Overview of AI Labs in India

 An description and overview of Indian AI Labs via ODSC

Standout Artificial Intelligence Labs in India

ODSC - Open Data Science

Our passion is bringing thousands of the best and brightest data scientists together under one roof for an incredible learning and networking experience.

As dynamic fields, what we can do with and how we apply data science and artificial intelligence is almost constantly changing and growing. Research institutions, in particular, contribute to the discovery of new innovations and applications. Right now, we are seeing a significant amount of interesting research coming out of institutions in India, some of which are discussed below in this list of artificial intelligence labs in India.  ... '

Known UnKnowns: Uncertainty in AI

Ultimately is always an issue.  Consider it early.  Test it often.

Known Unknowns: Designing Uncertainty Into the AI-Powered System

from ODSC - Open Data Science

Uncertainty may be a fearful state for many people, but for data scientists and developers training the next wave of AI, uncertainty may be a good thing. Designing uncertainty directly into the system could help AI focus on what experts need to leverage state of the art AI and use it to inform our world.  ... "

Differential Programming

Intriguing description and demonstration code.    I am always looking at ways to connect process models and AI pattern recognition. (or any analytics)    Is this an alternative way?

Reinforcement Learning vs. Differentiable Programming

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#ODSC - Open Data Science

We’ve discussed the idea of differentiable programming, where we incorporate existing programs into deep learning models. But if you’re a researcher building, say, a self-driving car, what does differentiable programming mean in practice? How does it affect the way we express our problem, train our model, curate our dataset, and ultimately the results we achieve?

This article shows what DP can bring to some simple but classic control problems, where we would normally use Reinforcement Learning (RL). DP-based models not only learn far more effective control strategies than RL, but also train orders of magnitude faster. The code is all available to run for yourself — they will mostly train in a few seconds on any laptop. ... "

TensorFlow

Was asked this question recently.  Here a quick, non technical answer.  But does also include code, which is by its nature technical.

What is Tensorflow?

ODSC    https://opendatascience.com/  

It would be a challenge nowadays to find a machine learning engineer who has heard nothing about TensorFlow. Initially created by Google Brain team for some internal purposes, such as spam filtering on Gmail, it was open-sourced in 2015 and became the most popular deep learning framework in the next few years.

Tensorflow is often used for solving deep learning problems and for training and evaluating processes up to the model deployment. Apart from machine learning purposes, TensorFlow can be also used for building simulations, based on partial derivative equations. That’s why it is considered to be an all-purpose tool for machine learning engineers.  ... " 

Best Data Science Youtube Channels

Good resources, did  quick scan and there are some useful things there,  somewhat varied in quality,  but there are gems.

4 of the Best Data Science YouTube Channels in Medium
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There are a lot of ways that you can learn about data science and/or stay up to date with the latest trends, but the easiest by far is still Youtube. You could do a search for data science and come up with thousands and thousands of hits, but we’ve got our top four picks to help you get started. Let’s take a look:   ... '

Ontologies vs Knowledge Graphs

Challenging thoughts, which we examined for some time in the enterprise.   Not solved there either, or what it would take to construct, use and maintain this from either direction.       Ultimately it's the most important idea we can implement well to solve real, but also changing business problems in context.

Where Ontologies End and Knowledge Graphs Begin

#ODSC - The Data Science Community

Ontologies have been present in artificial intelligence research for at least forty years, coming into their own in the ’80s on the back of a research wave that catapulted them into popularity by the mid-‘90s. However, interest in ontologies waned by the 2000s as machine learning became the hot new technology for search engines and advertising. But in the past decade, two words have pushed ontologies and semantic data back into the spotlight: knowledge graphs.

Knowledge graphs have been embraced by numerous tech giants, most notably Google, which is responsible for popularizing the term. But that new widespread attention from the research community has helped foment a significant debate among knowledge representation experts: what even is a knowledge graph?

In truth, no one is really sure — or at least there isn’t a consensus.  .... "