Listening Better

Source: Fast Company, Mar 2017


“Listening is good, but the intent has to be curiosity, not generosity. True dialogue does not happen when we pretend to listen, and it certainly cannot happen if we are not listening at all.”

“Each day, ask yourself, ‘What am I going to be curious about?’” says Gregersen.


While you can’t control someone else’s listening habits, you can control your own, and that involves quieting down your mind.

“Turn off those agendas,” says Gregersen. “Really listen to what someone else is trying to say. We need information that is disconfirming, not confirming. If we ever finish a conversation and learned nothing surprising, we weren’t really listening.”


One of the simplest ways to be a better listener is to ask more questions than you give answers, says Gregersen. When you ask questions, you create a safe space for other people to give you an unvarnished truth.

“Listening with real intent means I’m going to be open to being very wrong, and I’m comfortable with that in this conversation,” says Gregersen.


Strive for a 2:1 ratio of listening to talking, says Eblin.


A number of problems interfere with people’s ability to understand accurately what another person is trying to communicate, says Adam Goodman, director of the Center for Leadership at Northwestern University.

“Am I anticipating what the other person is about to say? Do I agree or disagree with what’s being said? Maybe I’m agreeing too quickly and, upon reflection, I’d find myself disagreeing later?” he asks. “Put simply, there’s more opportunity to misunderstand then there is to actually understand.”

implement a process called active listening. “It’s been around for a long time, and works if done right,” says Goodman. The basic concept is repeating back to the speaker what you heard. If the speaker agrees that what you heard is what he or she intended to say, you can move on. If not, the speaker needs to reword their statement until the listener really does understand.


The most difficult component of listening effectively is waiting for a period at the end of a sentence before formulating a reply, says Leslie Shore, author of Listen to Succeed.

We all require self-focus, but leaders who make a difference are the ones who know the purpose is bigger than themselves, says Gregersen.

Solo and Group Creativity

Source: Fast Company, Mar 2017

The part of our brain that usually leads to our most creative ideas is called the “default mode network.” It’s what gives us the ability to relate seemingly unrelated concepts, to create novel connections, to see patterns where others see noise. This network works best when we daydream, when we’re quiet, when we’re involved in mindless tasks and are just staring off into space, not really seeing anything in the outside world. It works best when we sleep. In other words, when we’re alone.

It’s this part of the brain that the introvert camp (Cain et al.) tend to study most intensively and point to as the source of true creative inspiration. But it doesn’t work alone.

The extroverts (Sawyer and company) have a solid argument, too. One of the ways the default mode network functions is by being stimulated with new ideas. When you space out, your hippocampus starts to build new memories out of the raw material of your experiences. And when it does that, it has a tendency to throw random memory shards into the default mode network. These random shards of new memories act like sparks to the kindling of your default network, lighting the fire of what ultimately becomes a creative breakthrough.

And these new ideas most often become apparent to us in conversation with others, in a lively chat at the café, or in an argument in a bar.

the answer is that human beings are most creative when we get time by ourselves and then time with one another. The way to maximize creative potential is to flow between being alone and being in a group, and back again. When you’re alone, you’re essentially building a woodpile in your brain. Then, when you join a group, you’re igniting a shower of sparks that might light it up. Of course, you sometimes need to go be alone again in order to let the sparks you’ve started generating get close enough to the wood.

Alternating between solo time and collaboration seemed to encourage more creativity than either approach exclusively–very likely because that’s how our brains are built.

How can you put this into practice? Try brainstorming like this:

  1. Grab some large sticky notes and have everyone write down their ideas, one per note, for 10 minutes.
  2. Have them put their ideas on the wall, and everyone gets three minutes to look them over.
  3. When time’s up, everyone goes back and writes new ideas for five more minutes.
  4. The stickies go up, and everyone looks at them for two minutes.
  5. Then everyone goes back to being alone and writes out new ideas for just 90 seconds.
  6. The stickies go up one last time, and everyone looks at them for a final five minutes.
  7. Discuss.

