The Atlantic: “The Best Time-Management Advice is Depressing but Liberating”

Pinsker: And yet people frequently postpone their time-intensive passion projects, like, say, working on a novel, because they have this sense that they’ll get around to them eventually. Psychologically, what gets in the way of us doing big things that we care about?

Burkeman: We all feel overwhelmed by lots of little stuff we feel we have to do, and we have these big things that we’d like to do. But to do them, it feels like you need long stretches of focus when all the other little stuff is out of the way—it feels like it would be selling the project short to try beginning to write your novel in 20 minutes on a subway commute, for example. So instead, you decide to go through your email and deal with other outstanding things—but for the reasons we’ve discussed, the time never comes when you clear all that [out of the way].

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If I’m working on a difficult article, it’s not like I’m really happy doing it but Twitter comes and takes me away from it. Instead, I run away to Twitter because the article is challenging me and causing me to experience uncomfortable emotions, and Twitter promises the opposite.

So I think the reason that we seek distraction is that working on stuff that we care about is often scary. It brings us into contact with all the ways in which we’re limited—our talents might not be up to what we’re trying to do, and we can’t control how things will unfold. If you’re writing a difficult article, you don’t get to know in advance that it’s going to come out well, which can make you feel constrained and imprisoned by reality. Meanwhile, the internet feels limitless, like you’re an all-powerful consciousness surfing the unlimited waves of the web and social media. It’s very relieving.

Joe Pinsker

Short article, but the advice is sound and realistic – maybe that’s what makes it ‘depressing’ for the person who wrote the title: the key to better time management is not becoming more efficient at getting tasks done, but instead selecting which projects are personally important and prioritizing these over more pressing, but ultimately less rewarding things. Accept that time is in fact limited, and work within those constraints, not struggle fruitlessly against them.

Popular Science: “Why Spotify’s music recommendations always seem so spot on”

Spotify has even been testing a neural network called CoSeRNN that weighs certain features such as past listening history and current context to suggest song recommendations that suit the moment.

As for testing whether music mirrors certain human characteristics, they published results from a small survey-based study last December to see how music preference matched up to certain personality traits. In a blog post, the researchers noted that there appeared to be some correlations between personality and music genre preference. Unsurprisingly, people who identified as “open to new experiences” checked out Discover Weekly more; those who identified them as extroverts listened more to playlists that other people had created, while those who identified as introverts preferred to delve into a newly discovered artist’s discography.

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To stay ahead of our changing preferences, and keep their recommendations fresh, Spotify also needs to be able to understand how what we like can evolve over time. Earlier this year, researchers there built a model based on a dataset of 100,000 Spotify users who were continuously active from 2016 to 2020. They looked at the entire streaming history of every user, grouped their music into “micro-genres”, and mapped them across time. What they came up with was a connected graph that illustrated the transitions between different genres of music. As an example, their model suggested that to go from liking “EDM” to “nu jazz” or “gospel”, users were likely to pass through a phase of liking “tropical house”, which is chill but upbeat electronic music.

Charlotte Hu

Interesting overview of the various research and data crunching powering Spotify’s recommendations algorithm. I can’t say that I noticed some super-relevant suggestions from the app, but I admit that its autogenerated playlists (artist radio’s and genre mixes) are generally well tuned and enjoyable. The insights into microgenres have been put to good use in the Spotify Wrapped yearly recaps as well. I find these fascinating, and apparently so do a lot of other people (who wouldn’t want to feel unique and special?), as in 2021 we got a second similar event in June, Only You. Before then, I never heard of the music genre ‘Morna’, but apparently I am a regular listener.

Quanta Magazine: “What Does It Mean for AI to Understand?”

These schemas were the subject of a competition held in 2016 in which the winning program was correct on only 58% of the sentences — hardly a better result than if it had guessed. Oren Etzioni, a leading AI researcher, quipped, When AI can’t determine what ‘it’ refers to in a sentence, it’s hard to believe that it will take over the world.

