Taking my life into my hands tonight- at least I’ll go out with a bang.
1. A Bee’s Knees- gin, lemon, honey, and Angostura. 2. Some kind of fancy tater tot crudités 3. Salsify purée with green olive jelly and shaved leek 4. House bread and butter
Main courses- 1. Goat cheese and planed beet tart 2. Herb-crusted lamb with Parmesan funnel cake 3. Duck breast with pickled cherries 4. Some sort of coconut foam bullshit pre-dessert- I hate coconut.
1. Taylor Fladgate 40 yo Tawny 2. Chocolate soufflé 3. House petit fours 4. Some innovative local jam (?) as a gift
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Not to pick on this guy in particular, but there is a great deal of misinformation floating around re: DWAC. Fortunately for you all, I spent today reading the S-1, and as a SPAC expert I can confidently answer the question of “can Trump sell Monday” with a firm “idk, maybe?”
Here is their lock-up agreement, I’ve attached a screenshot of the relevant sections. Formal disclaimer that everything that follows is neither legal nor financial advice, I may have positions in securities mentioned, do your own research, etc. sec.gov/Archives/edgar…
This is pretty boilerplate, as far as these things go, which it of course is because SPACs mostly just use a standardized template. The three major conditions are as follows: can’t sell until the EARLIEST of: six months, five months of the price is above $12, or they get bought
I just attended a talk on the mathematics of diffusion image generation models and it blew me away. Takeaways: 1. The math is very “simple” 2. In fact, it’s so simple that this method *shouldn’t really work* 3. The fact it does says something very fundamental about the universe
The basic idea is you define a stochastic process X_t, where dX_t = a(t,X)dt + b(t,X)dW_t. Let X_0 be random noise and X_1 be, eg, vector of RGB values for an image. Interpolate and add noise to generate a sample X_t, do this for many images, and then you can “learn” a() and b()
To generate a new image, you simply pick a new vector of random noise and evolve forward your newly discovered SDE until you reach t=1, at which point you have a perfectly sensible image if you’ve done your job right, modulo various finicky fine-tuning bits.
Since it's Sunday and I'm bored, I figured I would finally, definitively answer the question of "why do people think the economic is bad (and is that the case?)". This is because it is easy to answer, and the answer is funny and will make many people mad.
First of all, we will ignore everyone on Twitter and look at objective data, in this case the University of Michigan's consumer survey asking what people think economic conditions are. Spoiler: People think the economy is very bad, worse than any time other than 1980 and 2008!
Ok, now let's think of all the variables that might cause them to think that and build a model. I picked the following:
Inflation rate
Inflation rate change
Unemployment
Unemployment change
Housing prices
Real wages
Dollar strength
Interest rates
Stock prices
and went from there
Junior data scientist interview question: Assume you generate points X = N(0,1); Y = N(0,0.1). Rotate the (x,y) dataset 45 degrees, so they look something like pic below (line is y = x). If you were to calculate the OLS regression y = b1*x + b0, what is E[b1] as n->infinity?
(this question and the answer were previously buried in my replies, don't cheat or i will bully you for it)
The responses to this were bifurcated between “this is a hard question no one would get” and “this is a trivial question everyone should get ”. Surely if “data scientist” means anything, it means you should be able to answer basic linear algebra and mathematical stats questions!
As I strive to provide #content for my followers, I typed up my ratings from this weekend. Of the 200+ wines I tasted, ~150 were producer samples of guaranteed quality, and ~100 of those were reds (I don't drink enough white burg to have an opinion). Editorializing to follow:
The scoring method was just A+ to F, since it needed to be simple enough to be robust to me getting smashed over the course of the tastings, since I didn't spit. The older wines were Friday, all the 2020s were Saturday.
It is probably not surprising that Dujac, Hudelot-Noellat, Salon, etc. had the best wines. However, I was very impressed with the Robert Chevillon NSG wines, and the Didier Fornerol regional appellations punched way above their weight. Denis/Arnaud Mortet was also great.
Doesn’t take a genius to read behind the lines here and conclude that the agencies most likely to have actual relevant data from China think it’s natural, whereas the one who would have the least (the FBI, a *domestic* agency) has the highest confidence it is a leak (“moderate”).
The current agency distribution is 4-2-2 natural-leak-undecided, and curiously despite the breathless reporting on the FBI+DOE the identities and arguments of the 4 is are unremarked upon, despite their evidence being persuasive enough that an interagency panel sided with them.
Also, look, not to be tweeting about COVID in the year of our Lord 2023, but doesn’t lab leak prove that all the things lab leakers were complaining about were justified? If it’s a dangerous engineered Chinese pathogen then of course vax mandates, shutdowns, etc. are a good idea!