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Category: robotics/AI – Page 1864

The competition between the United States and China on artificial intelligence is heating up recently. In the coming AI Race, can India with an abundance of engineering talent really catch up with the US and China?

Artificial Intelligence, Machine Learning, Robotics, and The Internet of Things (IoT) are one of the rapidly advancing technological developments. The rate of progress in the field of these is amazingly rapid. From SIRI to self-driving cars, artificial intelligence is changing our daily life in many ways.

India is on course to become the third-largest economy in the world (by GDP) within the next few years according to MIT Technology Review. Indian government released a report on artificial intelligence in 2018 that calls for the country to boost investment and focus on deploying the technology in manufacturing, health care, agriculture, education, and public utilities. Currently, around 400 new companies in India have put resources into work including artificial intelligence and machine learning.

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Amazing 100% I hope it is real and next we can detect more diseases easier and more accurate.

Doctors can detect heart failure from a single heartbeat with 100% accuracy using a new artificial intelligence-driven neural network.

That’s according to a recent study published in Biomedical Signal Processing and Control Journal, which explores how emerging technology can improve existing methods of detecting congestive heart failure.

Led by researchers at the Universities of Surrey, Warwick and Florence, it shows that AI can quickly and accurately identify CHF by analyzing one electrocardiogram (ECG) heartbeat.

Continue reading “Artificial Intelligence Detects Heart Failure From One Heartbeat With 100% Accuracy” | >

The code used below is on GitHub.

In this project, we’ll be solving a problem familiar to any physics undergrad — using the Schrödinger equation to find the quantum ground state of a particle in a 1-dimensional box with a potential. However, we’re going to tackle this old standby with a new method: deep learning. Specifically, we’ll use the TensorFlow package to set up a neural network and then train it on random potential functions and their numerically calculated solutions.

Why reinvent the wheel (ground state)? Sure, it’s fun to see a new tool added to the physics problem-solving toolkit, and I needed the practice with TensorFlow. But there’s a far more compelling answer. We know basically everything there is to know about this topic already. The neural network, however, doesn’t know any physics. Crudely speaking, it just finds patterns. Suppose we examine the relative strength of connections between input neurons and output. The structure therein could give us some insight into how the universe “thinks” about this problem. Later, we can apply deep learning to a physics problem where the underlying theory is unknown. By looking at the innards of that neural network, we might learn something new about fundamental physical principles that would otherwise remain obscured from our view. Therein lies the true power of this approach: peering into the mind of the universe itself.

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IBM HR Director Diane Gherson says that over the next three years, 120 million workers will need retraining as artificial intelligence continues to take jobs.

Artificial intelligence is obviously ready to get started. Over the next three years, about 120 million workers from the 12 largest economies in the world may need to undergo retraining due to advances in artificial intelligence and intelligent automation, according to a study published on Friday by the IBM Institute of Business Value. However, less than half of the CEOs surveyed by IBM said they had the resources needed to bridge the skills gap caused by these new technologies.

Concerns about how AI successes will affect work are not new. Tesla and SpaceX CEO Elon Musk said last month that AI could make many jobs “pointless”. In one report earlier this year, it was discovered that robots could replace people with a quarter of US jobs by 2030.

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Much like US corporations do now.

Debates about rights are frequently framed around the concept of legal personhood. Personhood is granted not just to human beings but also to some non-human entities, such as corporations or governments. Legal entities, aka legal persons, are granted certain privileges and responsibilities by the jurisdictions in which they are recognized, and many such rights are not available to non-person agents. Attempting to secure legal personhood is often seen as a potential pathway to get certain rights and protections for animals1, fetuses2, trees and rivers 3, and artificially intelligent (AI) agents4.

It is commonly believed that a new law or judicial ruling is necessary to grant personhood to a new type of entity. But recent legal literature 5–8 suggests that loopholes in the current law may permit legal personhood to be granted to AI/software without the need to change the law or persuade a court.

For example, L. M. LoPucki6 points out, citing Shawn Bayern’s work on conferring legal personhood on AI7, 8, “Professor Shawn Bayern demonstrated that anyone can confer legal personhood on an autonomous computer algorithm merely by putting it in control of a limited liability company (LLC). The algorithm can exercise the rights of the entity, making them effectively rights of the algorithm. The rights of such an algorithmic entity (AE) would include the rights to privacy, to own property, to enter into contracts, to be represented by counsel, to be free from unreasonable search and seizure, to equal protection of the laws, to speak freely, and perhaps even to spend money on political campaigns. Once an algorithm had such rights, Bayern observed, it would also have the power to confer equivalent rights on other algorithms by forming additional entities and putting those algorithms in control of them.”6. (See Note 1.)

Continue reading “Your Software Could Have More Rights Than You” | >