In the face of rising competition from Amazon Web Services and Microsoft, global tech giant Google is betting big on its cloud services to woo 44 million small and medium enterprises (SMEs), more than 20,000 start-ups and hundreds of major companies. Google’s cloud customers in India include Ashok Leyland, goibibo.com, Hero MotoCorp, Policybazaar.com, Quikr, Yaatra, SBI Cards, Hike Messenger, Vistara and ShareChat. The company, which currently has three data centres in Mumbai, is on an expansion spree. Knowing that the demand is set to increase from the fintech sector in over the next couple of months as banks and non-banking financial institutions hurry to meet Reserve Bank of India’s (RBI) directive to bring financial data back to India, the company is hoping for a rise in demand.
Showing posts with label machine learning. Show all posts
Showing posts with label machine learning. Show all posts
Thursday, 14 June 2018
Tuesday, 4 July 2017
Google may get access to genomic patient data - why we should worry
If this were to happen, it could help bring down costs and speed up genetic sequencing – potentially helping the science to flourish. But what are the risks of letting a private company have access to sensitive genetic data?
Genomic sequencing has huge potential – it could hold the key to improving our understanding of a range of diseases, including cancer, and eventually help find treatments for them. The 100,000 Genomes Project was set up by the government to sequence genomes of 100,000 people. And it won’t stop there. A new report from the UK’s chief medical officer, Sally Davies, is calling for an expansion of the project.
However, a statement by the Department of Health in response to a freedom of information (FoI) request I made in February reveals this decision has already been made. The department said in this response that the project will be integrated into a single national genomic database. The purpose of this will be to support “care and research, and the acceleration of industrial usage”. Though it will “inevitably exceed the original 100,000 genomes, we do not anticipate that there will be a set target for how many genomes it should contain”, the statement reads.
The costs of sequencing the genome on a national scale are prohibitive. The first human genome was sequenced at a cost of US$3 billion. However, almost two decades later, Illumina, which is responsible for the sequencing side of the 100,000 Genomes Project, produced the first “$1,000 genome” – a staggering reduction in cost. Applying machine learning to genomics – that is, general artificial intelligence – has the potential to significantly reduce the costs further. By building a neural network, these algorithms can interpret huge amounts of genetic, health, and environmental data to predict a persons health status, such as their level of risk of heart attack.
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Thursday, 9 February 2017
Ola appoints Badri Raghavan as chief data scientist
Latest News - "This team will work across various business units and departments, to gain operational and business efficiencies, ranging from demand and supply prediction, driver behaviour and performance management, location Intelligence, to name a few," Ola said in a statement.
"Ola is moving on a much larger scale towards building technology based on deep insight into the Indian psyche, and for this, Big Data is a must," Ola CTO and co-founder Ankit Bhati said.
With over a million trips on the platform every day, an enormous amount of data is (Read More)
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