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Blog – Page 193

Month: February 2023 – Page 193

Quantum entanglement breakthrough is world first

For the first time, physicists have achieved quantum mechanical entanglement of two stable light sources.

Called “spooky action at a distance” by Einstein, quantum entanglement is a seemingly magical phenomenon. Entangled particles, for example light particles called “photons”, share a physical state. Changes to the physical state of one particle in an entangled pair instantaneously causes the same change to occur in its partner – no matter how far apart they are separated.

While quantum mechanical theory is clear on the existence of this effect in the universe, creating entangled pairs of particles is no trivial feat.

React Internationalisation (i18n) with React-Intl example

Check out my courses here!
https://www.udemy.com/user/maksym-rudnyi/

!! Updated version with fix all issues from comments — https://youtu.be/mmCnx0YnBs4.

Today we’ll implement Internationalisation for our React app. To do any site/app available for different languages, we can use React-Intl module.

In this React i18n tutorial, we will add 3 different languages: English, German and French. You can add as many as you want languages and it’ll work fine.

GitHub Demo — https://github.com/MaksymRudnyi/ReactIntlDemo.
React Context tutorial — https://youtu.be/tEFrcYNm9HY
Create React app — https://github.com/facebook/create-react-app.
React-Intl — https://github.com/formatjs/react-intl.

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Saudi Arabia Showcases NEOM’s Progress With Newly Released Footage and Exhibition

Last Updated on January 30, 2023

The futuristic smart city of The Line at NEOM, being built as part of the larger NEOM project in northwestern Saudi Arabia, was put on display in Riyadh in January 2023. The exhibition will run until April 29th at the Diriyah Biennale Foundation for Contemporary Art in the Jax district and offers visitors a glimpse into life in the revolutionary linear city.

New AI classifier for indicating AI-written text

We’re launching a classifier trained to distinguish between AI-written and human-written text.

We’ve trained a classifier to distinguish between text written by a human and text written by AIs from a variety of providers. While it is impossible to reliably detect all AI-written text, we believe good classifiers can inform mitigations for false claims that AI-generated text was written by a human: for example, running automated misinformation campaigns, using AI tools for academic dishonesty, and positioning an AI chatbot as a human.

Our classifier is not fully reliable. In our evaluations on a “challenge set” of English texts, our classifier correctly identifies 26% of AI-written text (true positives) as “likely AI-written,” while incorrectly labeling human-written text as AI-written 9% of the time (false positives). Our classifier’s reliability typically improves as the length of the input text increases. Compared to our previously released classifier, this new classifier is significantly more reliable on text from more recent AI systems.

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