When COVID-19 first hit, I was terrified to leave my home. As the father of three and a husband of 25 years, I felt helpless to protect my family as the narrative changed seemingly day-to-day. I knew fashioning medical masks from scarves was far from ideal, so I made masks for my family, friends, and any elderly customer that wanted one, using my 3D printer and some micron-level cloth filter material intended for residential HVAC systems. Still, I felt like I had no control over what was happening. The CDC reported in 2020 that between June 24 and 30, close to 40% of adults in the U.S. reported at least one adverse mental health concern--including anxiety, depression, substance use, and suicidal ideation, among others. UK-based researchers introduced the term "COVID-19 anxiety syndrome" in Psychiatry Research, noting avoidance, worrying, daily symptom checking, and threat monitoring as key traits.

The future of transportation is all about brilliant engineering, sure, the sort of fast-moving modeling and number-crunching that Volvo employees needed to pull to transform a concept car to a production one in less than two years. Ford making strategic, symbolic moves and purchases in the big, struggling city it once helped make great. Massachusetts attempting to balance the leeriness of its citizens about self-driving tech with its desire to maintain its reputation as a center of innovation. This week was all about automakers, tech goliaths, states, and cities making canny moves to position themselves to welcome the next few months, years, and decades. Sometimes, you gotta get down and dirty.

Asset managers are spending tens of millions on data science. The idea is to use lots of data and machine-learning tools in search of trading ideas and blind spots, the Journal reports. "Most of it is at an early stage, and I don't think it's matured yet," says Onur Erzan, a senior partner at consultant McKinsey & Co. "There will be new sources of data and it will help with investment decisions, but the real question is can an asset manager sustain an edge on those kinds of insights." This is how it starts. "Petter Stensland's foray into data began in late 2012 when, as a junk-bond analyst at AllianceBernstein Holding LP, he needed to analyze the prospects of the many oil-and-gas companies emerging in the nation's energy boom," the Journal says.

Hours after Tesla sued its former employee on charges he had stolen company secrets, and days after chief Elon Musk had called him a saboteur, the Silicon Valley automaker made a startling claim. The company had received a call from a friend of the employee, Martin Tripp, saying he would be coming to Tesla's Gigafactory battery plant in Nevada to "shoot the place up," according to a Tesla spokesman. But Tripp, who says he became a whistleblower after seeing what he called dangerous conditions in the company's car batteries, told The Washington Post he had said no such thing. Emails exchanged that day between him and Musk, provided to The Post and confirmed by Tesla, show bitter words from both men but also Tripp saying he had "never made a threat." Tesla's claims, he said, are "absurd! Insane is a better word."

Tesla sued a former employee Wednesday for allegedly hacking the automaker's computer systems and stealing company secrets, shedding light on what chief Elon Musk had suggested was the work of a secretive internal saboteur. Tesla attorneys wrote in their lawsuit that Martin Tripp, a former technician at the company's Gigafactory battery plant in Nevada, wrote software to aid in an elaborate theft of several gigabytes of confidential data, including photos and video of Tesla's manufacturing systems. The firm's attorneys said Tripp worked at Tesla from October to last week, when company investigators confronted him with evidence. Tripp, attorneys wrote, also gave journalists false information about the company, including claims that defective batteries had been used in Tesla's Model 3 sedans. The court file did not name an attorney for Tripp, who could not be located.

Next week, I'll be at Think 2018 in Las Vegas. As I share this, several of my clients are deciding if they should make larger investments in data science and machine learning over the next 6-18 months. I believe data science and machine learning are the dynamic duo that are going to transform how we do business and how we lead our lives. I'll talk about machine learning after I attend the IBM Think 2018 conference. As an external technology advisor, I'm paid to help my clients better understand where they should invest, sometimes how much, and, in several cases, who should lead their pilot programs.

How can machine learning (ML) provide your business with a competitive edge today, and market leadership over time? When I attend technology conferences I ask my clients what they want to learn more about. Every year, I take this information and help them grow their markets, revenue, and profits. I've been doing this for many years. This year I was invited by IBM to attend Think 2018 as their guest.

Next week, I'll be at Think 2018 in Las Vegas. As I share this, several of my clients are deciding if they should make larger investments in data science and machine learning over the next 6-18 months. I believe data science and machine learning are the dynamic duo that are going to transform how we do business and how we lead our lives. I'll talk about machine learning after I attend the IBM Think 2018 conference. As an external technology advisor, I'm paid to help my clients better understand where they should invest, sometimes how much, and, in several cases, who should lead their pilot programs.

How can machine learning (ML) provide your business with a competitive edge today, and market leadership over time? When I attend technology conferences I ask my clients what they want to learn more about. Every year, I take this information and help them grow their markets, revenue, and profits. I've been doing this for many years. This year I was invited by IBM to attend Think 2018 as their guest.

As we look at 2018 and predict changes on the way, they coalesce under a singular point of view: this year is all about bringing intelligence to our data-science processes. Last year we created dashboards and started asking how to turn data into real insights that we could act on; this year we'll see changes that enable us to build and deploy intelligent applications. The hottest topic in financial news this year--and most of last year--is Bitcoin. With the CBOE and CME launching Bitcoin futures in December 2017, the currency has sparked many academic conversations, but we'll see practical repercussions beyond rampant cryptocurrency speculation. The year 2018 will be when blockchain goes mainstream.