Summary of “Habits, Not Goals, Will Bring You Success”

Victor Hugo’s dramatic trick to stop procrastinating The daily habit that made Jerry Seinfeld such a success The single behavior that often separates top performers from the pack.
Where would the wanting [come] in on some of these habits that we know we need to do, but we don’t really like to do?
Most people want to have clean teeth, or want to be in shape, or want to be calm and not stressed, or want to succeed in the workplace.
For a long time, my mom wanted to be in shape, but she didn’t like working out in public, so the idea of going to a YMCA or a gym wasn’t appealing to her.
Jay: Sometimes wanting doesn’t have to be, “I want to go to Alaska on vacation.” It can also be, “Oh, I know I need to do that.”
For a long time, I would buy apples and put them in the crisper in the bottom of my fridge, and they would sit there for three weeks and go bad. I was like, “I want to eat fruit. I want to be healthy, and I’m just wasting money.” [So] I bought a larger bowl and set that on the counter.
There are a lot of ways to be average, but if you want to be extraordinary, the system is the surest way to get there.
Of course you want to keep your chain going for as long as you can, but at some point, your kid’s going to get sick, or you’re going to get sick, or you’re going to go on vacation, and you’re going to slip.

The orginal article.

Summary of “How to Avoid Focus-stealing Traps”

According to Daniel Goleman, a leading psychologist and expert in attention science, and author of Focus: The Hidden Driver of Excellence.
“Getting a job done well requires applying concentration while creative insights flow best when we are in a loose, open awareness.” In other words, while focus involves how we’re casting our attention, different modes.
The most successful of us develop and balance out this “Triad of awareness,” because “a failure to focus inward leaves you rudderless, a failure to focus on others renders you clueless, and a failure to focus outward may leave you blindsided.”
Inner focus involves developing self-awareness, or listening to our inner voice.
How do we successfully use our willpower? Goleman says there are three w.a.y.s. Voluntarily disengage our focus from what’s distracting us Work toward resisting distraction so that we don’t gravitate back to it.
Practice training your “Focus muscle.”
“The ability to focus is like a mental muscle. The more we work it out, the stronger it [becomes].”
Focus on your breath Recognize that your thoughts have drifted off Let go of your current thought Focus on your breath again and stay there.

The orginal article.

Summary of “North Dakota’s Norway Experiment – Mother Jones”

Late one night in October 2015, North Dakota prisons chief Leann Bertsch met Karianne Jackson, one of her deputies, for a drink in a hotel bar in Oslo, Norway.
The Norway sojourn was the brainchild of Donald Specter, executive director of the Prison Law Office, a California public-interest law firm.
Fred Patrick, director of the Center on Sentencing and Corrections at the Vera Institute of Justice, cites the nation’s staggering recidivism rate-77 percent of inmates released from state prisons are rearrested within five years.
Of North Dakota, drivers are greeted by billboards advising people to “Be Nice” or “Be Kind.” Fittingly, the state’s incarceration rate of 240 prisoners per 100,000 residents is among the lowest in America, where the national average is 670.
North Dakota’s prison population of about 1,821 is less than half that of its neighbor to the south.
The number of inmates in North Dakota prisons has increased by 28 percent since the end of 2011.
Like Norway, it is sparsely populated and relatively homogeneous-race-based prison gangs hold little sway here.
In North Dakota, where falling oil and grain prices have put the state government in belt-tightening mode, I watched Bertsch shame state senators for the tough new criminal penalties they’d enacted.

The orginal article.

Summary of “Technology Is Biased Too. How Do We Fix It?”

