The smallest mobile phone ever arrived in India, weighing only 13 grams: -

The smallest mobile phone ever arrived in India, weighing only 13 grams: -

Now in our country, the world's smallest mobile phone has been launched. Whose name "Jenko tiny T1" and its weight is just 13 grams. And the length is just 0.49 Enches and its price is only being considered as Rs. 2300, which is going to be launched with OLD completely till 2018 in India. This project was recently listed in the Kickstick Campaign and got enough response. At present, with a total of 896 supporters for this project, the small TTI of Zhenko has earned $ 55,970. The target set for  the project was $ 33,397. Interested customers can also ship mobile phones to India, but it will be available in limited units. To be specific, only 1000 units are made available initially, and currently, only 208 are left to purchase.
Diving in specifications, Kickstarter Project Page shows that Zanaco Tiny T1 will work with any mobile phone network all over the world. Users need to insert their nano-SIM card on mobile phones and start using it.

Also, keep in mind that it can work only on 2G networks. This phone will be available in frequency 2 times - 850/1900 and 900/1800 Kickstick Campaigns page indicates that customers will be able to select frequency band according to country in post-campaign survey.

Zanco Small T1 is a talk and text mobile phone, and does not have internet capability in TT.
The device weighs 46.7x21x12 mm and weighs 13 grams. It can store up to 300 contacts and up to 50 SMS. 32 MB RAM, internal memory of 32 MB, and has MediaTek MTK 6261D Motherboard. Keypad also comes with white light, allowing users to use it even in bright light conditions. It has a Micro USB port and is running in 13 voices.
Apart from this, the support of the small T1 is a 200 mAh battery, which promises three day standby and talktime of 180 minutes.

Google AI helps NASA discover 'another' solar system

Washington: NASA has used Google's artificial intelligence (AI) to discover a record-tying eighth exoplanet circling a Sun-like star 2,545 light-years from Earth, marking the first finding of an eight-planet solar system like ours.

Kepler-90i - a sizzling hot, rocky planet that orbits its star once every 14.4 days - was found using machine learning from Google to scour data from NASA's planet-hunting Kepler Telescope.

"The Kepler-90 star system is like a mini version of our solar system. You have small planets inside and big planets outside, but everything is scrunched in much closer," said Andrew Vanderburg, a NASA Sagan Postdoctoral Fellow and astronomer at the University of Texas at Austin.Machine learning is an approach to artificial intelligence in which computers "learn." In this case, computers learned to identify planets by finding in Kepler data instances where the telescope recorded signals from planets beyond our solar system, known as exoplanets.

"Just as we expected, there are exciting discoveries lurking in our archived Kepler data, waiting for the right tool or technology to unearth them, said Paul Hertz, director of NASA s Astrophysics Division in Washington. "This finding shows that our data will be a treasure trove available to innovative researchers for years to come," said Hertz.
The researchers trained a computer to learn how to identify exoplanets in the light readings recorded by Kepler the minuscule change in brightness captured when a planet passed in front of, or transited, a star. Inspired by the way neurons connect in the human brain, this artificial "neural network" sifted through Kepler data and found weak transit signals from a previously-missed eighth planet orbiting Kepler-90, in the constellation Draco.

While machine learning has previously been used in searches of the Kepler database, this research demonstrates that neural networks are a promising tool in finding some of the weakest signals of distant worlds.

Other planetary systems probably hold more promise for life than Kepler-90. About 30 per cent larger than Earth, Kepler-90i is so close to its star that its average surface temperature is believed to exceed 800 degrees Fahrenheit, on par with Mercury. Its outermost planet, Kepler-90h, orbits at a similar distance to its star as Earth does to the Sun. Kepler's four-year dataset consists of 35,000 possible planetary signals.

Automated tests, and sometimes human eyes, are used to verify the most promising signals in the data. However, the weakest signals often are missed using these methods. The researchers first trained the neural network to identify transiting exoplanets using a set of 15,000 previously-vetted signals from the Kepler exoplanet catalogue.

In the test set, the neural network correctly identified true planets and false positives 96 per cent of the time. Then, with the neural network having "learned" to detect the pattern of a transiting exoplanet, the researchers directed their model to search for weaker signals in 670 star systems that already had multiple known planets. Their assumption was that multiple-planet systems would be the best places to look for more exoplanets.

Kepler-90i was not the only jewel this neural network sifted out. In the Kepler-80 system, they found a sixth planet. This one, the Earth-sized Kepler-80g, and four of its neighbouring planets form what is called a resonant chain - where planets are locked by their mutual gravity in a rhythmic orbital dance. The result is an extremely stable system, similar to the seven planets in the TRAPPIST-1 system.