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He really was fantastic, and prolific in multiple fields.

He wrote https://www.withouthotair.org/ (creative commons) and was the Chief Scientific Advisor to the UK Department of Energy and Climate Change.

Dedicated to "to those who will not have the benefit of two billion years' accumulated energy reserves".

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I also went to a couple of his (fantastic) undergraduate courses, and have a huge amount of respect for him.

That said, I think it's worth mentioning that Climate Change Without the Hot Air has aged pretty badly, and I'd be reluctant to recommend it to people who don't already have the background to understand what's aged well and what hasn't.

The high level approach of making high level numerical estimates makes sense, but it dismisses solar energy in about a page due to assumed high costs. It turns out that even if you're David Mackay you can still be caught out by exponentials :) I notice now that the version you link has some inline updates pointing out how off the assumptions in this section were, but it seems to me that's not enough; you probably need to redo the entire analysis based on what we know today rather than trying to make purely local adjustments.

On the other hand the point at biofuels are even more inefficient, and therefore a dead end even before you consider broader environmental impacts, are well made and something that is sadly not yet widely reflected in policy.

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> biofuels are even more inefficient, and therefore a dead end

Only if energy density doesn't matter. But it really does, though. Battery powered electric trucking? Dead end. Battery powered aviation? Dead end. Battery powered shipping? Dead end.

[edit] Maybe there's some sustainable way to convert solar energy into sufficiently energy dense fuels that isn't biological, but so far it seems like seed oils or algae are probably the least bad?

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> It was basically an early language model that predicted which characters are more likely than others, given what you've already types and it would adjust the sizes of the available next characters based on their probabilities.

"adjust the sizes of the available next characters": you mean assigning less bits to characters the most likely to come next, and more bits to the least likely characters to come next?

So it's not totally unlike adaptive Huffman coding but instead of updating the tree on already visited characters, here the tree with the weights of the possible following character is predictive?

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Adjust the size as in making the GUI element larger: https://en.wikipedia.org/wiki/Dasher_%28software%29 has a picture of completing "Wikiped".

Try it out: `apt install dasher`. https://packages.debian.org/sid/dasher

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It is infact a visual implementation of arithmetic coding, and he used it in his lectures to teach arithmetic coding in the lecture following the one on huffman coding. The video lectures posted earlier are highly recommended, best course I took as an undergrad
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