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This interview is an episode from @The-Well, our publication about ideas that inspire a life well-lived, created with the @JohnTempletonFoundation.

Watch Lisa Feldman Barrett’s next interview ► • The biggest myths about emotions, deb…

Our perception of reality is not an exact representation of the objective truth but rather a combination of sensory inputs and the brain’s interpretation of these signals. This interpretation is influenced by past experiences and is often predictive, with the brain creating categories of similar instances to anticipate future events.

The brain’s categorization process extends beyond physical characteristics to include abstract, functional features. This ability allows humans to create “social reality,” where we collectively assign functions or meanings to objects or concepts that don’t inherently possess them, such as the value of money or the concept of borders and citizenship.

Continue reading “Your brain doesn’t detect reality. It creates it. | Lisa Feldman Barrett” | >

Large Language Models (LLMs) are exceptionally resource-intensive on the CPU and memory, but Apple is said to be experimenting with storing this technology on flash storage, likely to make it easily accessible on multiple devices. However, the technology giant also wishes to make LLMs ubiquitous on its iPhone and Mac lineup and is exploring ways to make this possible.

Storing LLMs on flash memory has been difficult; Apple aims to fix this on machines with limited capacity

Under typical conditions, Large Language Models require AI accelerators and a high DRAM capacity to be stored. As reported by TechPowerUp, Apple is working to bring the same technology, but to devices that sport limited memory capacity. In a newly published paper, Apple has published a paper that aims to bring LLMs to devices with limited memory capacity. iPhones have limited memory too, so Apple researchers have developed a technique that uses flash chips to store the AI model’s data.

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Elon Musk and “conscious AI.” Please visit https://brilliant.org/digitalengine — a great place to learn about AI and STEM subjects. You can get started for free and the first 200 people will get 20% off a premium annual subscription.

Thanks to Brilliant for sponsoring this video.

I used GPT-3 and a Synthesia avatar. All answers are by GPT-3 (except the brief joke at the end).

Continue reading “This AI says it’s conscious and experts are starting to agree. w Elon Musk” | >

Scientists have discovered a new class of materials, carbon nitrides, which could rival diamonds in hardness. This discovery, the result of international collaboration and decades of research, opens up possibilities for various industrial applications due to their durability and other properties like photoluminescence and high energy density. Funded by international grants and published in Advanced Materials, this breakthrough marks a significant advancement in material science.

Scientists have solved a decades-long puzzle and unveiled a near unbreakable substance that could rival diamond, as the hardest material on earth, a study says.

Researchers found that when carbon and nitrogen precursors were subjected to extreme heat and pressure, the resulting materials – known as carbon nitrides – were tougher than cubic boron nitride, the second hardest material after diamond.

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Shirriff’s blog goes into a deep dive with a look inside the HP PHI chip, its construction, and die. He even examines its logic gates, first-in-first-out buffers (FIFOs), and address decoder. Please check out the blog for all these finer details and more.

In conclusion, the computer historian echoes our initial thoughts that this silicon-on-sapphire IC is “interesting as an example of a ‘technology of the future’ that didn’t quite pan out.”

Shirriff also contrasts late 70s era processors built on silicon-on-sapphire vs regular silicon in terms of energy consumption and clock speeds. Would you be surprised to hear that silicon-on-sapphire ICs were far superior using these metrics? Things might have panned out differently if these transparent ICs had been mass-produced at better yields and lower manufacturing costs. A frightening statistic highlighted by Shirriff is that HP’s silicon-on-sapphire yields were a mere 9%.

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The world works at different levels — fundamental physics, physics, chemistry, biology, psychology, sociology — with each level having its own rules and regularities. Here’s the deep question: Ultimately, can what happens at a higher level be explained entirely in terms of what happens at a lower level? If the answer is ‘No’, if complete explanatory reduction fails, then what else could be going on?\
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New findings published in Molecular Cell provide details about the hidden organization of the cytoplasm—the soup of liquid, organelles, proteins, and other molecules inside a cell. The research shows it makes a big difference where in that cellular broth, messenger RNA (mRNA) gets translated into proteins.

“You know the old real estate saying, ‘location, location, location.’ It turns out it applies to how proteins get made inside of cells, too,” says Dr. Mayr, a molecular and cell biologist at the Sloan Kettering Institute, a hub for basic and translational research within MSK. “If it’s translated over here, you get twice as much as if it’s translated over there.”

This first-of-its-kind study highlights the degree to which the cytoplasm is “beautifully organized” rather than being just a big jumble of stuff, she says.

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