“Northpointe answers the question of how accurate it is for white people and black people,” said Cathy O’Neil, a data scientist who wrote the National Book Award-nominated “Weapons of Math Destruction,” “But it does not ask or care about the question of how inaccurate it is for white people and black people: How many times are you mislabeling somebody as high-risk?”.
Biased data can create feedback loops that function like a sort of algorithmic confirmation bias, where the system finds what it expects to find rather than what is objectively there.
“Part of the problem is that people trained as data scientists who build models and work with data aren’t well connected to civil rights advocates a lot of the time,” said Aaron Rieke of Upturn, a technology consulting firm that works with civil rights and consumer groups.
There are similar concerns about algorithmic bias in facial-recognition technology, which already has a far broader impact than most people realize: Over 117 million American adults have had their images entered into a law-enforcement agency’s face-recognition database, often without their consent or knowledge, and the technology remains largely unregulated.
“We’re handing over the decision of how to police our streets to people who won’t tell us how they do it.”
“A lot of these algorithmic systems rely on neural networks which aren’t really that transparent,” said Professor Alvaro Bedoya, the executive director of the Center on Privacy and Technology at Georgetown Law.
Once we move beyond the technical discussions about how to address algorithmic bias, there’s another tricky debate to be had: How are we teaching algorithms to value accuracy and fairness? And what do we decide “Accuracy” and “Fairness” mean? If we want an algorithm to be more accurate, what kind of accuracy do we decide is most important? If we want it to be more fair, whom are we most concerned with treating fairly?
Advocates say the first step is to start demanding that the institutions using these tools make deliberate choices about the moral decisions embedded in their systems, rather than shifting responsibility to the faux neutrality of data and technology.

The orginal article.

Summary of “The Business of Artificial Intelligence”

Jeff Wilke, who leads Amazon’s consumer business, says that supervised learning systems have largely replaced the memory-based filtering algorithms that were used to make personalized recommendations to customers.
Unsupervised learning systems seek to learn on their own.
Such possibilities lead Yann LeCun, the head of AI research at Facebook and a professor at NYU, to compare supervised learning systems to the frosting on the cake and unsupervised learning to the cake itself.
In reinforcement learning systems the programmer specifies the current state of the system and the goal, lists allowable actions, and describes the elements of the environment that constrain the outcomes for each of those actions.
Business models need to be rethought to take advantage of ML systems that can intelligently recommend music or movies in a personalized way.
In particular, machine learning systems often have low “Interpretability,” meaning that humans have difficulty figuring out how the systems reached their decisions.
If a system learns which job applicants to accept for an interview by using a data set of decisions made by human recruiters in the past, it may inadvertently learn to perpetuate their racial, gender, ethnic, or other biases.
A second risk is that, unlike traditional systems built on explicit logic rules, neural network systems deal with statistical truths rather than literal truths.

The orginal article.

Summary of “The Truth about How Creativity Really Works”

“Maybe that’s enlightenment enough: to know that there is no final resting place of the mind; no moment of smug clarity. Perhaps wisdomis realizing how small I am, and unwise, and how far I have yet to go.” - Anthony BourdainOn March 20, 1997, a quiet crowd settled into the Old Post Chapel at Arlington National Cemetery for the memorial service of Colonel John Boyd.John Boyd was a fighter pilot.
Boyd’s work focused on how the military could adapt from the highly centralized 19th and early 20th century wars between large nation states to the reality that began for the U.S. with Vietnam: a guerilla-style war between incumbent central governments and insurgent guerilla forces.
Snowmobiling, Boyd’s term, is how Creativity really happens.
The tendency is that once you create a coherent conceptual system that explains reality, you turn inwards to refine the system within itself and work out the details.
According to Gödel, you can’t understand a system from within that system.
Any self-consistent system cannot be proven to be self-consistent from within that system.
In order to determine the consistency of a new system, we need to discover another system beyond it.
Any attempts to prove the system is consistent and matches up with reality actually generates even more disorder and uncertainty, and it makes the conceptual system less useful for increasing your capacity for independent action.

The orginal article.

Summary of “Every New York City Subway Line Is Getting Worse. Here’s Why.”

