Aaron Sorkin: As a fictional president, Trump would be "simply implausible"

Marc Tracy, Aaron Sorkin Thinks Life Still Imitates ‘The West Wing’, NYTimes, Sept. 19, 2024.

We are speaking to each other the day after the only scheduled debate between the two presidential candidates this year.

If I had scripted last night’s debate, you would have said that I made Kamala Harris fight a straw man. A lot [of shows and movies are] going to be written about this time that we’re living in now. But my prediction is that you’ll never see Donald Trump as anything but an offscreen character. You’ll see him on a television set on the news. Because he is simply implausible.

There is a movie coming out about Trump, but to your point, it is set 40 years ago.

Sebastian Stan is playing Trump in the ’70s and ’80s. I mean President Trump. Even saying it doesn’t really sound right.

It has been a pretty dramatic summer politically. What have you made of it?

Over the years, cable newscasters have used the phrase “‘West Wing’ moment,” as in: “There’s a clash over the debt ceiling. There’s not going to be a ‘West Wing’ moment.” They’ve used that to mean: an unrealistically high expectation of character triumphing over selfishness, and in the real world, there are not “‘West Wing’ moments.” I believe that the morning Biden stepped out of the race, that was a “West Wing” moment. That’s the kind of thing we write stories about.

Boats lined up on a pier

Emergence

𝗘𝗺𝗲𝗿𝗴𝗲𝗻𝗰𝗲, 𝘄𝗵𝗮𝘁 𝗶𝗻 𝘁𝗵𝗲 𝘄𝗼𝗿𝗹𝗱 𝗶𝘀 𝗶𝘁??
It would be cool to have a discussion on this one, who knows @seanmcarroll might even join??? https://t.co/VCuoabW8zf pic.twitter.com/Uhb9gD3Fz8

— Luiz Pessoa (@PessoaBrain) September 18, 2024

The most beautiful-sounding poem in English: "Kubla Khan"

Coleridge's "Kubla Khan" and honestly it's not even close. https://t.co/VBMv8KcQSC

— Adam Roberts (@arrroberts) September 16, 2024

LLMS are not fundamentally about language [Karpathy]

It's a bit sad and confusing that LLMs ("Large Language Models") have little to do with language; It's just historical. They are highly general purpose technology for statistical modeling of token streams. A better name would be Autoregressive Transformers or something.

They…

— Andrej Karpathy (@karpathy) September 14, 2024

Note that some time ago I pointed out that transformers would operate in the same way on strings of colored beads as they do on strings of word tokens.

Tree stump and water, two versions

Can we make an AI scientist?

Sam Rodriques, What does it take to build an AI Scientist? August 15, 2024:

What will it take to build an AI Scientist?

I run FutureHouse, a non-profit AI-for-Science lab where we are automating research in biology and other complex sciences. Several people have asked me to respond to Sakana's recent AI Scientist paper. However, judging from comments on HackerNews, Reddit and elsewhere, I think people already get it: Sakana’s AI Scientist is just ChatGPT (or Claude) writing short scripts, making plots, and grading its own work. It's a nice demo, but there's no major technical breakthrough. It's also not the first time someone has claimed to make an AI Scientist, and there will be many more such claims before we actually get there.

So, putting Sakana aside: what are the problems we have to solve to build something like a real AI scientist? Here’s some food for thought, based on what we have learned so far:

It will take fundamental improvements in our ability to navigate open-ended spaces, beyond the capabilities of current LLMs

Scientific reasoning consists of essentially three steps: coming up with hypotheses, conducting experiments, and using the results to update one’s hypotheses. Science is the ultimate open-ended problem, in that we always have an infinite space of possible hypotheses to choose from, and an infinite space of possible observations. For hypothesis generation: How do we navigate this space effectively? How do we generate diverse, relevant, and explanatory hypotheses? It is one thing to have ChatGPT generate incremental ideas. It is another thing to come up with truly novel, paradigm-shifting concepts.

I note that this is quite different from playing games like chess or Go. Those gaves have huge search spaces, much larger than we can explicitly construct. But they are well-structured spaces. The space of scientific hypotheses is not at all well-structured. I discuss this problem in various posts, including this one: Stagnation, Redux: It’s the way of the world [good ideas are not evenly distributed, no more so than diamonds] (August 13, 2024).

It will take tight integration with experiments

Once we have a hypothesis, we then need to decide which experiment to conduct. This is an iterative process. How can we identify experiments that will maximize our information gain? How do we build affordance models that tell us which experiments are possible and which are impossible? Affordance models are critical, because discovery is about doing things that have never been done before.

There's much more at the link.

There are no AI-shaped holes lying around

“There are no AI-shaped holes lying around”

-> this is how I reconcile the facts that (a) AI is already powerful and (b) it’s having relatively little impact so far

Making AI work today requires ripping up workflows and rebuilding *for* AI. This is hard and painful to do…

— Matt Clifford (@matthewclifford) September 12, 2024

Crane and sky in Hoboken

The story of "Sukiyaki," No. 1 in the USA in 1963

Mary Spender and Adam Neely talk about being musicians on tour and on YouTube

Rick Beato on the current Spotify top ten 10

Two points:

• First time since in the last three or four years that the Spotify top ten didn't include any rap or hip hop.
• First time since ??? when there's a top ten tune with a key change: Sabrina Carpenter, "Please, Please, Please."

The Dimensions of Dimensionality

The Dimensions of dimensionality

Review by Brett D. Roads (@BDRoads) & Bradley C. Love (@ProfData)https://t.co/58gCIFahBN pic.twitter.com/lJJXALVulV

— Trends in Cognitive Sciences (@TrendsCognSci) August 29, 2024

Gavriil is picking up Beethoven's 'Fur Elise'

 

Gavriil is 2 years and 11 months.

Pianist Robert Levin improvises when he plays Mozart

Zachary Woolfe, A Pianist Who’s Not Afraid to Improvise on Mozart, NYTimes, Aug. 27 2024. The article opens:

Cadenzas are a concerto soloist’s time to shine: the moments when the rest of the orchestra dramatically drops out and a single musician gets the chance to command the stage.

For about half of Mozart’s piano concertos, cadenzas he wrote have been preserved, and those are what you usually hear in concerts and on recordings. Other composers later filled in the gaps with cadenzas that have also become traditional. Some performers write their own.

But 250 years ago, when Mozart was a star pianist, he wouldn’t have performed prewritten cadenzas — even ones he had composed.

“When Mozart wrote his concertos, they were a vehicle for his skills,” the pianist and scholar Robert Levin said by telephone from Salzburg, Austria — Mozart’s hometown — where he teaches at the Mozarteum University. “He was respected as a composer and lionized as a performer, but it was as an improviser that he was on top of the heap.”

Levin, 76, has long argued that Mozart, as a player, made up new cadenzas and ornaments in the moment. And he has sought to revive that spirit of improvisation in a landmark cycle of the concertos on period instruments, a 13-album project begun more than 30 years ago with the Academy of Ancient Music, led by Christopher Hogwood.

After a two-decade gap caused by record company budget cuts, and with the last installment finally released this summer, the cycle takes an invaluable place as the most complete survey of Mozart’s music for keyboard and orchestra.

There's much more at the link.

A Diverse Trio of Flix