Everyone knows that exercise helps both body and mind, but high-intensity interval training (HIIT) offers older adults an even greater boost for long-term brain health, compared to less intense workouts.
Comparing color qualia structures through a novel similarity task in young children versus adults https://osf.io/preprints/psyarxiv/wdcu7Moriguchi, Y., Watana…
In a gold-trimmed command center on the outskirts of Abu Dhabi, scientists are seeking to wring moisture from desert skies. But will all their extravagant cloud-seeding tech—planes that sprinkle nanomaterials, lasers that scramble the atmosphere—really work at scale?
Passwords, Touch ID, and Face ID could all be a thing of the past, as Apple is working on a future where unlocking your devices is as easy as just holding a future iPhone or letting your Apple Watch sense your unique heart rhythm.
Everyone’s heart has a unique rhythm, which the Apple Watch monitors through the ECG app. In a recently granted patent, Apple describes a technique for identifying users based on their unique cardiovascular measurements.
With this technology, you can unlock all your devices if you keep wearing your Apple Watch. Verifying your heart patterns instead of a password or a fingerprint scan increases security and speeds up your identification.
A team led by researchers from the California NanoSystems Institute at UCLA has designed a unique material based on a conventional superconductor—that is, a substance that enables electrons to travel through it with zero resistance under certain conditions, such as extremely low temperature. The experimental material showed properties signaling its potential for use in quantum computing, a developing technology with capabilities beyond those of classical digital computers.
Tomohiro harada 1 and masashi kimura 2
Published 28 November 2014 • © 2014 IOP Publishing Ltd.
Visual riddles a commonsense and world knowledge challenge for large vision and language models.
Visual Riddles.
A commonsense and world knowledge challenge for large vision and language models.
Brandon Wang is vice president of Synopsys.
The rapid development of AI has led to significant growth across the computing industry. But it is also causing a huge increase in energy consumption, which is leading us into an energy crisis. Current AI models, especially large language models (LLMs), need huge amounts of power to train and run. AI queries require much more energy than traditional searches; for example, asking ChatGPT a question consumes up to 25 times as much energy as a Google search. At current rates of growth, AI is expected to account for up to 3.5% of global electricity demand by 2030, twice as much as the country of France.
We need to address this issue urgently before it becomes unsustainable. If we don’t, the impact could threaten sustainable growth and the widespread adoption of AI technologies themselves. Fortunately, there are a number of pathways toward more energy-efficient AI systems and computing architectures.
Lithium-ion batteries have a lot of advantages. They charge quickly, have a high energy density, and can be repeatedly charged and discharged.
They do have one significant shortcoming, however: they’re prone to short-circuiting. This occurs when a connection forms between the two electrodes inside the cell. A short circuit can result in a sudden loss of voltage or the rapid discharge of high current, both causing the battery to fail. In extreme cases, a short circuit can cause a cell to overheat, start on fire, or even explode.
Continue reading “Adding thin layer of tin prevents short-circuiting in lithium-ion batteries” »
