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Legit question and there would have been negotiations happening to exchange hostages for prisoners (like it was done in the past)

> What about border security?

What about it? I didn't say that Isreal should not secure its border. The entire reason why Hamas was successful in the first place was because the border was not secured because the troops were moved and Israel's security services didn't take the warnings and threats seriously that Hamas was planing such an attack.

> The game theory is absolutely clear here. When an attack of this magnitude is carried out, you need to respond with overwhelming force to cutoff the possibility of further escalation. Stop it cold

First, I don't think game theories applies in this conflict and second when did this ever work in the past? At least I would argue that the "war on terror" after 9.11 was anything but successful. Actually compared to the current reaction of Israel the reaction of the US after 9.11 looks very restraint.

> Restraint here is the significant effort that has been taken by the IDF to minimize civilian casualties.

That's a bold claim, looking at the number of civilian deaths in that relative short period of time. Yes I know that the numbers come indirectly from Hamas but they were relatively accurate in the past when they were confirmed afterwards. Most people say Hamas to blame for this because they hide behind civilians. However I would argue that it's neither morally right nor strategically smart to killing dozens of civilians for one Hamas operative. Also Israeli officials were quoted with: "We’re focused on maximum damage and not accuracy" (https://www.theguardian.com/world/2023/oct/10/right-now-it-i...).

But the mistakes happened way before by moving troops away from the Gaza border to West Bank to protect illegal settlements and also supporting Hamas as an opposition to PLO. Don't get me wrong. Don't get me wrong the world would be a better place without Hamas however your policy has to be strategic and not emotional (i.e. revenge)

For strength: I basically just do the "The Bridge by Barbell Medicine" (https://liftvault.com/programs/strength/bridge-program-sprea...) around 3x a week (sometimes a 4th General Practice Day). I started like most with 5x5 Stronglift probably 8 years ago but switched to this program around 3 years ago. The nice thing is that it has some variation and doesn't take too long. It consists of the big compound lifts so I think it's great for general strength

For Cardio: I started to do to 4x Zone 2 training on an indoor bike (https://peterattiamd.com/category/exercise/aerobic-zone-2-tr...) recently because a lactate test showed that I have horrible aerobic peformance. I blame it on Covid but I guess it's because after stopping with football/soccer due to a knee injury I virtually did no aerobic exercise. The upside is that a great aerobic performance has tons of health benefits (blood preassure, cholestoral, etc).

I train always in the morning (start between 6:30 and 7:00) before work in fasted state (time restricted feeding between 12:00-20:00) for cardio and with a pre-workout shake (creatine) on the strenght days. I am not a huge morning person but I got used to getting up early and the great thing is that even if my day was super unproductive one thing was accomplished and it's also quite compatible with social life (in case I want to do something after work).

Physically I am probably now in a better shape than in my 30ies and I plan to contineu to do this as long as possible

Additionally the typical workloads that run on our HPC system are often some badly maintained bioinformatics software or R/perl/pythong throwaway scripts and often enough a typo in the script causes the entire pipeline to fail after days of running on the HPC system and needs to be restarted (maybe even multiple times). Again on the on-prem system you have wasted electricity (bad enough) but in the cloud you have to pay the computing costs of the failed runs. Again cost transparency might force to fix this but the users are not software engineers.

One thing that the cloud is really good at, is elasticity and access to new hardware. We have seen for example a shift of workloads from pure CPUs to GPUs. A new CryoEM microscope was installed where the downstream analysis is relying heavily on GPUs, more and more resaerch groups run Alpafold predictions and also NGS analysis is now using GPUs. We have around 100 GPUs and average utlizations has increased to 80-90% and the users are complaining about long waiting/queueing times for their GPU jobs. For this bursting to the cloud would be nice, however GPUs are prohibitively expensive in the cloud unfortunately and the above mentioned caveats regarding job resource efficiencies still apply.

One thing that will hurt on-prem HPC systems tough are the increased electricity prices. We are now taking measures to actively save energy (i.e. by powering down idle nodes and powering them up again when jobs are scheduled). As far as I can tell the big cloud providers (AWS, etc) haven't increased the prices yet either because they cover elecriticity cost increase with their profit margins or they are not affected as much because they have better deals with elecricity providers.

https://www.phoronix.com/review/amd-ryzen-7900x-7950x-linux/...

