[Link] Crazy New Ideas

Paul Graham on why he asks questions – rather than voice his opinions – when someone who’s a domain expert comes up with crazy new ideas

Few understand how feeble new ideas look when they first appear. So if you want to have new ideas yourself, one of the most valuable things you can do is to learn what they look like when they’re born. Read about how new ideas happened, and try to get yourself into the heads of people at the time. How did things look to them, when the new idea was only half-finished, and even the person who had it was only half-convinced it was right?

But you don’t have to stop at history. You can observe big new ideas being born all around you right now. Just look for a reasonable domain expert proposing something that sounds wrong.

Tech Tales

Jack Clark’s Tech Tales need a section all on their own. From Import AI 240

Tell me the weight of the feather and you will be ready
[A large-scale AI training infrastructure, 2026]

When you can tell me precisely where the feather will land, you will be released, said the evaluator.
‘Easy’, thought the baby artificial intelligence. ‘I predict a high probability of success’.

And then the baby AI marked the spot on the ground where it thought the weather would land, then told its evaluator to drop the feather. The feather started to fall and, buffeted by invisible currents in the air and their interplay with the barbs and vanes of the feather itself, landed quite far from where the baby AI had predicted.

Shall we try again? asked the evaluator.
‘Yes,’ said the baby. ‘Let me try again’.

And then the baby AI made 99 more predictions. At its hundredth, the evaluator gave it its aggregate performance statistics.
‘My predictions are not sufficiently accurate,’ said the baby AI.
Correct, said the evaluator. Then the evaluator cast a spell that put the baby AI to sleep.
In the dreams of the baby AI, it watched gigantic feathers made of stone drop like anvils into the ground, and tiny impossibly thin feathers made of aerogel seem to barely land. It dreamed of feathers falling in rain and in snow and in ice. It dreamed of feathers that fell upward, just to know what a ‘wrong’ fall might look like.

When the baby woke up, its evaluator was there.
Shall we go again, said the evaluator.
‘Yes,’ said the baby, its neurons lighting up in predictive anticipation of the task, ‘show me the feather and let me tell you where it will land’.
And then there was a feather. And another prediction. And another comment from its evaluator.

In the night, the baby saw even more fantastic feathers than the night before. Feathers that passed through hard surfaces. Feathers which were on fire, or wet, or frozen. Sometimes, multiple feathers at once.

Eventually, the baby was able to roughly predict where the feather would fall.
We think you are ready, said the evaluator to the feather.
Ready for what? said the baby.
Other feathers, said the evaluator. Ones we cannot imagine.
‘Will I be ready?’ said the baby.
That’s what this has been for, said the evaluator. We believe you are.
And then the baby was released, into a reality that the evaluator could not imagine or perceive.

Somewhere, a programmer woke up. Made coffee. Went to their desk. Checked a screen: “`feather_fall_pred_domain_rand_X100 complete“`.

Things that inspired this story: Domain randomization; ancient tales of mentors and mentees; ideas about what it means to truly know reality

[Link]: A Checklist to Find Your Way Back

Some wonderful questions to ask any time I suppose.

  • What’s been eliminated or greatly reduced in my life that I really miss and want to add back? How much of that do I want to add back?
  • What’s been eliminated or greatly reduced in my life that I don’t really miss and want to keep it that way?
  • What have I started doing during the pandemic year that has been beneficial and that I want to keep doing? How much of that do I want to do?
  • What have I been doing during the pandemic year that’s draining and not sustainable over the long-run that I want to stop doing?
  • How and when should I continue to capture the value of meeting virtually without the added overhead of travel time and expense?
  • What have I stopped doing during the pandemic year that has improved the quality of my life and work?
  • What really makes me happy and feeling like I’m really living and leading at my best?


[Link]: Allowing Ourselves to Feel Joy

Leo Babauta has a suggestion I think we can all try.

Joy and wonder are two emotions we shut down, for so many reasons: it’s safe, it’s not allowed, we’re worried about ourselves, we’re stressed. But wouldn’t we like to live a life that has joy every day? That feels wonder at the incredibleness of this world and the richness of humanity?



[Link] Touch is a Language We Cannot Afford to Forget

At the times in our lives that we are most fragile, we need touch more than ever. From everything we know about social touch, it needs to be promoted, not inhibited. We need the nuance to recognise its perils, but avoiding touch entirely would be a disaster. The pandemic has given us a glimpse of what life would look like without touch. The fear of the other, of contamination, of touch has allowed many of us to realise how much we miss those spontaneous hugs, handshakes and taps on the shoulder. Physical distancing leaves invisible scars on our skin. Tellingly, most people mention ‘hugging my loved ones’ as one of the first things they want to do once the pandemic is over.

Read Laura Crucianelli’s essay in full here

[Link] Diversity & Inclusion has a Polarisation Problem

A thoughtful essay from Lily Zheng on a thorny, polarising topic.

In this essay, I’m going to make the case that D&I workshops as we know it are designed to be unwelcome for people who haven’t bought in to their premise. I’ll start by diving into the most common assumptions embedded into today’s D&I programming. I’ll show how these assumptions can influence D&I programming in ways that can unwittingly can widen the gap in knowledge among employees, create polarization and resentment, and paradoxically, undermine future efforts at inclusion. Finally, I’ll present an alternative framework for D&I programming and explore the implications of adopting it.

HT to my AltMBA tribe member Aray M. Till

[Link] Why is the World So Beautiful

This is a fascinating conversation with Prof. Robin Wall Kimmerer, a plant ecologist, writer, and Distinguished Teaching Professor at the SUNY College of Environmental Science and Forestry in Syracuse, NY and a member of the Potawatomi First Nation.

“Mosses have this ability, rather than demanding a lot from the world,  they’re very creative in using what they have, rather than reaching for what they don’t have,” Kimmerer told Tapestry.

“When there are limits, the mosses say, ‘Let’s be quiet for a while. Abundance, openness, water, will return.  We’ll wait this out.'”

Listen to this conversation

HT John Hagel

[Link] The Future of Analytics may be low/no code… at first

George Mount doesn’t buy the “point-and-click” story about analytics tools, making everyone an analyst.  Innovation in this space – like all others – happens in waves, & it’s happened before.  With several examples, including for Power Query, he recommends

data professionals learn a bit about coding. Maybe not every data solution requires it; that’s fine. But given where we’ve come from in the data world, I’m not inclined to say that the future is all low and no code.