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This is not how stocks work at all outside of stock offerings…

If you use a new cloaking image for each picture you upload to social then they will all be embedded in a different location for a given feature extractor and an adversary wouldn’t be able to reverse search for linked pictures—that’s at least my understanding of how the method would need to be used. But if you keep using the same cloaking image, your adversary could definitely learn that process and effectively undo it.

This should be somewhat mitigated if you keep using different cloaking images, no?

There is definitely a main function in the CPython source code.

Thanks for this—easier to digest than other posts I’ve seen. The ability to restrict interfaces to specific types is pretty cool (unique?) but otherwise seems like generics as usual, but with a distinct Go flavor. Looking forward to using this and cleaning up some boilerplate!

Why would you prefer the risks of editing versus the risks of preimplantation screening? Editing would be strictly riskier unless there’s really no alternative (unlikely but possible)

Same--going to a market feels like a very human experience.

This opinion piece is citing a lot of evidence and blatantly misinterpreting it. At a minimum it defers to the IHME models as the reference standard but they’ve performed terribly; similarly it cites Ioannidis from Stanford who has consistently failed to predict the actual consequences of the disease and is being ridiculed by the scientific community.

Soon to be 100,000 dead in the US with lockdowns; how could it have been a mistake? The only mistake was not doing it earlier.

Hmm I’d say all the book clubs I belong to are social first, book second; one club spends the majority of each meeting roasting the people who haven’t read the book, another good portion debating our selection procedures, and a minimal amount of time on the book itself. Different flavors for different people!

I guess in my experience, the phrase is routinely used to refer to code availability and often the fact that a licensing fee doesn’t need to be negotiated or paid in order to run the code on our servers (either in an academic or corporate setting), which is a weaker requirement than the OSI definition.

Real usage by real people not particularly passionate about adherence to the OSI definition—to me this is its de facto meaning. I’m not saying it’s correct usage, but it’s definitely real and frequent.

It’s my impression a non-negligible number of people share the same understanding, evidence by the fact that this discussion apparently is recurring? Even those who corrected the Defold release language knew what was intended, even if they said it was incorrect usage of the phrase.

Your response assumed the number of people who use the phrase with a looser meaning is small; I just don’t think that is true based on my day to day experiences.

That there is any significant confusion at all means it is not de facto (and if something is right and true based on a definition I don’t think you can call it de facto either...).

The distinction really doesn’t seem that important for most use cases so it’s not that surprising a weaker, possibly more useful interpretation has become common...

Quite a remarkable lack of IANAL flags for a lot of people talking about false advertising/trademark law...IANAL but the minimal data I have suggests the phrase “open source” has very little protection (not strictly claimed on OSI website, no major track record of being defended in court, broadly accepted vague definition, unlikely to damage the trademarked brand’s image/rep).

Very different from falsely claiming the release is OSI compliant or whatever the legalese is...

This is a super pessimistic and misleading description of phase 2 & 3 trials; actual efficacious drugs do come out of the FDA review process. Many phase 3 trials are against standard of care rather than placebo and many are longer than a few weeks, particularly for treatments where efficacy is hard to prove.

There are legitimate concerns about efficacy (there’s research that suggests that evolution will help mosquitoes escape the gene drive effect, making it useful for only a short period of time) and about unknown ecological consequences (knocking out a primary food source in an ecosystem can have devastating health and economic consequences). That’s not to say it’s not worth it, but it is worth debating and figuring out how to do it correctly. I don’t think it’s fair to say there’s a silver bullet that is being held up by ignorant/uninformed/unethical skeptics.

In order to uniquely identify, not a lot of space! A recent paper puts it at 50 SNPs (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5785835/).

Describing your total unique genetic profile would obviously require a lot more space, and wouldn't be constant across individuals/ancestral backgrounds (e.g. there's more genetic diversity in people of African descent).

Not a given, particularly for people fleeing countries in crisis, disarray, or violent turmoil. Or if a parent died during the migration, etc.

It would mitigate this issue to an extent, but also introduces new challenges (for instance and as pointed to elsewhere: dealing with officially/unofficially adopted children). I'm not sure if there are published numbers on what fraction of adult asylum seekers are attempting to use children in this way, but the preoccupation with "solving" this particular issue demonstrates that either (a) that fraction is disturbingly high or (b) we'd like to make the process even more complicated for no particularly good reason. The trend of every policy along the border seems to suggest that (b) is more likely, which is upsetting.

You would only be able to select from those 5 backgrounds, however, and the predicted heights for those embryos will be drawn from a normal distribution; you can only "design" from what you've sampled.

On the other hand, if you sampled millions of embryos, you could find the rare few predicted to grow to be 6'5" person -- but this would be very expensive and basically impossible without synthetic embryos.

The models are predicted off of "~20k activated SNPs" - 20,000 separate mutations, most of which have really small effects on height. "Designer babies" are pretty far off (IVF is awesome and great, but not trivial, so it would be risky to do this just to make sure a baby will be...probably somewhere near average height). Engineering the right mutations with CRISPR/Cas9-based gene editing would be astronomically expensive (and is realistically impossible); filtering embryos for the right genetic background would also be incredibly expensive and probably impossible, as you'd be relying on the natural, stochastic arrangement of those 20,000 mutations to be in sync with the vision you have for your baby.