Friday August 17, 2018
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Intel to Train 15,000 people Under It’s ‘AI Developer Education Program’

The company says use of AI in sectors such as autonomous driving and the internet of things will create massive amounts of data.

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Research on AI and Machine Learning is already on at all Indian Institutes of Technologies (IITs). VOA
Intel bets on artificial intelligence, to train 15,000 people in India. VOA
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Intel is betting on Artificial Intelligence (AI) to drive demand for its electronic chips, for which it is aiming to train 15,000 scientists, developers, engineers and students on AI in India over the next one year.

The company will host 60 courses under its ‘AI Developer Education Program’. These will train people on ways they can adopt AI for better research, testing or even building of products. Intel is looking at India due to the country’s large base of technical talent. The country is the third largest global site for AI companies.

“As India undergoes rapid digital transformation, data centres and the intelligence behind the data collected will enable the government and industry to make effective decisions based on algorithms. This means increasing opportunities for using AI in the country,” said Prakash Mallya, managing director at Intel for South Asia.

The enterprise solutions major has integrated SAP CoPilot with the "SAP S/4HANA" Cloud.
AI will contribute to the biggest workload in data centres by 2020 Pixabay

He says adoption of AI in developing countries would be much faster than in developed nations, as the magnitude of change it will bring will be far larger. Intel wishes to involve the government, academia and hospitals, too.

Research on AI and Machine Learning is already on at all Indian Institutes of Technologies (IITs), the Indian Institute of Science and some private universities. The company is keen to partner with these institutions, to drive adoption of its services and to get the next generation of scientists and technologists trained for using its products and services.

“Our research groups are currently working on implementation of evolutionary algorithms in parallel environments, and using Intel based platforms and software tools to deploy, parallelise and optimise systems,” said Pushpak Bhattacharya, Director at IIT, Patna. Intel says by 2020, AI would contribute to the biggest workload in data centres, as analysis of data becomes ever more important for businesses, governments and academia. Its products reflect this change, becoming more capable in handling tasks on machine learning, computer vision and the like.

Also Read: Intel Introduces Xeon E Processor for Entry-Level Workstations

The company says use of AI in sectors such as autonomous driving and the internet of things will create massive amounts of data, which in turn will have to be analysed. Mallya says a million autonomous cars have the capacity to create half as much data as humanity creates as a whole today. (IANS)

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Researchers Develop AI That Can Help Make Cancer Treatment Less Toxic

The new "self-learning" machine-learning technique could make the dosing regimen less toxic but still effective

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Indian-American researchers unleash turmeric's power to fight cancer. Pixabay

MIT researchers, including one of Indian-origin, have developed novel machine-learning techniques to improve the quality of life for patients by reducing toxic chemotherapy and radiotherapy dosing for an aggressive form of brain cancer.

Glioblastoma is a malignant tumour that appears in the brain or spinal cord, and the prognosis for adults is no more than five years.

Patients are generally administered maximum safe drug doses to shrink the tumour as much as possible, but they still remain at risk of debilitating side effects.

The new “self-learning” machine-learning technique could make the dosing regimen less toxic but still effective.

It looks at the treatment regimen currently in use, and finds an optimal treatment plan, with the lowest possible potency and frequency of doses that should still reduce tumour sizes to a degree comparable to that of traditional regimen, the researchers said.

“We kept the goal where we have to help patients by reducing tumour sizes but, at the same time, we want to make sure the quality of life — the dosing toxicity — doesn’t lead to overwhelming sickness and harmful side effects,” said Pratik Shah, principal investigator from the Massachusetts Institute of Technology (MIT) in Boston, US.

Cancer
Representational image. Pixabay

The findings will be presented at the 2018 Machine Learning for Healthcare conference at Stanford University in California, US.

In simulated trials of 50 patients, the model comprising of artificially intelligent “agents”, designed treatment cycles that reduced the potency to a quarter or half of nearly all the doses while maintaining the same tumour-shrinking potential.

Many times, it skipped doses altogether, scheduling administrations only twice a year instead of monthly.

You May Also Like to Read About The Relation of Cancer Cells With Immune System- Decoded: How Cancer Cells Cripple Immune System

However, the researchers also had to make sure the model does not just dish out a maximum number and potency of doses. Whenever the model chooses to administer all full doses, it gets penalized, so instead it chooses fewer, smaller doses.

“If all we want to do is reduce the mean tumour diameter, and let it take whatever actions it wants, it will administer drugs irresponsibly,” Shah said.

“Instead, we need to reduce the harmful actions it takes to get to that outcome.” (IANS)