Candidates should have a PhD in a relevant field

I'm really curious as to what constitutes a relevant field. The 3 people you list are an economist, a conservation biologist, and a someone with a doctorate in geography. Presumably those are relevant fields, but I don't know what they have in common exactly.

I don't know what to think about this. You're new and you have sort of unconventional funding and a really broad mission statement. I'm not really sure what sort of research you're looking for or what journals it would be published in. I can't tell how much of this is science and how much of this is economics or political science and your institute is under the umbrella of the Arts and Humanities Research Center. What sorts of positions do you envision your post-doctoral fellows taking two years down the road?

This is definitely interesting, but I'm not sure that I have any actual idea who you're looking for and having read your website and downloaded the job listing and read the bios of the people involved, I'm still not really sure. I can't figure out whether this seems sort of vague and confusing because it isn't directed at me or because you're still sort of figuring out the shape of the group yourself.

Hence, I'd like to take this opportunity to appeal for a charitable reading of posts of this nature

Duly noted, thanks. This kind of tone deafness seems to be a pattern here in the LW-sphere, however. For instance, look at this:

http://lesswrong.com/lw/lco/could_you_be_prof_nick_bostroms_sidekick/

If funding were available, the Centre for Effective Altruism would consider hiring someone to work closely with Prof Nick Bostrom to provide anything and everything he needs to be more productive.

Really?

An appeal to charity in the reading of "public-facing, external communication" is a little odd. Public-facing means you can't beg off on social incompetence, being overworked, etc. You have to convince the public of something, and they don't owe you charity in how they read your message. They will retreat to their prejudices and gut instincts right away. It is in the job description of public-facing communication to deal with this.

Ok, let me see if I can help.

Aside from the fact that this was an incredibly rude, cultish thing to say, utterly lacking in collegiality, how do we even judge who a 'mere mortal' is here? Do we compare CVs? Citation rank? A tingly sense of impressiveness you get when in the same room?

Maybe people should find a better hobby than ordering other people from best to worst. Yes, I know this hobby stirs something deep in our social monkey hearts.

They've also released their code (for non-commercial purposes): https://sites.google.com/a/deepmind.com/dqn/

In other interesting news, a paper released this month describes a way of 'speeding up' neural net training, and an approach that achieves 4.9% top 5 validation error on Imagenet. My layperson's understanding is that this is the first time human accuracy has been exceeded on the Imagenet benchmarking challenge, and represents an advance on Chinese giant Baidu's progress reported last month, which I understood to be significant in its own right. http://arxiv.org/abs/1501.02876

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe, Christian Szegedy

(Submitted on 11 Feb 2015 (v1), last revised 13 Feb 2015 (this version, v2))

Training Deep Neural Networks is complicated by the fact that the distribution of each layer's inputs changes during training, as the parameters of the previous layers change. This slows down the training by requiring lower learning rates and careful parameter initialization, and makes it notoriously hard to train models with saturating nonlinearities. We refer to this phenomenon as internal covariate shift, and address the problem by normalizing layer inputs. Our method draws its strength from making normalization a part of the model architecture and performing the normalization for each training mini-batch. Batch Normalization allows us to use much higher learning rates and be less careful about initialization. It also acts as a regularizer, in some cases eliminating the need for Dropout. Applied to a state-of-the-art image classification model, Batch Normalization achieves the same accuracy with 14 times fewer training steps, and beats the original model by a significant margin. Using an ensemble of batch-normalized networks, we improve upon the best published result on ImageNet classification: reaching 4.9% top-5 validation error (and 4.8% test error), exceeding the accuracy of human raters."

Seth is a very smart, formidably well-informed and careful thinker - I'd highly recommend jumping on the opportunity to ask him questions.

His latest piece in the Bulletin of the Atomic Scientists is worth a read too. It's on the "Stop Killer Robots" campaign. He agrees with Stuart Russell (and others)'s view that this is a bad road to go down, and also presents it as a test case for existential risk - a pre-emptive ban on a dangerous future technology:

"However, the most important aspect of the Campaign to Stop Killer Robots is the precedent it sets as a forward-looking effort to protect humanity from emerging technologies that could permanently end civilization or cause human extinction. Developments in biotechnology, geoengineering, and artificial intelligence, among other areas, could be so harmful that responding may not be an option. The campaign against fully autonomous weapons is a test-case, a warm-up. Humanity must get good at proactively protecting itself from new weapon technologies, because we react to them at our own peril."

http://thebulletin.org/stopping-killer-robots-and-other-future-threats8012

I saw Ex Machina this weekend. The subject matter is very close to LWs interests and I enjoyed it a lot. My prior prediction that it's "AI box experiment: the movie" wasn't 100% accurate.

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For those that worry it's Hollywood, hence dumb I think you'll be pleasantly surprised. The characters are smart and act accordingly, I spotted fewer than 5 idiot ball moments.

Is FLI using this money to fund research proposals? Where would one send such a proposal for consideration?

This is good news. In general, since all forms of existential risk seem underfunded as a whole, funding more to any one of them is a good thing. But a donation of this size for AI specifically makes me now start to wonder if people should identify other existential risks which are now more underfunded. In general, it takes a very large amount of money to change what has the highest marginal return, but this is a pretty large donation.

Do we know why he chose to donate in this way: donating to FLI (rather than FHI, MIRI, CSER, some university, or a new organization), and setting up a grant fund (rather than directly to researchers or other grantees)?

"You guys" has absolutely none of the hostile/contemptuous feeling that "you people" has (at least for me). It's distinctly informal and (as you surmise) some people may interpret it as sexist.

I think I'd generally just say "you" and, if necessary, make it explicit what particular group I had in mind.

It hadn't occurred to me that you might not be a native English speaker; sorry about that. I guess it's one of the perils of speaking the language very well :-).