yellowcake0

Good lord, AI engineers get paid a median salary of $243,500, while non-AI engineers only get paid a median of $166,750, how can it be so much more? Is it because AI jobs are more concentrated in big tech?

Hedge funds exist to manage risk. Suppose I offered you a choice of either a guaranteed 10 million dollars, or a 50% chance to win 20 million dollars, which would you choose? Probably option one, now suppose I slowly increase the dollar amount of option two, at what point would your choice flip to the second option? That point will not be the same for everyone, and its expected value minus 10 million is called the risk premium.

Because of the decreasing marginal utility of money, many wealthy people are interested in capital preservation, in other words, they're willing to underperform the market if it means a significant reduction in volatility. Hedge funds can provide this type of service.

One of my favorite math books, there's also the companion text, https://web.mit.edu/~jadbabai/www/EE605/additional_exercises..., which contains a lot of interesting applications, presumably compiled by Boyd himself and his colleagues over the years.

That's admirable that you didn't spit in anybody's food, but why is it stingy not to tip for counter service, or did you have wait staff at your cafe?

Well it's certainly in keeping with the view he has of himself as an under appreciated scientific genius, however I don't think it makes for a very compelling critique of peer-review. Frankly, all his boohoo-hooing about being shut out of the in-group at Harvard probably has more to do with him being an insufferable narcissist, rather than any attempt by the establishment to prevent heterodox views in physics from reaching the wider scientific community.

I'm not sure total lack of knowledge can ever be encoded into a prior distribution, and if it can, I think Jeffreys prior makes a more compelling case than a uniform prior. After all, to believe that all possible values of the prior parameter are equally likely, is to believe that all possible values of its square are not.

This isn't always possible, but sometimes you can define what's called an improper prior p(µ), such that even if ∫p(µ) is not finite, the posterior distribution p(µ|x) is.

A common example is when p(x|µ,v) is a Gaussian dist. with a prior on the mean set to p(µ)=1.

It is indeed a sorry state of affairs - even venerated journals such as Nature regularly publish papers which contain methodological errors so egregious as to be considered fraudulent and deserving of retraction.

There's also a lot of second-rate research published which is likely of no value to anyone, and only serves to clutter things up and make it more difficult for researchers to sift through the literature.

During graduate school I interacted with academics working in math education who felt similarly, that math should be taught through essay questions, e.g. "explain the concept of a limit", and the like. I've always felt it was a deeply misguided pedagogy and I hope it does not become popular. Solving well crafted exercises requires a deep understanding of the material, it's unnecessary to check understanding in some other way.

It sounds like it is working for that company so more power to them I suppose, and I've certainly done my fair share of coding tests and take home assignments, however I consider it personally disrespectful to automate the initial interview round in this way. If you're asking me to put in work, even if it's an ostensibly short task, I want to talk to someone first.

A DB Cooper inspired ending for Don would have been great, and possibly a more fitting conclusion to his story arc. The show began to decline in quality in the 5th season, and really started to come apart at the seams by season 7b.

At the time of airing there was also some speculation that upon moving to LA Megan was going to get murdered Sharon Tate style, as in one of the scenes she wore a red star shirt identical to the one Sharon wore in her Esquire photoshoot, but that also never came to pass.

> It's important to know whether or not the authors picked BsaI & BmBI blind, before looking at the genome.

You could never convince me that these restriction enzymes were picked blindly, no bioinformatician I have ever met does science this way. There is a preliminary period of exploratory data analysis which is done before any hypothesis is put forward, and data dredging and leakage are rampant in the literature.

That's not to say that the spacing of BsaI/BsmBI restriction sites isn't noteworthy, just something to keep in mind.

To your point however, could someone comment on the suitability of BsaI/BsmBI for the in vitro assembly of synthetic coronaviruses? Is it all just about finding sites in the genome at the right locations which can be turned into restriction sites without disrupting any existing functional genetic elements? or is there more to it than that. If a research team were to come along and decide they wanted to engineer their own coronavirus, how likely would it be that they would choose these restriction enzymes?

This reminds me a bit of the New Math pedagogy, popular in the US during the 1950s-1970s.

Without the proper context, group theory and abstract algebra are deeply uninteresting subjects. It would be like trying to read Bertrand Russell before you learned your ABCs, ridiculous. It's important to start with numbers because they are familiar.

I know the contribution of the higher order imaginary terms are negligible in the result, but dual numbers are the more appropriate choice in this instance correct? since the higher order terms will vanish.

Coffee in NYC has gone up by a significant amount, both at places like Starbucks and canned coffee that you can buy at CVS or the grocery store. I know this because I buy it everyday, and have been for several years.

what a terribly written, self-indulgent article. Basically unreadable.

This really is putting the cart before the horse though, we will have whole genome assembly technology long before we understand functional genomics well enough to do the type of restorative genetic engineering that you propose.

Your coworker from MIT left to be a quant/software engineer at a hedge fund, or was the role non-technical?

Writing det(W) in terms of an implicit parametrization of the eigenvalues is elegant, I think it's unlikely there's a better approach.

Brute-forcing it would be to write down the multivariate polynomial in full generality, as there would be no way to break it up using the logarithm.

They are used quite a bit in computational genomics. Indeed, genomics is full of latent variable problems where one has a good model for the underlying phenomena but often not a lot of labeled data.

> MusiCares, a charity that helps musicians recover from addiction

Of all the causes in this world, this has got to be just about the least deserving

both R and Matlab also use 1-based indexing, if anything among languages used for data science and scientific computing, it's Python that is special.

You may also be interested in the Yeast 2.0 project,

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5894084/

which is an attempt to redesign the genome of the model organism S. cerevisiae, i.e. standardize codons, remove junk DNA, etc.

Well, depending on how broad your definition of life is, viruses have the most stripped down genomes of all. In the smallest viruses, with genomes of just under 10kb in length, nearly every basepair is dedicated to either infection or replication. In fact, they are often so compact that open reading frames are interleaved, in order to provide more functionality without increasing size.

Scientists often refer to viruses as "obligate", in order to sidestep the question of what is life, as most have no interest in the topics which occupy philosophers. In any case, they are non-cell based, for whatever that is worth. I imagine in a non-hostile environment, even the infection functional would be shed, and you would be left with just replication, which is the fundamental component beyond which no further reduction in complexity can be made.

I know for me personally YouTube Premium is well worth the $11.99 per month, no way I would ever consider going back.

That's an odd lesson to take away from your anecdote about Bob. What Bob should have done was just told a white lie that wouldn't have raised any red flags or follow up questions, and left it at that.

There will always be a stigma around mental illness, it's human nature, not some social construct, and I would 100% lie to you about something like that and not feel the least bit bad about it.

gets is not a contraction, it's the conjugation of the verb "to get" when the subject is singular.

the big three are housing, healthcare and education

You realize you can go to food banks and soup kitchens right?

> But you make the assumption that the data can be generated by your model

Yes

> you also make assumptions about the parameter distribution

No

> your variance estimate only holds asymptotically

Don't follow