You’re correct. There are people in the US who drive in the passing lane without passing, but most consider that a bad practice, as it makes roads both less efficient and less safe.
Allianz Life publishes a HIPAA privacy notice at [0], which states:
> This notice applies to individuals who participate in any of the following programs under the closed line of business:
> • Long term care
> • Medical
> • Medical supplemental
> • Hospital income
> • Cancer and disease specific coverage
> • Dental benefits
> The Covered Entity’s actions and obligations are undertaken by Allianz employees as well as the third parties who perform services for the Covered Entity. However, Allianz employees perform only limited Covered Entity functions – most Covered Entity administrative functions are performed by third party service providers.
It sold long term care insurance policies until 2010.
(Disclosure, I happen to have worked at Allianz Life a long time ago, though I have no nonpublic information about any of this.)
The obvious one is that you can handle bigger workloads than you can fit in RAM on a single machine. The more important but less obvious one is that it right-sizes the resources needed for each workload, so you're not running an 8GB job on an 8TB machine, and your manually-allocated 8GB server doesn't OOM when that job grows to 10GB next year.
This is really cool, not sure how I missed it. I assume catalog support will be added fairly quickly. But ironically I think the biggest barrier to adoption will be the lack of an off-ramp to a FOSS solution that companies can self-host. Obviously Polars itself is FOSS, but it understandably seems like there's no way to self-host a backend to point a `pc.ComputeContext` to. That will be an especially tough selling point for companies that are already on Spark. I wonder how much they'll focus on startups vs. trying to get bigger companies to switch, and whether they'll try a Spark compatibility layer like DataFusion (https://github.com/apache/datafusion-comet).
Disclaimer: I work for Polars Inc, but my opinions are my own.
Polars itself is FOSS and will remain FOSS.
Self-hosted/on-site Polars Cloud is something we intend on developing as there is quite a bit of demand, but it is unlikely to be FOSS. It most likely will involve licensing of some sort. Ultimately we do have to make money, and we intend on doing that through Polars Cloud, self-hosted or not (as well as other ventures such as offering training, commercial support, etc).
Yep I totally get it and would probably go the same route in Polars' situation. Just sharing how some of the data teams I'm familiar with would likely be thinking about the tradeoffs.
Anecdotally, I use rideshare every workday for last-mile transit from the train station, and I’ll pick the $13 Waymo over the $7 Uber every time. There are some inherent advantages to the self-driving, like improved safety [0] and not having to talk to the driver, but the main benefits are that it’s just a consistent experience with nice quiet cars, ~90%-ile driving quality, and much more accurate time estimates.
I look forward to competition bringing prices down, but on pure quality and willingness to pay, the premium price seems to make sense.
Insurance requires risk transfer but that's different from cross-subsidization. It's fine for 100 equally flood-prone houses to all pay the same insurance premiums even if only 1 of them floods in a given year. But people in a less flood-prone area, all else being equal, should be paying less for flood insurance. The alternative (aka the status quo) creates market distortions, making it artificially cheap to live in flood-prone areas and encouraging more building there.
Plenty of people would still live in those areas even if they were paying actuarially fair prices for insurance. And lots of places are safe enough from natural disasters that they're affordable to live in without cross-subsidization - in fact, eliminating cross-subsidization would make most people's cost of living go down, at the expense of a minority of people who live in very high-risk areas.
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