The Belamy | Salary Study, Synthetic Data & Explainability
Here are our top AI stories from last week.
Analytics India Salary Study 2021
We have released our most impactful annual research report on data science salaries in India for 2021. Done in collaboration with AnalytixLabs, here are some of the key takeaways:
1. The median salary of analytics professionals in India in 2021 is INR 13.4 Lakhs – a 6.9% decline over the 2020 median salary of INR 14.4 Lakhs. Much of the decrease in salary can be attributed to the pandemic. In spite of this, the median has remained above the 2019 median.
2. The proportion of the analytics professionals remains the highest in the entry and middle-income levels (0-6 Lakhs – 38.2% and 6-10 Lakhs – 20.3%). The salary cuts led to an increase in the percentage of Analytics professionals in lower brackets.
3. However, 41.5% of all the analytics professionals fall under the higher income level (greater than 10 Lakhs per annum). The percentage of analytics professionals with greater than 10 lakh salary was 45.6% in 2020, signifying a decrease in the percentage of professionals in the bracket.
4. Once again, Mumbai emerges as the destination for the highest salaries for analytics employees at 14.7 Lakhs per annum as median salary, followed by Bengaluru at 14.5 Lakhs.
How Synthetic Data Levels The Playing Field
To build data-heavy applications like machine learning algorithms, generating synthetic data has become an essential skill set that a data scientist must possess.
Deep Generative Networks/Models can learn the distribution of training data to generate new data points with some variations. While it is not always possible to learn the models’ exact distribution, algorithms can come close.
Is Explainability In AI Always Necessary?
The ML community is yet to agree on a definition for explainability or interpretability. Sometimes it is even called understandability. Some define interpretability as “the ability to explain or to present in understandable terms to a human”. According to experts, interpretability depends on the domain of application and the target audience.
Therefore, a one-size-fits-all definition might be infeasible or unnecessary. When concepts are used interchangeably, would it be wise to sacrifice the usability of a model for lack of comprehension? Where does one draw the line?
Featured Video | Google uses AI to help you navigate indoors and more.
System on Chips And The Modern Day Motherboards
Data centres are no longer betting on the one-size-fits-all compute. Decades of homogenous compute strategies are disrupted by the need to optimise. Modern-day data centres are embracing purpose-built System on Chip (SoC) designs to have more control over peak performance, optimise power consumption and scalability.
Thus, customisation of chips has become the go-to solution for many cloud providers. Companies like Google Cloud especially are doubling down on this front.
Hands-On Guides for ML Developers
PEOPLE & STARTUPS
What To Make Of Intel’s Foray Into Foundry Business
Pat Gelsinger, who took on the CEO’s mantle at Intel last January, made a few important announcements at its global event– ‘Intel Unleashed: Engineering the Future.
Gelsinger shared his vision for the future of Intel’s integrated device manufacturing (IDM) model. Talking about IDM 2.0, he revealed three significant plans.
What To Expect From Adam Selipsky, The New AWS Cloud Head
Amazon recently roped in its former executive and Tableau CEO Adam Selipsky to lead its cloud business. He will replace Andy Jassy once he moves to the role of Amazon’s CEO after Jeff Bezos steps down.
AWS has high hopes from Selipsky as he takes on the mantle. Analysts believe Selipsky is a good choice as AWS CEO for several reasons.
BOTTOM OF THE NEWS
Here's what all happened last week.