Comments URL: https://news.ycombinator.com/item?id=46194998

Points: 2

# Comments: 1

As for the battery swap, it costs the same to do it my self using this service or to take it to an Apple Store. I want to do it myself, otherwise I would just take it to the store and pay the same amount to have Apple do it.

I was asking to see if anyone else has had luck ordering parts and tools from this service recently. You have no information on the subject, why did you choose to comment?

Did you also run the same experiment on Chinese hosted R1? I am curious now if their system prompt is the same.

I confirmed with both banks that all entered information is correct, and they have no issues processing the transaction if submitted properly. They even ran test transactions using the exact information I provided, confirming that they would approve the transaction if submitted correctly. This suggests the issue lies with the repair store's payment processing.

Has anyone else faced similar issues? Is this program still functional for consumers? I reached out to their support and was told that I can pay for just the battery via PayPal, but I am not able to rent a toolkit via PayPal. And they refused to help me any further.

Is it me or them?

Comments URL: https://news.ycombinator.com/item?id=43807650

Points: 8

# Comments: 0

So, take an app like WordPress that you want to make “highly available.” Let’s imagine it’s a very popular blog or a newspaper website that needs to serve millions of pages a day. What would you do without Kubernetes?

Without Kubernetes, you would get yourself a cluster of, let’s say, four servers—one database server, two worker servers running PHP and Apache to handle the WordPress code, and finally, a front-end load balancer/static content host running Nginx (or similar) to take incoming traffic and route it to one of the two worker PHP servers. You would set up all of your servers, network them, install all dependencies, load your database with data, and you’d be ready to rock.

If all of a sudden an article goes viral and you get 10x your usual traffic, you may need to quickly bring online a few more worker PHP nodes. If this happens regularly, you might keep two extra nodes in reserve and spin them up when traffic hits certain limits or your worker nodes’ load exceeds a given threshold. You may even write some custom code to do that automatically. I’ve done all that in the pre-Kubernetes days. It’s not bad, honestly, but Kubernetes just solves a lot of these problems for you in an automated way. Think of it as a framework for your hosting infrastructure.

On Kubernetes, you would take the same WordPress app and split it into the same four functional blocks. Each would become a container. It can be a Docker container or a Containerd container—as long as it’s compatible with the Open Container Initiative, it doesn’t really matter. A container is just a set of files defining a lightweight Linux virtual machine. It’s lightweight because it shares its kernel with the underlying host it eventually runs on, so only the code you are actually running really loads into memory on the host server.

You don’t really care about the kernel your PHP runs on, do you? That’s the idea behind containers—each process runs in its own Linux virtual machine, but it’s relatively efficient because only the code you are actually running is loaded, while the rest is shared with the host. I called these things virtual machines, but in practice they are just jailed and isolated processes running on the host kernel. No actual hardware emulation takes place, which makes it very light on resources.

Just like you don’t care about the kernel your PHP runs on, you don’t really care about much else related to the Linux installation that surrounds your PHP interpreter and your code, as long as it’s secure and it works. To that end, the developer community has created a large set of container templates or images that you can use. For instance, there is a container specifically for running Apache and PHP—it only has those two things loaded and nothing else. So all you have to do is grab that container template, add your code and a few setting changes if needed, and you’re off to the races.

You can make those config changes and tell Kubernetes where to copy and place your code files using YAML files. And that’s really it. If you read the YAML files carefully, line by line, you’ll realize that they are nothing more than a highly specialized way of communicating the same type of instructions you would write to a deployment engineer in an email when telling them how to deploy your code.

It’s basically a set of instructions to take a specific container image, load code into it, apply given settings, spool it up, monitor the load on the cluster, and if the load is too high, add more nodes to the cluster using the same steps. If the load is too low, spool down some nodes to save money.

So, in theory, Kubernetes was supposed to replace an expensive deployment engineer. In practice, it simply shifted the work to an expensive Kubernetes engineer instead. The benefit is automation and the ability to leverage community-standard Linux templates that are (supposedly) secure from the start. The downside is that you are now running several layers of abstraction—all because Unix/Linux in the past had a very unhealthy disdain for statically linked code. Kubernetes is the price we pay for those bad decisions of the 1980s. But isn’t that just how the world works in general? We’re all suffering the consequences of the utter tragedy of the 1980s—but that’s a story for another day.

In any case, let's argue in good faith about this one specific moment you pointed out. The question in hand is if Gradient Descent in ML should be considered a "Search" problem. Lex argues that it is a "Search" problem and Jim is arguing that "Search" has a specific meaning in CS, and ML Training is NOT that.

Jim's understanding of the word "Search" matches my own. Search is a process of looking for a particular data or __specific__ outcome. What happens in ML during training could be described as optimization, filtering, and, obviously, training, but in no way does it fit the definition of "search".

For reference, my definition of "Search" corresponds to the formal definition described hear: https://en.wikipedia.org/wiki/Search_problem, Lex's does NOT, and this is what Jim was pointing out. He eventually gave up when he figured out that Lex was using a colloquial definition of search, not the technical CS definition of the same word, and "conceded" by saying "sure, if that's what you mean by search" or something to that effect.

I would appreciate if you wouldn't flag this comment, but rather engaged with it, like an adult. Thank you.

Thank you for highlighting that point in the interview. That's another excellent example of Lex being incompetent in the very Science he proclaims to have a PhD in. If you don't know that, you basically just proved why I chose not to get into this argument with you. And Jim didn't concede, he moved on from a really stupid conversation topic onto something else.

https://youtu.be/1CSeY10zbqo

That's just what I had a moment to find right now and it was well labeled and I remembered that moment. As for your other comments, my only possible response would be insulting, and I have no desire to insult you.