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Artificial intelligence predicts when heart will fail


High blood pressure in the lungs damages part of the heart, and about a third of patients die with five years of being diagnosed.

 

But doctors need to have an idea of how long patients might have left, in order to pick the right treatment.

 

The software was given MRI scans of 256 patients' hearts, and blood test results.

 

It correctly predicted those who would still be alive after one year about 80% of the time.   The figure for doctors is 60%.

 

Dr Declan O'Regan, one of the researchers, told the BBC News website: "The AI really allows you to tailor the individual treatment.

 

The researchers also want to use the technology in other forms of heart failure, such as cardiomyopathy, to see who might need a pacemaker or other forms of treatment.

 

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How artificial intelligence can be used for good


Artificial intelligence (AI) is making its way from science fiction to reality, in applications like self-driving cars, personal AI systems like Cortana, Siri, and Google Assistant, and home assistants like Amazon's Alexa and Google Home.

Microsoft is, of course, one of the leaders in applying AI in real-life applications, and so far the company is focusing on how AI can help make us more productive.

According to Nadella, Microsoft's objective with regard to AI is to use it to enable developers and others to use the same AI tools that Microsoft is building into its own products.

AI is a focus of a number of leading technology companies, including Amazon with its Web Services offering AI for businesses and Google's Translate service that uses neural networks to provide more accurate and lifelike translation.

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Japanese company is replacing its staff with artificial intelligence


A future in which human workers are replaced by machines is about to become a reality at an insurance firm in Japan, where more than 30 employees are being laid off and replaced with an artificial intelligence system that can calculate payouts to policyholders.

Fukoku Mutual Life said it expects the $1.73 million smart system which costs around $129,000 each year to maintain to save the company about $1.21 million each year.

Citing the Mainichi Shimbun newspaper, the report says that Fukoku Mutual's AI would be able to read large quantities of medical documents and consider other relevant factors as it calculates the payout amount for each policy claimed but the actual payment still requires approval from a human staffer.

While the use of AI will drastically reduce the time needed to calculate Fukoku Mutual's payouts which reportedly totalled 132,000 during the current financial year the sums will not be paid until they have been approved by a member of staff, the newspaper said.

Dai-Ichi Life Insurance has already introduced a Watson-based system to assess payments - although it has not cut staff numbers - and Japan Post Insurance is interested in introducing a similar setup, the Mainichi said.

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Harvard, mit get $27m to research artificial intelligence for the public interest


LinkedIn co-founder Reid Hoffman and Omidyar Network anchor a newly formed $27 million fund to support research into the social impacts of artificial intelligence.

Hoffman and Omidyar are each kicking in $10 million to get the Ethics and Governance of Artificial Intelligence Fund started. 

Awards will be made from the fund to support a global cross-section of research aimed at applying the humanities, social sciences and other disciplines to the development of AI for the public interest. 

Technology and commerce will see to that,” Alberto Ibargüen, president of the Knight Foundation, said today in a news release announcing the fund’s establishment.

“Since even algorithms have parents, and those parents have values that they instill in their algorithmic progeny, we want to influence the outcome by ensuring ethical behavior, and governance that includes the interests of the diverse communities that will be affected,” Ibargüen said. 

The announcement lists the following as issues the Ethics and Governance of Artificial Intelligence Fund will seek to address:

- Communicating complexity: How do we best communicate, through words and processes, the nuances of a complex field like AI?

- Ethical design: How do we build and design technologies that consider ethical frameworks and moral values as central features of technological innovation?

- Advancing accountable and fair AI: What kinds of controls do we need to minimize AI’s potential harm to society and maximize its benefits?

- Innovation in the public interest: How do we maintain the ability of engineers and entrepreneurs to innovate, create and profit, while ensuring that society is informed and that the work integrates public interest perspectives?

- Expanding the table: How do we grow the field to ensure that a range of constituencies are involved with building the tools and analyzing social impact?

“One of the most critical challenges is how do we make sure that the machines we ‘train’ don’t perpetuate and amplify the same human biases that plague society,”said Joi Ito, director of the MIT Media Lab.   “How can we best initiate a broader, in-depth discussion about how society will co-evolve with this technology, and connect computer science and social sciences to develop intelligent machines that are not only ‘smart,’ but also socially responsible?”

The White House even pointed out racism in AI in an official report in October, and we can’t forget the disaster that was Tay, Microsoft’s AI chatbot meant to learn from Twitter, which ended up being baited into sending out racist tweets.

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5 things to watch in a.i and machine learning in 2017


After a tremendous 2016 for Artificial Intelligence software and hardware, we expect more AI will be will deployed in 2017 in automobiles, healthcare, manufacturing and entertainment. 

5 Things To Watch In AI And Machine Learning In 2017

1. Hardware accelerators for Machine Learning will proliferate.

2. Select application domains will leverage Machine Learning to improve efficiency of mission-critical processes.

3. Voice will enter the mainstream of man-machine interaction.

4. Enterprise IT will continue to lag in the adoption of ML, with few notable exceptions.

5. I Robot will take your job, but not just yet.

Read the full article on Forbes

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