Another week has passed, and summer time is getting closer and closer. Let’s hope the following weeks end up being productive and I can share some good news. Let’s start with the links this week, which group the topics of 3D printing, machine learning, food, and astrobiology:
3D printing takes the smart route
A very interesting article on how researchers have started to print smart 3D objects. These objects, after being manufactured, can change its shape/properties over time. They can reconfigure themselves and adapt to different conditions, which makes them extremely useful in many scenarios, such as biomedical implants (imagine an implant that changes its shape to adapt to the body of a specific patient).
The coolest thing about the approach is that it uses a relatively cheap technology that many people can adopt, and it fastens a lot the development cycle of these smart objects. This is quite interesting because building this kind of stuff with conventional techniques might be extremely expensive or even impossible.
3D printing adds another dimension, on Chemistry World
Where the magic happens
Who wants to attend the Olympics when you can follow the World Fondue Championship? Switzerland, November 2023, you are on my calendar.
The organisers went above and beyond to spoil the audience, supplying them with 450 kg of bread, 220 kg of charcuterie, 300 kg of cheese, 500 bottles of wine and 250 large beer bottles – a feast fit for Obelix.
I Was an Amateur Judge at France’s First Fondue Championship, on VICE
The leap of faith
Awesome video of salamanders gliding on a wind tunnel. Not much more to say (as I do not fully understand why this is of interest for biologists). You can take a look at the paper if you are interested, though.
Watch salamanders ‘skydive’ in a wind tunnel, on Science
Exotic beasts and how to find them
Really good article on The Economist about the search of life outside of our planet. Besides technical difficulties (looking far away is never easy), one of the biggest challenges to finding life in the universe has always been knowing which signs to look for. For the past few decades, scientists have assumed that life on other planets should be similar to the one we find on Earth, but that is a bold hypothesis. Nowadays, people are starting to search for different signs of life, based on chemical processes that differ from the ones living beings produce on our planet. The time for searching for signs of liquid water might have come to an end.
How to improve the search for aliens, on The Economist
Is AI getting cleverer?
During the past few weeks, we have seen a few AI models being announced. It started with DALL-E, which can generate images from small pieces of text from the user (you can take a look at the examples @hardmaru has been posting for a while now on Twitter). Shortly afterwards, Google showed its own monster, Imagen, which seems to provide even more photorealistic results. Earlier this month, DeepMind presented its generalist AI model, called Gato. It can play video games, caption images, chat with people and control a robot arm, among others. In fact, DeepMind’s AI can do a total of 604 different tasks, but it does not excel at any (when compared to task-specific algorithms).
Regardless of quality (which is quite impressive in all of these examples), the announcements have sparkled many interesting debates. Doubts about what can be considered as «general» when talking about artificial intelligence, many questions regarding how these models have been trained, and of course, a lot of theories with respect to what will be the next steps on the field. While many people think that we will see human-like AI models soon, there are still a few skeptics around.
“AGI speaks to something deeply human—the idea that we can become more than we are, by building tools that propel us to greatness,” he says. “And that’s really nice, except it also is a way to distract us from the fact that we have real problems that face us today that we should be trying to address using AI.”
The hype around DeepMind’s new AI model misses what’s actually cool about it, on the MIT Technology Review
The hype around DeepMind’s new AI model misses what’s actually cool about it, on the MIT Technology Review
ALL THESE IMAGES WERE GENERATED BY GOOGLE’S LATEST TEXT-TO-IMAGE AI, on The Verge
OpenAI’s DALL-E AI image generator can now edit pictures, too, on The Verge
The dark secret behind those cute AI-generated animal images, on the MIT Technology Review
And that’s it for the week. Stay safe!
Featured image from Imagen
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