EricLeer

They are part of nvidia's profesional offering (rendering, machine learning). They are basically on which every large model has been trained (dall-e 2, GPT3).

I wonder how to use a devops flow for machine learning workloads. Something we are working on at my current job is how to balance the speed of releasing together with keeping data, pipeline and model versions aligned (where it for instance takes multiple days to release a new model).

Releasing new features which need a model retraining is currently a very jarring experience.

Personally I use notion for this. Not dedicated software, but the extra options in formatting/structuring and linking can make a document like this a lot more readible.

Yes, by the same mechanism burning waste also has a lower impact then letting it sit on a landfill (even excluding using the heat for something usefull like electricity production, or a heat network).

With current tech you can get fairly easily (not necessarily cheap) to 80% renewables penetration in Europe. The rest of the 20% could then be covered by coal, gas, biomass and nuclear.

Mind you if the goal is to get Russia out of the European gas market, by greatly increasing the amount of renewables we use the rest could be supplied by LNG + Norwegian/Dutch/English fields.

Recently the CoRecursive podcast did an episode [0] on the culture behind cocoa development and the big nerd ranch.

[0] https://corecursive.com/cocoa-culture-with-hansen-hsu/#big-n...

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What an interesting story! I was wondering if you where you also working in the quantum computing field back then, or if you just worked on this as a hobby. 6 years ago the entire quantum computing field was not hyped as much yet (this was just about when the ibm quantum experience started?).

Slightly related is the crashes[1], which collects reports of crashes in the local news. They do this because they feel that in the news cycle these are heavilly underreported (as compared to for instance a terrorist attack) and therefore they seem less as a problem (to for instance improve infrastructure to reduce the risk of crashes).

[1] https://us.thecrashes.org/

I'm selfhosting miniflux (from a raspberry pi) and am just using the web interface. It has been working great from computer, phone and tablet.

Ram usage is a lot better when using docker as a driver instead of a vm, which immediately reserves all memory you give it. see https://minikube.sigs.k8s.io/docs/drivers/ for more info

Still if you multiply that by 1.5-2 to get to a full fte, it is a high salary.

I wonder how these salaries where determined, if it is like you said that it was just devided by 4, or if there was some outside governance/input for it.

I still feel like if you would place a job ad for a babel engineer for an amount like that it would be filled instantly.