Monday, April 8, 2019

Stir the IPR pot for innovation

Last month, the US Chamber of Commerce’s Global Innovation Policy Centre (GIPC) released its 7th annual International Intellectual Property (IP) Index, which assesses the IP climate in 50 world economies. India moved from 44th rank in 2018 to 36th in 2019. But, looking at the scores across the eight categories assessed, India comes in well below the average score of the top five economies, and scores considerably lower than the Asia average.
India’s national IP Rights Policy (IPR) was created in 2016. One of its stated objectives was ‘to guide and enable all creators and inventors to realise the potential for generating, protecting and utilising IP which would contribute to wealth creation, employment generation and business development’. It also aimed to ‘foster predictability, clarity and transparency in the entire IP regime in order to provide a secure and stable climate for stimulating inventions and creations’.
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प्राचार्य होण्यासाठी दहा शोधनिबंध प्रसिद्ध करण्याची अट

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Friday, April 5, 2019

Blockchain (Accenture)

It’s changing the future as we speak—but where do you start? Harness Blockchain with real-world applications from the leaders in distributed ledger technologies.

To read the full article, visit:
https://www.accenture.com/gb-en/services/blockchain-index (Accessed on April 5, 2019)

Will Blockchain Replace EDI? Yes And No

The first version of the GS1 EPCIS standard was drafted in 2007 by GS1 and GS1 US. GS1 is a nonprofit organization that creates and maintains standards for business communications and GS1 US is a member of GS1. The standard enables organizations to create and share visibility event data, both within and across organizations. The standardized data (the payload) was intended to be exchanged as XML files. Little could anyone have foreseen the standard using blockchain as a transmission medium.

To read the full article, please visit:
https://www.forbes.com/sites/forbestechcouncil/2019/04/03/will-blockchain-replace-edi-yes-and-no/#2ccced9847d7 (Accessed on April 5, 2019)

Artificial Intelligence can help in treating brain tumours: Study

The study showed that using a reference database with MRI scans of patients, the algorithms automatically recognised and localised brain tumours using artificial neural networks. 

brain tumour, brain
Artificial Intelligence can help in treating brain tumours  |  Photo Credit: Thinkstock
London: Researchers have developed an artificial intelligence-based (AI) method for analysis of brain tumours, paving the way for individualised treatment of tumours.
According to the study, published in the The Lancet Oncology, AI machine learning methods, carefully trained on standard magnetic resonance imaging (MRI), are more reliable and precise than established radiological methods in the treatment of gliomas. 






Source: 

7 Indicators Of The State-Of-Artificial Intelligence (AI), March 2019

  1. AI “Sputnik moment” (say it in Chinese*) is at hand
  2. AI continues to be popular among business executives, regardless of complications, concerns and confusion
  3. The race against the machine is on. Still, some humans trust AI more than their governments.
  4. “AI” is the new “Big Data” and the new “New Economy.” Tech bubbles are defined by poorly-defined terms and the proliferation of billion- and trillion-dollar forecasts leading to investors’ irrational exuberance
  5. After years in the (mostly Canadian) wilderness followed by (almost) seven years of plenty, Deep Learning is officially recognized as the dominant AI paradigm
  6. AI is not perfect and will never be. Same as the humans using AI.
  7. AI is not perfect. Smart and well-endowed people hope it can be improved by establishing research and education centers focusing on “multidisciplinary collaboration and diversity of thought”
To read in-depth about the above points, please visit:

How to Operationalize Your Machine Learning Projects

Operationalizing those data science, analytics, and machine learning projects is one of the top concerns of IT leaders. But the same tried-and-true best practices you've used for other IT projects can guide you on these new technologies, too.
Everyone knows that to compete in the future, you need to invest in machine learning, artificial intelligence, data, and analytics. But there still can be a big gap between knowing that you need to do it and figuring out how to do it in a way that is meaningful for your business.
Putting these technologies into production systems continues to be a challenge for many enterprises, according to Erick Brethenoux, a research director at Gartner.
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