaign during the 2016 elections, according to reports.

The hacker group, known as "Fancy Bear," has been using a malware program called "VPN Filter" to compromise home and small office routers made by Linksys, MikroTik, Netgear and TP-Link, as well as QNAP network-attached storage devices.

VPN Filter is "particularly concerning" because components of the malware can be used for the theft of website credentials and to target industrial system protocols, such as those used in manufacturing and utility settings, Cisco Talos Threat Researcher William Largent explained in a Wednesday post.

"The malware has a destructive capability that can render an infected device unusable," he said, "which can be triggered on individual victim machines or en masse, and has the potential of cutting off Internet access for hundreds of thousands of victims worldwide."

LinkedIn is nearly useless for actually getting a job

Congrats on your 1,500 LinkedIn connections. But did they help you snag a job?

Weak online connections on job sites and social networking sites are no match for “strong connections” — i.e., close friends and family members with whom you communicate at least once a month — when it comes to landing a gig, according to a new study from the Institute for Operations Research and the Management Sciences.

The survey of 424 college-grad LinkedIn users, published this week in the INFORMS journal Management Science, asked about various job-search avenues: job sites like Monster.com, social-networking sites like LinkedIn, print media, close friends and family offline, and career centers and recruiters. It also took stock of how many leads, interviews and offers those channels spawned, and measured the number and strength of the job hunters’ connections.

Tesla settles class-action lawsuit over its Autopilot system

Tesla’s Autopilot keeps making headlines for all the wrong reasons.

The electric car maker has settled a class-action lawsuit with buyers of its Model S and Model X vehicles who alleged that the assisted-driving system was “essentially unusable and demonstrably dangerous.”

The 2017 lawsuit in San Jose federal court named six Tesla Model S and Model X owners from Colorado, Florida, New Jersey and California who alleged the company had engaged in fraud by concealment, and had violated various state consumer protection and unfair competition laws.

The Tesla owners said they had paid an extra $5,000 to have their cars equipped with the Autopilot software, which promised to provide additional safety features, but in fact was “completely inoperable,” according to the complaint.

The case, settled late Thursday, was closely watched in the automotive and legal communities, as it was the only known court challenge Tesla faced with regard to its assisted-driving technology.

The settlement came the same day a police report obtained by the Associated Press about a Tesla crash in Utah earlier this month showed that the vehicle — which was in Autopilot mode at the time of the crash — actually accelerated in the seconds before it smashed into a stopped fire truck.

The report suggested that the Tesla was traveling behind another vehicle at 55 mph, but accelerated automatically to its preset speed of 60 mph when the leading car switched lanes.

The vehicle’s 29-year-old driver had told police she was on her phone prior to the crash — which resulted in her breaking a foot — and thought the Tesla’s automatic emergency braking system would stop before the car hit anything.

She said she had owned the car for two years and used the semi-autonomous Autopilot feature on all sorts of roadways, including on the Utah highway where she crashed, according to the report.

The police said car data showed the driver did not touch the steering wheel for 80 seconds before the crash, and the driver said the car did not provide any audio or visual warnings prior to impact.

Tesla has said it repeatedly warns drivers to stay alert, keep their hands on the wheel and maintain control of their vehicle at all times while using the Autopilot system.

The company has come under increased scrutiny over Autopilot in recent months after two Tesla drivers died in crashes in which Autopilot was engaged. The most recent fatal crash, in March, is being investigated by safety regulators.

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On Wednesday, two US consumer advocacy groups also urged the Federal Trade Commission to investigate what they called Tesla’s “deceptive and misleading” use of the name Autopilot for its assisted-driving technology.

Payphone lines aren't essential, CRTC rules as it discontinues wholesale access rates

Payphones continued their slow march to obsolescence this spring when the federal telecom regulator concluded payphone lines are not an essential service in a country where most people own cellphones.

Citing the diminishing demand for payphones and the proliferation of wireless services, the Canadian Radio-television and Telecommunications Commission decided in April to discontinue a regulation that forced BCE Inc. and Telus Corp. to offer payphone lines at a lower price than regular business lines. It gave them one year to phase out the discount for smaller payphone operators.

This marks the end of a 20-year-old scheme to inject competition into the formerly monopolized payphone market. In 1998, the CRTC opened up the market. To give new entrants a chance, it mandated that Bell and Telus sell payphone lines to smaller competitors for 25 per cent less than business lines. At the time, the CRTC said this would “stimulate service innovation, foster a viable domestic industry and increase total market revenues.”

Fast-forward to 2018 and the notion of a competitive payphone market seems quaint given the advance of mobile phones. Wireless services now dominate the communications industry with 31 million wireless subscriptions in Canada, whereas the number of payphones plummeted to 57,542 in 2016 from 185,000 in 1998.