This week's top stories in AI & data science
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India’s answer to AI-powered vehicles (long read)
The Indian automobile industry transcended into a hub for manufacturing excellence and innovation. That’s right, “Bharat” is now on par with automobile juggernauts like the U.S., Germany, China, Japan, France, and Brazil.
Let’s investigate the top automotive companies in India leveraging bleeding-edge technologies like AI to transform how we perceive transportation.
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Thinking fast and slow with AI
Acclaimed economist Daniel Kahneman in his book Thinking Fast and Slow, proposed that the human brain has two separate systems for decision making – system 1 and system 2.
System 1 controls unconscious decision making like walking, climbing stairs, brushing teeth, and other tasks that may not require conscious thought.
System 2 is a slower and more deliberative type of decision-making system for tasks like playing chess, solving mathematical equations, etc.
Now, what if we apply the same principle to artificial intelligence systems?
These articles are written by members of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill the form here.
+ Explainable AI and its impact on creating a data-driven culture by Anirban Nandi
+ How to choose the right analytics/data science program by Ritesh Mohan Srivastava
Param Pravega VS all other supercomputers
The Indian Institute of Science, Karnataka, has claimed to have launched India’s most powerful supercomputer, Param Pravega. As of 2020, India has two supercomputers, PARAM Siddhi-AI and Mihir, that have made it to the Top 500 global supercomputer lists, ranking 63rd and 146th, respectively.
Param Pravega, with its claims, could possibly beat these computers in being the most powerful Indian supercomputer. But is it true?
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Hands-on Guides for ML Developers
People & Startups
Data science hiring process at Yulu
The core of everything Yulu does today is driven by its data science team.
In an interview with AIM, Jaideep Datta Dhok, head of data science at Yulu, shared some of the game-changing solutions that its data science team has delivered across departments.
Why is Kubernetes so hard to master?
The popularity of Kubernetes soared on the back of businesses’ massive migration to the cloud triggered by the pandemic. However, the extremely complex nature of developing and running distributed frameworks at scale remains a huge challenge.
While Kubernetes has become a standard in deployment management, a developer from a traditional hosting background might find it hard to master the platform.
BOTTOM OF THE NEWS
Here's what all happened last week.