matmatmatmat

Yes, normally in a case where data were later shown to have been taken incorrectly, you would remove just the incorrect data but leave an unmodified copy of the old data available somewhere. Or, just leave a very prominent note about the change with a detailed explanation somewhere else. You would not take down everything because 1. That would deprive taxpayers of the correct data they had already paid for, and 2. That would mess up the data ingestion pipelines of the researchers who depended on the data.

Some more examples: Saving Private Ryan, All Quiet on the Western Front, The Deer Hunter.

Personally, I would also include Schindler's List.

I can't speak to most of what they do, but they seem to be at the forefront of quantum computing.

I've wondered this, too. I think the market must just not be big enough to support other players?

Roselle St (where Fabric8 Labs has their office) is the most innovative street in San Diego. I don't know what it is about that particular street, but a ton of great companies have come out of there.

Yes, labor is the killer cost of these installations, IME. Labor can easily be 50% or more of the total cost.

This uncertainty should be accounted for in the confidence intervals of their stats.

Bokeh has support for WebGL. We had to switch away from Vega/Altair when a project hit around 50,000 data points in a plot, but under ~5,000 data points Vega/Altair was still good.

It's actually even worse in SDG&E territory. A kWh costs around 32 cents, but "transmission" and "distribution" are again twice that. The end result is about $1.00 / kWh.

"If you give me six lines written by the hand of the most honest of men, I will find something in them which will hang him." -- Cardinal Richelieu [1]

[1] https://history.stackexchange.com/questions/23785/what-did-r...

Well, I look forward to benefiting from this nice work when the next Debian Stable release comes around.

Makes sense, but would this be so egregious that they had to fire him on the spot?

Unless you're just a dyed-in-the-wool Elon Musk fan, in which case it's 5D chess.

Can I ask where you're living?

This is such a wasted opportunity, not just for the US, but across the Middle East. I guess Jordan is availing themselves to some degree, though, but it's also out of necessity, due to the refugees living there.

My understanding is that prior to the Iranian revolution, there were Israeli experts working in Iran on drip irrigation methods. Of course, they had to get out pretty quickly.

Ah, you would be right, it appears I have a J1772 at home. I did not know that the CCS is a superset of the J1772 connector.

I don't get the hate for the CCS connector? I use it multiple times a week, it works fine. Now and then I come across a charger that refuses to start, OK, the connector is worn. I suppose someone will come along and fix it.

I have one in my garage; it does not sag under its own weight.

It so happens I recently took a Pixel 6 Pro and a Canon 80D on a trip abroad. I used a rebuild of the stock camera app that does away with the automatic over-sharpening that the stock camera app has, and with the 80D, I used the EF-S 15-85 mm lens that (I believe) used to be the kit lens for the 7D. I also used the EF 70-300 mm non-L lens.

There is, in my opinion, no question that the 80D takes sharper pictures in daylight. It's just hard to beat a sensor that's that much bigger. The lenses, also, just have way, way more light gathering power.

Now, in dark places, at night, I used the P6P more, and that worked better than the 80D. But I'm glad I had the 80D for the big landscape shots and for the tight shots of people's faces.

The A7 III is way lighter and smaller than the 80D, and takes way better pictures. I would suggest considering finding a space for it in your bag. At least take a few pictures with both the P6P and the A7 III and view them at 100% to see if you're happy with the results.

Question on the ML side of this post: How are these "parameterizations" used? Is this really just feature engineering with a new name? Are they including this information when training the model?

In the article, they mention using the new labels to build a "more balanced" dataset -- is this a realistic possibility in practice when most teams still have a dearth of data?

With Germany, in particular, I think there was also a lot of pressure from Green parties.

In any case, I would agree it looks like a mistake in hindsight.

Unless you capture it, as Amsterdam has been doing.

$10 MM of compute doesn't seem all that out-of-reach for most "mid-size" companies, especially if the result is economical.

50% of us are below the median. Depending on the distribution, there could be many of us or few of us below the mean.

Now, does the employer use the median or the mean to evaluate their employees? Interesting question..., I don't know.

Well, if you'd permit not getting into details, I'm not exactly a total non-expert.

This isn't really here or there, but I've recently been going through the deeplearning.ai course by Andrew Ng and friends, and at the end of each week, there is an interview with a luminary in deep learning.

A couple of weeks ago it was Andrej Karpathy. I got about three sentences in when I realized this guy is really, really smart. The way he spoke about neural nets and the problems he was working on suggested to me a deep and nuanced understanding, and a way of thinking that always tries to expand that depth and breadth.

Anyway, I figure if a guy like that couldn't make it work after so many years, even with a team that surely has other strong players, then it's just out of reach for the time being, with the hardware they're constrained to. It's even possible that deep neural nets will just never be able to do FSD at a level that will gain broad acceptance and some new architecture will be necessary.

Legitimate question.

> In a purely market-driven world Europe would not be investing in solar.

Well, maybe, but there's more to a market than buy and sell price. There is also the cost of external energy dependency, for example, or environmental degradation.

Man, ever find someone who's interested in all the same things as you but has had time to explore them, correctly, and even publishes the results?

What an amazing find, this blog, especially wing optimization (as you pointed out). I hope this guy gets the resources to run free with his work and just create incredible things.

These people had no shame, did they?