However, the ability of AI programs to solve Winograd schemas rose quickly due to the advent of large neural network language models. A 2020 paper from OpenAI reported that GPT-3 was correct on nearly 90% of the sentences in a benchmark set of Winograd schemas. Other language models have performed even better after training specifically on these tasks. At the time of this writing, neural network language models have achieved about 97% accuracy on a particular set of Winograd schemas that are part of an AI language-understanding competition known as SuperGLUE. This accuracy roughly equals human performance. Does this mean that neural network language models have attained humanlike understanding?

Melanie Mitchell

I mean, the answer to this question is obviously no. It’s one thing to statistically infer the right answers to increasingly convoluted tests, and quite another to understand the meaning of the questions. In some ways, the machine learning approach to passing this linguistic test reminds me of ‘Dieselgate’: a system designed not to perform a proper task, but instead to fulfil requirements in a predefined scenario. In other words, you can always find a way to cheat when you know the questions in advance. The AI model may incorporate more and more examples into its training data, but that doesn’t mean it can spontaneously understand the concepts behind sentences and perform equally well in a random situation.

Ars Technica: “The secret Uganda deal that has brought NSO to the brink of collapse”

A few months after the initial approach, NSO’s chief executive, Shalev Hulio, landed in Uganda to seal the deal, according to two people familiar with NSO’s East Africa business. Hulio, who flew the world with the permission of the Israeli government to sell Pegasus, liked to demonstrate in real time how it could hack a brand-new, boxed iPhone.

The eventual business was small for NSO. A person familiar with the transaction said it brought in between $10 million and $20 million, a fraction of the $243 million that Moody’s estimated the privately owned NSO made in revenues in 2020.

But about two years after the sales pitch, someone deployed Pegasus to try to hack the phones of 11 American diplomats and employees of the US embassy in Uganda, according to two US officials, who spoke after notifications were sent out by Apple when the iPhone maker discovered and closed a flaw in its operating system in November.

It is not clear who tried to hack the US citizens. Uganda’s neighbor, Rwanda, had also been using Pegasus to hack phones inside Uganda, but the revelation shocked the US. NSO has always told its customers that US phone numbers are off-limits. In this case, all 11 targets were using Ugandan numbers but had Apple logins using their State Department emails, according to the two US officials.

Mehul Srivastava

A story about smartphone security at first glance, to me it blatantly exposes the ingrained hypocrisy of US foreign policy. Earlier this summer, an investigative report revealed how NSO’s Pegasus spyware was used to target tens of thousands of prominent personalities from all over the world (with the exception of the United States). The US response at the time: crickets… The same software was apparently used by the Polish government to hack an opposition senator, and the list of examples certainly wouldn’t stop here.

The Verge: “Microsoft PowerToys get a Windows 11 UI, universal mute, and find my mouse feature”

Alongside the design tweaks, PowerToys is also getting two new features with this 0.49 version update. Video Conference Mute debuts with this release, a feature that lets you mute your microphone or disable your webcam globally across Windows 10 or Windows 11.

You can bind Video Conference Mute to a keyboard shortcut, and pick the webcam and microphone you’d like to disable. There’s even a toolbar that appears when a webcam or microphone is in use. Microsoft had been planning to launch Windows 11 with its own universal microphone mute button, but this feature didn’t make the release and should be coming at some point in the future.

Tom Warren

I have paid little attention to PowerToys since the initial release because I didn’t find much use for its range of small utilities, with the exception of Image Resizer – it’s perplexing how after decades of development Windows doesn’t have such a basic feature built-in, and starting the Photos app for a simple resizing seems excessive. But the addition of Video Conference Mute suddenly made it a lot more useful, especially since I was able to install PowerToys on my current work laptop. The company is using Teams and Zoom in parallel, so it’s easier to remember a single keyboard shortcut for muting your microphone. On top of that, this utility can mute/unmute while the conference app is not in focus, so you can continue working during the meeting if you choose to, and quickly get back into the conversation when needed without scrambling to return to the right window and click the right button.

