Toggle light / dark theme

❤️ Check out Runway and try it for free here: https://runwayml.com/papers/
Use the code TWOMINUTE at checkout to get 10% off!

📝 The paper “High Definition Video Generation with Diffusion Models” is available here:
https://imagen.research.google/video/

📝 My paper “The flow from simulation to reality” with clickable citations is available here for free:
https://rdcu.be/cWPfD

🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible:
Aleksandr Mashrabov, Alex Balfanz, Alex Haro, Andrew Melnychuk, Benji Rabhan, Bryan Learn, B Shang, Christian Ahlin, Eric Martel, Geronimo Moralez, Gordon Child, Jace O’Brien, Jack Lukic, John Le, Jonas, Jonathan, Kenneth Davis, Klaus Busse, Kyle Davis, Lorin Atzberger, Lukas Biewald, Luke Dominique Warner, Matthew Allen Fisher, Matthew Valle, Michael Albrecht, Michael Tedder, Nevin Spoljaric, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, Ted Johnson, Thomas Krcmar, Timothy Sum Hon Mun, Torsten Reil, Tybie Fitzhugh, Ueli Gallizzi.
If you wish to appear here or pick up other perks, click here: https://www.patreon.com/TwoMinutePapers.

Thumbnail background design: Felícia Zsolnai-Fehér — http://felicia.hu.

Chapters:

Scientists including an Oregon State University materials researcher have developed a better tool to measure light, contributing to a field known as optical spectrometry in a way that could improve everything from smartphone cameras to environmental monitoring.

The study, published today in Science, was led by Finland’s Aalto University and resulted in a powerful, ultra-tiny that fits on a microchip and is operated using artificial intelligence.

The research involved a comparatively new class of super-thin materials known as two-dimensional semiconductors, and the upshot is a proof of concept for a spectrometer that could be readily incorporated into a variety of technologies—including quality inspection platforms, security sensors, biomedical analyzers and space telescopes.

If you’ve been closely following the progress of Open AI, the company run by Sam Altman whose neural nets can now write original text and create original pictures with astonishing ease and speed, you might just skip this piece.

If, on the other hand, you’ve only been vaguely paying attention to the company’s progress and the increasing traction that other so-called “generative” AI companies are suddenly gaining and want to better understand why, you might benefit from this interview with James Currier, a five-time founder and now venture investor who cofounded the firm NFX five years ago with several of his serial founder friends.

Currier falls into the camp of people following the progress closely — so closely that NFX has made numerous related investments in “generative tech” as he describes it, and it’s garnering more of the team’s attention every month. In fact, Currier doesn’t think the buzz about this new wrinkle on AI isn’t hype so much as a realization that the broader startup world is suddenly facing a very big opportunity for the first time in a long time. “Every 14 years,” says Currier, “we get one of these Cambrian explosions. We had one around the internet in ’94. We had one around mobile phones in 2008. Now we’re having another one in 2022.”

Next, you seem to assume that when I catch a ball, my mind solves equations unconsciously, brining together inertia, gravity, air resistance to calculate my response. You may be right, but I don’t think most neuroscientist agree with you. That’s another computationalist prejudice. Rather than solving equations, my nervous system uses experience and extrapolation through repeated trial and improvement to hone a skill in extrapolating paths; no equations involved. As I say, I could be wrong, it’s an empirical question. But as far as I know, the balance of evidence and theory supports my interpretation.

The meaning of semantics is not just that it means something, but that it can be used to make statements about the world, beyond the formal system used to express that meaning. That, too, is definitional.

Your main argument seems like a really desperate move to sustain the computationalist faith that you assert at the beginning in the face of huge, perhaps insuperable difficulties.

The recipe for the Imaginarium is locked behind the ancient doors. Three brave hunters are sent on a mission to get the three mysterious scrolls needed to open them… but somebody doesn’t like it at all.

Official Music Video for “Imaginarium” by Fish Basket.

But this track on Bandcamp: https://fishbasket.bandcamp.com/track/imaginarium.

This video was classically shot and modified using artificial intelligence.

Shot and edited by Kamil Arbuz (Arbuz Hyper Film) — https://www.facebook.com/arbuzhyperfilm @ARBUZ HYPER FILM
Directed by: Fish Basket and Kamil Arbuz.
Produced by Kamil Arbuz and Piotr Wicher.
Ai FX: Piotr Wicher.
Sound FX: Kamil Arbuz.
Screenplay: Fish Basket.
Additional editing: Piotr Wicher.
Costumes: Fish Basket.
Music recorded in Rombalnia by Adam Gajewski and Piotr Wicher.
Music Production: Piotr Wicher.
Mix and mastering: Nebula Studio.

Cast:

So even insects like to play and have fun.


Bumble bees enjoy playing with balls, suggesting insect minds are far more sophisticated than previously thought, researchers have found.

It is the first study to prove that the insects like to play with toys, even when there is no apparent benefit to their actions.

Researchers at Queen Mary University of London found that bees spontaneously chose to ignore food to roll wooden balls, with younger bees opting to roll more balls than older bees.

It suggests that younger bees are more playful, just like human children.

Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists and venture capitalists alike. As with many phrases that cross over from technical academic fields into general circulation, there is significant misunderstanding accompanying the use of the phrase. But this is not the classical case of the public not understanding the scientists — here the scientists are often as befuddled as the public. The idea that our era is somehow seeing the emergence of an intelligence in silicon that rivals our own entertains all of us — enthralling us and frightening us in equal measure. And, unfortunately, it distracts us.

There is a different narrative that one can tell about the current era. Consider the following story, which involves humans, computers, data and life-or-death decisions, but where the focus is something other than intelligence-in-silicon fantasies. When my spouse was pregnant 14 years ago, we had an ultrasound. There was a geneticist in the room, and she pointed out some white spots around the heart of the fetus. “Those are markers for Down syndrome,” she noted, “and your risk has now gone up to 1 in 20.” She further let us know that we could learn whether the fetus in fact had the genetic modification underlying Down syndrome via an amniocentesis. But amniocentesis was risky — the risk of killing the fetus during the procedure was roughly 1 in 300. Being a statistician, I determined to find out where these numbers were coming from.