Subway delays have become a frustrating fact of life in New York City.
Large crowds slow down trains, which creates more crowding in a vicious circle that takes hours to unwind during every rush.
How exactly does overcrowding cause delays? Subway officials say trains slow down as they face an onslaught of passengers at each station.
The delay reverberates down the line as a queue of trains behind it backs up.
A train is considered late if it reaches the final station on the line more than five minutes after its scheduled arrival time.
“The only truly effective way to address crowding on the subway is to run more trains,” said John Raskin, the executive director of the Riders Alliance, an advocacy group.
What the system needs is more capacity: trains that run more frequently and new lines to carry the growing population.
Another subway rider, KC Brown, recently found herself in a situation that is sadly familiar to most New Yorkers: The train doors closed in her face and when they opened, the train was too full to get on.

The orginal article.

Summary of “How Chaos Cures Metaphysics”

Given two real numbers, we know how to add, subtract, multiply, and divide them.
We know how to add, subtract, multiply, and divide complex numbers.
Just as one can construct the complex numbers from pairs of real numbers, so too can one construct the quaternions from pairs of complex numbers.
Let c1 = r1 + r2i and c2 = r3 + r4i be complex numbers; then we can construct a quaternion as q = c1 + c2j where j is a special number.
So while the complex numbers are comprised of two real numbers, the quaternions are comprised of four real numbers.
Rather than looking at the real numbers as central and the octonions as strange larger number systems, think of the octonions as fundamental and all the other number systems as just special subsets of octonions.
Let us turn this view on its head. Rather than looking at the real numbers as central and the octonions as strange larger number systems, think of the octonions as fundamental and all the other number systems as just special subsets of octonions.
Let us explore how we can derive all the properties of the number systems that we are familiar with.

The orginal article.

Summary of “A Cyberattack ‘the World Isn’t Ready For'”

What Mr. Ben-Oni had witnessed was much worse, and with all eyes on the WannaCry destruction, few seemed to be paying attention to the attack on IDT’s systems – and most likely others around the world.
In IDT’s case, attackers used DoublePulsar to steal an IDT contractor’s credentials.
Mr. Ben-Oni learned of the attack only when a contractor, working from home, switched on her computer to find that all her data had been encrypted and that attackers were demanding a ransom to unlock it.
Attackers entered IDT’s network at 6 p.m. on Saturday on the dot, two and a half hours before the Sabbath would end and when most of IDT’s employees – 40 percent of whom identify as Orthodox Jews – would be off the clock.
With the exception of Amazon, which found that some of its customers’ computers had been scanned by the same computer that hit IDT, no one had seen any trace of the attack before Mr. Ben-Oni notified them.
‘No One Is Running Point’Since the Shadow Brokers leaked dozens of coveted attack tools in April, hospitals, schools, cities, police departments and companies around the world have largely been left to fend for themselves against weapons developed by the world’s most sophisticated attacker: the N.S.A.A month earlier, Microsoft had issued a software patch to defend against the N.S.A. hacking tools – suggesting that the agency tipped the company off to what was coming.
For his part, Mr. Ben-Oni said he had rolled out Microsoft’s patches as soon as they became available, but attackers still managed to get in through the IDT contractor’s home modem.
There are now YouTube videos showing criminals how to attack systems using the very same N.S.A. tools used against IDT, and Metasploit, an automated hacking tool, now allows anyone to carry out these attacks with the click of a button.

The orginal article.

Summary of “Meet the Chinese Finance Giant That’s Secretly an AI Company”

The company boasts more than 450 million active users compared to about 12 million for Apple Pay.
Ant’s progress will be significant to the future of the financial industry beyond China, including in the U.S., where the company is expanding its interests.
A spokesperson for the company says it hasn’t brought Alipay to the U.S. because existing financial systems provide less of an opportunity.
Yuan Qi, a vice president and chief data scientist at Ant, says the company’s AI research is shaping its growth.
Qi speaks a mile a minute, which seems appropriate given how quickly his company seems to be moving.
Dressed in a smart shirt and dress pants on a sweltering afternoon in Beijing this May, shortly after giving a speech at a major AI conference, Qi explained that the company considers itself not a “Fintech” business but a “Techfin” one, due to the importance of technology.
The company has invested almost $1 billion in Paytm, an Indian payments company.
Last year the company acquired EyeVerify, a U.S. company that makes eye recognition software.

The orginal article.