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Paywall articles with workarounds _are_ allowed (https://news.ycombinator.com/newsfaq.html)

Fun fact: one of the author, Larry Guth, is the son of Alan Guth, theoretical physicist of inflation Cosmology fame (https://en.wikipedia.org/wiki/Larry_Guth)

MIT abandoned DEI statements also recently.See also the discussion here.


Here's something I just don't understand. I have a profit sharing plan *for life*, and yet I want to publicly thrash it so that the benefits I can derive from it is reduced, all in the name of some form of ... what, social service?

Yeah, people do things financially not optimal for the sake of ethics. That’s a key part of living in a society. That’s part of why we don’t just murder each other.

Your assumption is that covering up unethical behavior is good for you in the long run. Really it's only good for you in the long run if you manage to be canny enough to sell just before the ****storm hits.

But what's stopping the ex-staffers from criticizing once they sold off the equity?

Nothing, these don't seem like legally enforceable contracts in any case. What they do appear to be is a massive admission that this is a hype train which can be derailed by people who know how the sausage is made.

It reeks of a scammer's mentality.

The threat of a lawsuit.

You can't just sign a contract and then not uphold your end of the bargain after you've got the benefit you want. You'll (rightfully) get sued.

Here's something that bugs me about ML: all we have is prediction and no explanation how we come to that prediction, ie: no deeper understanding on the underlying principles.

So despite that we got a good match this time, how can we be sure that the match will be equally good next time? And how to use ML to predict structure that we have no baseline to start with or experimental result to benchmark ? In the absence of physics-like principles, How can we ever be sure that ML results next time is correct ?

There is a biannual structural prediction contest called CASP [1], in which a set of newly determined structures is used to benchmark the prediction methods. Some of these structures will be "novel", and so can be used to estimate the performance of current methods on predicting "structure that we have no baseline to start with".

CASP-style assessments are something that should done for more research fields, but it's really hard to persuade funders and researchers to put up the money and embargo the data as required.

[1] https://en.wikipedia.org/wiki/CASP

Speaking of physics, we should borrow the quote "Shut up and calculate" to describe the situation: it works so use it now and worry about the explanations later.

Except the model is not open-source. You can't calculate anything.

Zoho prices strategically. For example, it ensures that the price for the help desk product, ZohoDesk is the lowest in the market; across all tier it is priced at USD 1/month cheaper than the next cheapest competitor, FreshDesk.

Also, IIRC, the CEO of Freshworks (company behind FreshDesk) was heading product management at Zoho earlier.

They just separated out Servers in Endpoint Central, where servers now require a different license. My use of the product will not change, the price of renewal goes up 12%. I'm paying more this year for the same thing. Strategic pricing indeed, lock'em in and crank'em up.

Also, Redhat and CentOS are 'servers' under this new licensing, but Ubuntu is not a server.

I've found Endpoint Central to be rather buggy, and not really improving over time, they just keep introducing new bugs.

Endpoint Central, now with arbitrary pricing.

The book "The Bell Curve" basically expressed the same point -- with data-- as yours here. And yeah, you are right. But then everyone is terrified by it, and hence the outcryand the name calling.

Wow, I thought this book had been burned by zealots and its ashes buried long ago. Thank you for resurrecting it.

Duh. Of course I should want a bigger population: more market for my business, more chances for me to mate, and more people I can talk to and learn from.

It's a no brainer, no ?

>> Avalonia's big money-maker is their drop-in replacement platform for WPF, which allows you to basically take an old WPF application and turn it into a Windows/macOS/Linux/web application with two lines of code, if you're willing to pay the price

Forgive my ignorance. But what "price" you are talking about, money, or dev time spent to root out the kinks?

I have a WPF application running on Windows, and I am thinking about porting it to Avalonia for the purpose of cross platform. Just for the background

Money, specifically $20k per app per platform (assuming you're not a small startup). That's Avalonia XPF, though, not the open source component; XPF is an alternative platform to target that'll turn WPF into Avalonia without rewriting any code.

If you're willing to rewrite/port code, you can use the open source stuff and get the benefits for free, of course!

It is a few thousand USD/EUR. It is pricey but inline with most commercial WPF components.

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