The Guardian: “How big tech is dragging us towards the next financial crash”

No matter what the Silicon Valley giants might argue, ultimately, size is a problem, just as it was for the banks. This is not because bigger is inherently bad, but because the complexity of these organisations makes them so difficult to police. Like the big banks, big tech uses its lobbying muscle to try to avoid regulation. And like the banks, it tries to sell us on the idea that it deserves to play by different rules.

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I began digging for more on the topic, and about two years later, in 2018, I came across a stunning Credit Suisse report that both confirmed and quantified the idea. The economist who wrote it, Zoltan Pozsar, forensically analysed the $1tn in corporate savings parked in offshore accounts, mostly by big tech firms. The largest and most intellectual-property-rich 10% of companies – Apple, Microsoft, Cisco, Oracle and Alphabet (Google’s parent company) among them – controlled 80% of this hoard.

According to Pozsar’s calculations, most of that money was held not in cash but in bonds – half of it in corporate bonds. The much-lauded overseas “cash” pile held by the richest American companies, a treasure that Republicans under Trump had cited as the key reason they passed their ill-advised tax “reform” plan, was actually a giant bond portfolio. And it was owned not by banks or mutual funds, which typically have such large financial holdings, but by the world’s biggest technology firms. In addition to being the most profitable and least regulated industry on the planet, the Silicon Valley giants had also become systemically crucial within the marketplace, holding assets that – if sold or downgraded – could topple the markets themselves. Hiding in plain sight was an amazing new discovery: big tech, not big banks, was the new too-big-to-fail industry.

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As in any transaction, the party that knows the most can make the smartest deal. The bottom line is that both big-platform tech players and large financial institutions sit in the centre of an hourglass of information and commerce, taking a cut of whatever passes through. They are the house, and the house always wins.

Rana Foroohar

Smart analysis in this two-year old article. Since then, throughout the pandemic, the world economy has become even more dependent on Big Tech companies to keep things running, from video conferencing to home deliveries, cementing their status as ‘too-big-to-fail’. At the same time, some resistance to their dominance is slowly taking shape, from US presidential candidates arguing for the breakup of Big Tech to increased antitrust scrutiny, to a global initiative to set minimum tax rates for multinational corporations. I am somewhat skeptical that these measures will have the desired effects – it feels more likely that these megacompanies will slowly lose steam under the weight of their own complexity and opacity.

The Wall Street Journal: “Venezuela’s Fatal Embrace of Cuba”

Venezuela’s implosion isn’t simply the case of a Latin American basket case doing the things that basket cases do. For much of the 20th century, Venezuela was the poster child for the successful South American republic: democratic when its neighbors were despotic, prosperous when its neighbors were poor, and stable all through the vagaries of the Cold War. Venezuela carved out a niche as the country that the U.S. State Department could highlight to make its case that democracy could work in Latin America.

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That a nation once as prosperous as Venezuela could regress to this dystopian state is the first and most sobering lesson of the Venezuelan experience—proof that development gains aren’t permanent. Mismanage an economy badly enough, and the progress achieved in a generation evaporates dizzyingly fast.

Another lesson is that bad government can be as destructive as a great physical calamity. The scale of Venezuela’s implosion would suggest that the country had endured a war or a string of ghastly natural disasters. No such affliction came to Venezuela. Rather, it turns out that a country can endure wartime levels of destruction without a war—stemming from no force more destructive than the terrible policy decisions of its own government.

Moisés Naim

A cautionary tale for people who blindly assume progress is a one-way street, from poor to wealthy, from autocracy to democracy, from war to peace. There are similar signs of decay in many countries around the world: rampant inflation in Turkey, fueled by Erdoğan’s obstinance to impose his own economic policies; erosion of democratic institutions in Hungary and Poland, despite being members of the European Union; money laundering and tax evasion in London and US states from Wyoming to South Dakota. But in Venezuela, unfortunately, all these factors acted in unison to the country’s ruin.