How the tech giant is trying to leverage the science of breakthroughs and resurrect the lost art of invention
A snake-robot designer, a balloon scientist, a liquid-crystals technologist, an extradimensional physicist, a psychology geek, an electronic-materials wrangler, and a journalist walk into a room. The journalist turns to the assembled crowd and asks: Should we build houses on the ocean?
Scientists at The University of Manchester have created the world’s first ‘molecular robot’ that is capable of performing basic tasks including building other molecules.
The tiny robots, which are a millionth of a millimetre in size, can be programmed to move and build molecular cargo, using a tiny robotic arm.
Each individual robot is capable of manipulating a single molecule and is made up of just 150 carbon, hydrogen, oxygen and nitrogen atoms. To put that size into context, a pile of a billion billion of these robots would still only be the same size (volume/weight) as a few grains of salt.
According to India’s Frontline magazine, anecdotal evidence from Chennai, Hyderabad, Bangalore, Pune and other cities suggests that a number of large IT service companies are shedding thousands of jobs as artificial intelligence, automation and deep learning technologies replace humans.
Bangalore’s outsourcing businesses may be on the wane, but cities like Hangzhou may indicate its best course for the future.
PUBLISHED : Tuesday, 10 October, 2017, 10:00am.
UPDATED : Tuesday, 10 October, 2017, 10:00am.
MouseAge (https://www.lifespan.io/mouseage) is creating the first photographic biomarker system using the power of artificial intelligence.
The goal of MouseAge is to create a system capable of determining the age of mice without the need for invasive or even harmful tests.
This means researchers can measure changes to biological age in mice helping to speed up research and reduce animal suffering.
China may have the clear lead in the development of artificial intelligence (AI) systems in the region, but Japan’s government, realising how vital the sector is to its economic future, has intervened in the hopes of levelling the playing field.
Japan announced in late August that it is planning to invest billions of yen to fund next-generation semiconductors and other technologies critical to AI development.
Billions of yen in public investment could help firms innovate, but analysts say the nation may never catch up with China and the US, global tech leaders that show no signs of slowing down.
By Julian Ryall
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We are using A.I. and Computer Vision Techniques to Determine Age and Assess the Effect of Therapies Against Aging in Mice, Increasing the Pace of Life Extension Research. Please subscribe, share, and fund our campaign today! ►Campaign Link: https://www.lifespan.io/mouseage ►Subscribe: https://www.youtube.com/user/LifespanIO?sub_confirmation=1
MouseAGE is working to develop the first photographic biomarker of aging in mice to help validate potential anti-aging interventions, save animal lives, and greatly speed up the pace of longevity research.
To create it we will harness the power of an area of artificial intelligence called Machine Learning, and in particular Deep Learning.
Machine Learning, where a computer system can train itself to become better at a task without explicit programming, has already showed great performance in areas such as human facial recognition, autonomous driving, medical image processing, recommendation engines and many others. While these results are powerful, building up the necessary Neural Networks, or algorithms inspired by the human brain, requires a large dataset of images to use for training: thousands of them.
Due to this, the first stage of the project will be to build a simple instrument for data collection, implemented in a mobile application. This will be distributed among numerous mouse breeding facilities and research universities all over the world to rapidly collect and properly annotate image data for analysis.
Like so many other new technologies, however, AI has generated lots of unrealistic expectations. We see business plans liberally sprinkled with references to machine learning, neural nets, and other forms of the technology, with little connection to its real capabilities. Simply calling a dating site “AI-powered,” for example, doesn’t make it any more effective, but it might help with fundraising. This article will cut through the noise to describe the real potential of AI, its practical implications, and the barriers to its adoption.
What it can — and cannot — do for your organization.