This is how I would describe my experience. Sometimes it’s crunch time and most of the time it’s fuck around time. After crunch time I always throw a tantrum about how if we only bothered with planning we could largely avoid it.

Probably not. Electron is popular not just for its cross-platform support, but also that its skills are highly transferable from existing web dev.

Instruction decoding takes space and power. If there are fewer, smaller transistors dedicated to the task it will take less space and power.

Well, not exactly. You have to remove instructions at some point. That’s what Intel’s x86-S is supposed to be. You lose some backwards compatibility but they’re chosen to have the least impact on most users.

I also haven’t wanted an Intel processor in a while . They used to be best in class for laptops prior to the M1, but they’re basically last now behind Apple, AMD, Qualcomm. They might win in a few specific benchmarks that matter very little to people, and are still the default option in most gaming laptops. For desktop use the Ryzen family is much more compelling. For servers they still seem to have an advantage but it’s also an industry which requires longer term contracts that Intel has the infrastructure for more so than it’s competitors, but ARM is also gaining ground there with exceptional performance per watt.

Exactly. Adding a third should be much simpler than a second.

As a fellow risc-v supporter, I think the rise of arm is going to help risc-v software support and eventually adoption. They’re not compatible, but right now developers everywhere are working to ensure their applications are portable and not tied to x86. I imagine too that when it comes to emulation, emulating arm is going to be a lot easier than x86, possibly even statically recompilable.

I’m both surprised and not surprised that ever since the M1, Intel seems to just be doing nothing in the consumer space. Certainly losing their contract with Apple was a blow to their sales, and with AMD doing pretty well these days, ARM slowly taking over the server space where backwards compatibility isn’t as significant, and now Qualcomm coming to eat the windows market, Intel just seems like a dying beast. Unless they do something magical, who will want an Intel processor in 5 years?

All else being equal, a complex decoding pipeline does reduce the efficiency of a processor. It’s likely not the most important aspect, but eventually there will be a point where it does become an issue once larger efficiency problems are addressed.

We stuck to x86 forever because backwards compatibility and because nobody had anything better. Now manufacturers do have something better, and it’s fast enough that emulation is good enough for backwards compatibility.

I think it is this way because Apple thought it would be misleading if the option was “deny tracking”, because there isn’t a specific technical mechanism to ensure that. It’s unfortunate but I’d rather it was honest than lied.

If it ends up being ruled that training an LLM is fair use so long as the LLM doesn’t reproduce the works it is trained on verbatim, then licensing becomes irrelevant.

As someone who primarily uses Unix-like systems and develops cross platform software, having windows as a weird outlier is probably best for the long term. Windows is weird and dumb but it forces us to consider platform differences more explicitly. In the future if a new operating system becomes popular, all the checks that were implemented for windows will make it a bit easier to port to newer systems.

If something like that were to work, a lot of effort would need to be put into minimizing the UI friction. I could see something like: uploaders add topic tags to their videos, and an AI runs in the background to generate and apply new tags based on the content (most people would not understand how to properly tag content). An AI would also be used to create a graph of related tags, where similar or closely related tags are nodes joined by an edge. Then, on first login the user is prompted to pick some tags to start with. Over time, the client uses the adjacent tag graph to fine-tune users’ tags, on device. The idea here is that we could get a decent algorithm that can recommend new stuff based on what the user watches, but keep that data processing of user-specific content local. Then, the client would also have an option the user could enable that would contribute their client’s tag information back to the global tag graph, improving the global tag graph for everybody. This data could also be combined with other users data at the instance level to somewhat anonymize the data, assuming it is a large multi-user instance. If you were to host a single user instance, you’d probably not want to contribute to the global tag graph unless you’re ok with your tag preferences being public.

It’s a bit tricky but I think a privacy preserving algorithm is possible. Simply put, the more data available, the better an algorithm can be.

I think the easy discoverability on these platforms is part of what makes them so popular. Using TikTok or similar, a user typically wants to be shown new things, it maintains a sense of novelty that keeps users constantly engaged. Having to do this manually would be a huge negative.

The algorithms are what makes these services. Most interactions aren’t searching and selecting something specific or intentional, they’re just opening a fire hose and expecting the algorithm to pick content they find entertaining for them. It requires the algorithm to have a lot of information, both about the specific user, and about similar users.

Most people shouldn’t self host. It’s a hobby for people who want to do it, and there are benefits, but spending 3 hours on a weekend fixing stuff is not how most people wish to spend their time. Furthermore, it’s not a good use of most people’s time. We split labor up into specialties, forcing people to do work outside their specialty causes pointless inefficiency. I agree with what other commenters have said in that a better approach would be to have more small businesses hosting federated together, and anyone not inclined to self host should just purchase service through one of those many small providers instead.

I use it to describe a variety of things, but usually it’s related to servers not being able to handle load rather than an outright crash, but I’m not strict about it. Laos balancer failures could be it, could also just be that something was really I efficient but wasn’t noticed until it went into production.

Reddit wants data, as personal and uniquely identifiable as possible, as collecting and selling that data is a core component of their business. To a significantly lesser degree they also want to minimize spam. VPNs reduce the amount of uniquely identifiable data they can collect (really just an IP address they/their customers can use to match your Reddit data to data from other sources. VPNs also reduce the efficacy of using IP blocks to stop spammers, but I really don’t think Reddit cares too strongly here unless the spam interrupts normal usage, as spam that looks human-like can be sold as user data.