Unlocking the complexities of the fruit fly brain is a crucial step toward understanding the human brain. Fruit flies share many genetic similarities with humans, making them a valuable model organism for studying brain functions as well as diseases.

“An estimated 75% of human genes related to diseases have homologs in the fly genome,” Sebastian Seung, co-leader of the research team, told Interesting Engineering (IE).

“We’ve long known about the molecular similarities between fly and human brains. We have been slower to realize that there are also similarities at the circuit level, revealed by examining patterns of connectivity. We now know that fly circuits for olfaction, vision, and navigation have architectural similarities with mammalian circuits for the same functions,” Seung added.

The team says that DNA — known for its stability and density — could be an ideal candidate for MRI data storage.

Brain MRI scans provide invaluable insights into our bodies.

Interestingly, the team successfully encoded 11.28 megabytes of brain MRI data into roughly 250,000 DNA sequences. This translates to a data density of 2.39 bits per base.

The encoded oligos, which are the DNA sequences containing the MRI data, are stored in a “dry powder form.” The oligos weigh only 3 micrograms, which is incredibly small. This suggests that a vast amount of data can be stored in a tiny space.

It can “support over 300 reads under current technical standards.”

A theoretical analysis from researchers at Japan’s largest scientific research agency, RIKEN, suggests that intermediate energy heavy-ion collisions can give birth to the strongest electromagnetic fields ever observed.

Heavy ion collisions involve colliding large atomic nuclei at high velocities. Such collisions generate strong electric fields for a brief period, enabling scientists to study behaviors and phenomena that are otherwise remain hidden.

New cooling technologies that incorporate energy storage could help by charging themselves when renewable electricity is available and demand is low, and still providing cooling services when the grid is stressed.

“We say, take the problem, and turn it into a solution,” says Yaron Ben Nun, founder and chief technology officer of Nostromo Energy.

One of Nostromo Energy’s systems, which it calls an IceBrick, is basically a massive ice cube tray. It cools down a solution made of water and glycol that’s used to freeze individual capsules filled with water. One IceBrick can be made up of thousands of these containers, which each hold about a half-gallon, or roughly two liters, of water.

The allure of AI companions is hard to resist. Here’s how innovation in regulation can help protect people.

Acquired for an undisclosed sum, Hugging Face thinks the buyout will help developers build large-scale models, on par with OpenAI and Google.

But that doesn’t mean Frosst is bullish on everything the industry is building. He doesn’t think AI is really ever going to get to artificial general intelligence, defined as human-level intelligence, which is a noticeably different narrative from some of Frosst’s AI peers like Mark Zuckerberg and Jensen Huang. He added that if the industry does get there, it’s not going to be for a long time.

“I don’t think we’re gonna have digital gods anywhere, anytime soon,” Frosst said. “And I think more and more people are kind of coming to that realization, saying this technology is incredible. It’s super powerful, super useful. It’s not a digital god. And that requires adjusting how you’re thinking about the technology.”

Frosst said they try to be realistic at Cohere about what AI technology can and can’t do and what types of neural networks can provide the most value. Cohere’s approach to building its business model is based on the research work of Cohere co-founder and CEO Aidan Gomez while at Google Brain. Gomez is, of course, known for his extensive AI research. He’s most famous for co-writing a paper that bought AI the transformer model that ushered in this generative AI era. But he also co-wrote a paper in 2017 called One Model to Learn Them All. This research came to the conclusion that an all-encompassing large language model is more useful than small models trained for a specific task or on data from a specific industry, Frosst said.

Yes, use of these platforms can sometimes harm. But it’s not all bad.

Kenyan runners, like many others, are grappling with the impact of expensive, high-performance shoes.

The track at Moi University’s Eldoret Town Campus doesn’t look like a facility designed for champions.

Explore the concept of the singularity— the point where AI could surpass human intelligence—and its potential impact on society.