digital_ins

You should look up the NTPC chairman's explanation for why average PLF runs below 75%.

Apparently, the transmission & distribution network for evacuation is overburdened already. This results in plants running below their rated capacities.

Also, you're absolutely wrong about imported coal plants being rare. I don't know of any critical or super critical plants that could use 100% domestic coal without having to blatantly lie on their EIA study about ash disposal. It's just not viable.

This is incorrect. Local, domestic coal has significantly worse project economics, which is why local plants prefer the imported variety.

That's not true. As anyone in the power industry will tell you, Indian coal, tho voluminous in availability, has a relatively very low calorific content and relatively much higher Ash content. As a result, disposal of ash is far more expensive than project economics can sustain. As a result, imported coal IS the standard, domestic coal may be used as a supplement, and long term supply contracts from local traders who import from sites in Indonesia, et al. is commonplace.

But Parse was acquired by Facebook. So this clause wouldn't apply.

Dell's focus on selling cheaper laptops has resulted in treating the consumer as fungible; and that's the reason for their absolutely appalling customer service.

You're starting to see this across industries where their products and services are commoditized. Quite surprisingly, when the service / product turns into a commodity (due to competition), so does the customer (due to budgetary constraints)

kinda describes what's going on in developing countries too. The lack of innovation in developing country might have almost nothing to do with the previously popular and highly peddled concept of "inferior races"

I started off disagreeing with your statement but as I read further, I became a believer. In fact, "gotcha" and other trick questions are the worst, but understanding CS fundamentals shows that you were paying attention in class and are probably interested (if not passionate) about CS.

If not, there are hundreds of other openings that the candidate can apply to.

Nice! What's the thought process behind the recommendation? Are you using spelling similarities, or something like that?

I loved this article. Not just the term "AI", I've seen startups abuse the terms "machine learning" and "big data" to such an extent that it literally makes me cringe when I hear them.

How many times have you seen a TechCrunch article where the writer parrots the buzzwords the founder has thrown at them such as "x uses machine learning to sync your contacts with the cloud".

This is awesome. Thank you for sharing!