You’ll be done in half an hour.

By breaking this process up into ever shortening intervals, you keep the creative energy flowing, maintain a structure, and allow everyone’s brains to hop between the two forms of thought that creativity requires. The time constraints force people to be concise and trust their instincts rather than overthink things. And on a more tactical level, Paulus discovered that by writing everything down, no one could dominate the group conversations, and no one had to wait their turn, only to forget their idea.

So the introverts and extroverts are both right, up to a point. What they really need is to sit down together and chat it out, then go be alone again, and rinse, repeat. They may find they have more in common than they’d thought–and probably more creative ideas, too.


Source: FT, Mar 2017

With its cadre of researchers, from Bayesian mathematicians to cognitive neuroscientists, statisticians and computer scientists, DeepMind has amassed arguably the most formidable community of world-leading academics specialising in machine intelligence anywhere in the world.

“What we are trying to do is a unique cultural hybrid — the focus and energy you get from start-ups with the kind of blue-sky thinking you get from academia,” says Demis Hassabis, co-founder and chief executive. “We’ve hired 250 of the world’s best scientists, so obviously they’re here to let their creativity run riot, and we try and create an environment that’s perfect for that.”

DeepMind’s researchers have in common a clearly defined if lofty mission: to crack human intelligence and recreate it artificially.

Today, the goal is not just to create a powerful AI to play games better than a human professional, but to use that knowledge “for large-scale social impact”, says DeepMind’s other co-founder, Mustafa Suleyman, a former conflict-resolution negotiator at the UN.

To solve seemingly intractable problems in healthcare, scientific research or energy, it is not enough just to assemble scores of scientists in a building; they have to be untethered from the mundanities of a regular job — funding, administration, short-term deadlines — and left to experiment freely and without fear.

“If you look at how Google worked five or six years ago, [its research] was very product-related and relatively short-term, and it was considered to be a strength,” Hassabis says. “[But] if you’re interested in advancing the research as fast as possible, then you need to give [scientists] the space to make the decisions based on what they think is right for research, not for whatever kind of product demand has just come in.”

DeepMind’s three appearances in quick succession in Nature, along with more than 120 papers published and presented at cutting-edge scientific conferences, are a mark of its prodigious scientific productivity.

Our research team today is insulated from any short-term pushes or pulls, whether it be internally at Google or externally. We want to have a big impact on the world, but our research has to be protected,” Hassabis says. “We showed that you can make a lot of advances using this kind of culture. I think Google took notice of that and they’re shifting more towards this kind of longer-term research.”

DeepMind has six more early manuscripts that it hopes will be published by Nature, or by that other most highly regarded scientific journal, Science, within the next year. “We may publish better than most academic labs, but our aim is not to produce a Nature paper,” Hassabis says. “We concentrate on cracking very specific problems. What I tell people here is that it should be a natural side-effect of doing great science.”

Structurally, DeepMind’s researchers are organised into four main groups with titles such as “Neuroscience” or “Frontiers” (a group comprising mostly physicists and mathematicians who test the most futuristic theories in AI).

Every eight weeks, scientists present what they have achieved to team leaders, including Hassabis and Shane Legg, head of research, who decide how to allocate resources to the dozens of projects. “It’s sort of a bubbling cauldron of ideas, and exploration, and testing things out, and finding out what seems to be working and why — or why not,” Legg says.

Projects that are progressing rapidly are allocated more manpower and time, while others may be closed down, all in a matter of weeks. “In academia you’d have to wait for a couple of years for a new grant cycle, but we can be very quick about switching resources,” Hassabis says.

This organisational culture has been a magnet for some of the world’s brightest minds. Jane Wang, a cognitive neuroscientist at DeepMind, used to be a postdoctoral researcher at Northwestern University in Chicago, and says that she was attracted to DeepMind’s clear, social mission. “I have interviewed at other industry labs, but DeepMind is different in that there isn’t pressure to patent or come up with products — there is no issue with the bottom line. The mission here is about being curious,” she says.

