Roughly: the demand is about 33-35GW. That’s projected to become 50GW by 2050 as transportation and home heating become electrified. So that’s the puck we’re skating towards.

Nuclear supplies a constant 10% of the demand today (more, if you count imports from France). The goal is to power 20% of the 50GW demand through nuclear. If it’s cheap, even more. Each of these Small Modular Reactors (SMRs) generates 470MW, so we’d need about 20 of them.

The plan is to set up a factory near Sheffield and produce the reactor parts like IKEA, so they can be assembled on site. The hope is that manufacturing and assembling the same product repeatedly makes people more efficient. That’s the main problem with nuclear - over budget and delays - that SMRs aim to fix.

I’m glad the UK is taking electrification seriously, and is investing in domestic industry that will hopefully export reactors if it’s successful. Some folks might look at the estimated date of completion (2035) and get discouraged, but I wouldn’t. The best time to plant this tree was 20 years ago. The second best time is now.

I don't get why AMD doesn't solve their own software issues. Now they have a lot of money so not having money to pay for developers is not an excuse.

And data centers GPUs are not the worst. Using GPU compute for things like running inference at home is a much, much better experience with Nvidia. My 5 years old RTX 3090 is better than any consumer GPU AMD released up to this date, at least for experimenting with ML and AI.

The reasoning, I think, was that humans can drive using sight and a little bit of sound, so an AI should be able to do this too.

Humans can do this because we have a very rich well-developed world model that allows us to fill in the gaps. We don't do it perfectly but we can do it decently well.

Modern AIs, or at least the ones small enough to be run on smaller machines that are economical to put in cars, don't have a rich world model like that. They're doing stimulus response backed by a database. That's going to break down at all kinds of edge cases.

The way to compensate for this is to give the car superhuman senses like LIDAR. The car is much dumber than a person but it can perceive its environment orders of magnitude better than a person, which compensates well enough that it has a chance of driving at least as well as a person.

The probability of getting a Horizon Europe grant allegedly (not official stats) is about 8.5% according to some friends, which may seem low. You need to write 70 pages following a Word template and the key goal is to cover answers to a large number of questions. Each proposal gets various grades across a range of dimensions, which get added up and if you obtain at least 13 out of a possible 15 points, you are eligible to get funded, read: "You will get funded if there is enough money." Often, there are several proposals that justly achieve 15/15, and because of that, many prosals that have 14 points and all proposals that have less may not get funded, simply because there just is not enough total funding available to fund all the technically eligible proposals. Having judged many proposals in AI / ML / search / "big data" / language technology etc. I recommend optimizing recall, i.e. aspiring completeness.

The application process is not easy, but you can get help: there are support agency in each member country, free online Webinars to help, hotline help desks as well as an ecosystem of paid consultants that typically charge about 3k€ to vet a proposal for you if you need that kind of service (I never used it).

The process is neutral and conducted professionally and with external oversight (consultants are hired as "rapporteurs" that report on process/procedural integrity in additional to the actual reviewers). I value the research officers of the EC as people of high competency, integrity and motivation (research money is tax payers money so it should be spent carefully).

In comparison, VC (and even more so business angel) funding is achievable with much less formal apparatus, often a short business plan and a convincing slide deck and demo can get people to a partner meeting if the time is right. But the criteria and process are much different, and ideas ready for public research grants are typically too early for VCs (but the EC wants to foster the creation VC-funded startups resulting from the disseminated research).

Except that Apple, Intel, Tesla, etc have all received US government investment [1]. TSMC is a product of the Taiwanese state! Government investment can be done well, and seeds excellent companies.

[1]: https://www.sba.gov/blog/2024/2024-02/white-house-sba-announ...