Some lessons learned so far:

  - OpenStack is very complex     
  - It's less of a product and more a framework and you need a dedicated engineering team with cross cutting skillset     
  - You definately need a dev/staging environment to test upgrades and customizations  
  - Some of the reference implementations of OS servies (SDN) are fine for small deployments but if can replace them with dedicated hardware/appliances you should do that.

workout without breakfest does work, although if I go to very heavy weights, I tend to take a bit of BCAA before the workout.

Don't be too smart for your own sake when packaging your software. As an HPC administrator I stopped counting how many hours I spent installing scientific software with broken Makefiles, interactive installers, simple github dumps, unresolvable dependencies. Sadly this is quite prevelant in life sciences (I am looking at you bioconductor)

here are some more examples

Especially there are many options to play around with (projections, etc)

So in theory I should be able to mix and match web-components that are built using stencil, skatejs, polymer, or any other future opinionated web component library.

So is this also possible in practice and specifically can I mix stencil generated components with polymer ones (say use a paper-button inside a stencil compoenent) ?

1.) That might be populist opinion but surely is not comparable to what Hitler did. Or do you seriously claim that people like Sanders, Warren use the same rhetoric as Hitler? That's ridiculous. Hitler was blaming Jews and other minorities and the Versailles treaty for the bad economic situation in Germany. Interestingly Trump is doing the same thing (Nafta, China, Mexicans etc)

2.) The overthrow of the Libyen regime was mainly pushed and pursued by us Europeans (France, England, etc). The USA was in the beginning hesitant and eventually participated. Just to make clear: This was a stupid decision and Obama also admitted this as his worst mistake. Hitler never admitted a mistake or defeat (see Leningrad). Guess what Trump also does not admit

3.) Sorry, but that's part of geopolitics (just to make it clear: It's actually the reason why half of the world is fucked up by wars) and almost every powerful nation has done this in the past and will do this in future. So not sure what you are comparing here.

4.) So then almost all of Europe must have a Nazi healthcare system? Hitler was also a fascist and thus more an ally of corporations, banks and companies than of the people. Some of his policies could have been mistaken as socialist but in reality they were part of his plan to please the population (construction of highways, pumping money into the economy for short term gain). His entire ideology was built around a super-race and elites which is quite the opposite what a "socialist" healthcare system is all about.

5.) Citation needed for the fact that 2/3 of Americans dislike transgender bathrooms. Trump's policies (taxes, healthcare) are so unpopular that he can't even pass them with a Republican Senate and House. Apart from that Hitler tapped into a huge antisemitic sentiment that was carried by a wide majority of people. If that hadn't been the case, he would have never be able to create his Nazi regime. I also think this is the main difference to today. The alt-right, KKK and Nazi clowns are a minority - a loud one - but still a minority. So I don't think that we are facing another Nazi regime. Nevertheless you can clearly see similarities between Trump and Hitler behavior. The only difference is that Trump lacks the intellectual capacity (maybe Bannon has it) in order to pull something off that Hitler had done.

Also a pretty good read and recently discussed here: https://news.ycombinator.com/item?id=14661473

We will hopefully upgrade soon to the Newton release which will enable us to provide SaaS (Murano) and CaaS (Magnum) to the users. We will probably also evaluate Openshift on top of Openstack.

The biggest pain points is the integration with our existing HPC infrastructure (specifically the parallel filesystem/storage). We haven't really looked much at the code except of debugging some authentication issues, when we tried to integrate keystone with our core IT's AD, so we can't comment on that.

Additionally, the official openstack documentation (the commercially supported one is quite superficial) is often very confusing and it's very hard to find proper CHANGELOGS for each of the openstack components. Also we really don't like (or rather despise) openstack's issue tracker (Launchpad). It is very hard to find any existing issues, when we encounter some problems.

You are also right that some of the comp bio areas (CryoEM, protein folding, molecular dynamics) are well suited for GPUs

On the other hand many of the bioinformatics software solve a specific scientific question and usually are written by people with mostly non-computational background. They use higher level languages such as Python/Perl/R and people often don't have the expertise or time to implement them for GPUs.

However now that machine learning and deep neural network approaches are being picked up by the field, the workloads might change a and also there are frameworks that make it easer to leverage GPUs (Tensorflow, etc)