For Matt Botvinick, neuroscience team lead, joining DeepMind was not just a career choice but a lifestyle change too. The former professor who led Princeton University’s Neuroscience Institute continues to live in the US, where his wife is a practising physician, and commutes to DeepMind’s labs in London every other week. “At Princeton, I was surrounded by people I considered utterly brilliant and had no interest in working in an environment any less focused on primary scientific questions,” he says. “But I couldn’t resist the opportunity to come here because there is something qualitatively new going on, both with the scale and the spirit of ideas.”

What sets DeepMind apart from academic labs, he says, is its culture of cross-disciplinary collaboration, reflected in the company’s hiring of experts, who can cut across different domains from psychology to deep learning, physics or computer programming.

“In a lot of research institutions, things can become siloed. Two neighbouring labs could be working on similar topics but never exchange and pool information,” Botvinick says. “Unlike any place I’ve ever experienced before, all conversations are enhanced rather than undermined by differences in background.”

Google Supersonic – Transcribe Voice to Text & Emoji!

Source: The Next Web, Mar 2017

Supersonic is a messaging app that relies almost exclusively on voice input: hold down the mic button to dictate a message, and you’ll see it transcribed into a text and emoji-studded message in your one-on-one or group conversation. Your contacts can also play back your audio message, and it’ll disappear once it’s been heard.


Read Widely and Voraciously

Source: Keith Sawyer blog,  Mar 2017

I aggressively curate and monitor the notifications I receive about newly published papers, and I read those that strike my interest, even if they’re not directly related to my research. Perhaps the biggest question is why I make the effort. The short answer is that I read widely to prepare myself for whatever might come along in the lab. My biggest fear is the one that got away, the important discovery that I missed because I couldn’t see it for what it was.

Reading only in my subdiscipline would limit the kinds of connections I can draw.

Time and again, strange observations in the lab reminded me of a paper I had read in some far-out journal, or a seemingly irrelevant visiting speaker’s talk suddenly led me to understand a result that had been bugging me for weeks.

My advice: Read widely and voraciously.

One of the key lessons is that it’s not easy. It takes time and effort. It’s easier to stay focused on one thing, to work on what everyone else is working on, to read all of the same articles that your colleagues are reading. But creativity? You’ve got to work at that, to do things your colleagues aren’t.


Source: Washington Post, Jul 2015

What happens in the economics of Star Trek is that automation has taken over.

If you are in economics, what you are thinking about is basically the way society works under scarcity. And it’s hard to understand the way society works under scarcity unless and until you actually spend a bit of time understanding how a society might work without scarcity. And that’s exactly what we have in Star Trek.

Manu Saadia:

There’s no longer any necessity to work to sustain oneself. Machines complement our work as humans and allow us to escape the most dreadful effects of scarcity. Poverty, hunger, all that.

Instead of working to become more wealthy, you work to increase your reputation. You work to increase your prestige. You want to be the best captain or the best scientist in the entire galaxy. And many other people are working to do that, as well. It’s very meritocratic, similar to my friends who are mathematicians or scientists. And it’s extremely hard.

The nature of work is no longer tied to conspicuous consumption, or the necessity to actually feed yourself or to make money. Work has become something that allows you to increase your reputation, or your reputational capital. That’s how it’s depicted in the series.

Related Reading: InkShares, date indeterminate

In Trek’s universe, most if not all of the real-world conditions that drive economic behaviors essentially disappear. In Star Trek, currency has become obsolete as a medium for exchange. Labor cannot be distinguished from leisure. 

A world where evenly distributed cornucopia is both the norm and the policy profoundly changes its inhabitants. Just like money, the compulsion to work to ensure one’s survival has simply vanished.

competition among people is completely transformed. Reputation and honors, the esteem and recognition of one’s peers, replace economic wealth as public markers of status. But these are largely optional, as there are no material penalties or disincentives for those who do not seek nor attain higher status.


Peak Ages

Source: Business Insider, Mar 2017