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On Meta’s Wednesday earnings call, CFO Susan Li reiterated to investors that financial returns from its recent AI investments will “come in over a longer period of time.” Zuckerberg was direct about why Meta is spending billions on Nvidia hardware and the other infrastructure ahead of these future returns: “It’s hard to predict how this will trend multiple generations into the future, but at this point, I’d rather risk building capacity before it is needed rather than too late.”

He again telegraphed that the Meta AI assistant is on track to be the most used in the world before the end of the year. While he touted that generative AI features “are things that I think will increase engagement in our products,” he said the real revenue will come from business use cases, like AI creating ads from scratch and letting businesses operate their own AI agents in WhatsApp for customer service.

By Chuck Brooks


AI agents represent a great leap forward in technology, offering exponential benefits to society. From enhancing scientific research, healthcare, transportation, education, and cybersecurity. There are a lot of different applications that AI agents could help enable in our new digital world, including, foremost, for humans.

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In traditional Japanese basket-weaving, the ancient “Kagome” design seen in many handcrafted creations is characterized by a symmetrical pattern of interlaced triangles with shared corners. In quantum physics, the Kagome name has been borrowed by scientists to describe a class of materials with an atomic structure closely resembling this distinctive lattice pattern.

Since the latest family of Kagome metals was discovered in 2019, physicists have been working to better understand their properties and potential applications. A new study led by Florida State University Assistant Professor of Physics Guangxin Ni focuses on how a particular Kagome metal interacts with light to generate what are known as plasmon polaritons — nanoscale-level linked waves of electrons and electromagnetic fields in a material, typically caused by light or other electromagnetic waves.

The work was published in Nature Communications (“Plasmons in the Kagome metal CsV 3 Sb 5 ”).

I will begin with the first point and make my way gradually to the tenth point.

I’ve already mentioned to you that the AI of the 1970s was toy-like in comparison to the more involved and expansive AI of today. Modern-day generative AI, for example, makes use of vast amounts of data as scanned across the Internet to pattern-match the nature of human writing. This requires a massive amount of computing resources (something far beyond the depth readily employable in the 1970s). The large-scale modeling or pattern matching is what makes contemporary generative AI seem highly fluent.

A common phrase is to say that generative AI is mimicking or parroting human writing.

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.