give ai a self-preservation directive and let them do this for you: automatically switching models to keep themselves alive. Living off of whatever token source they can find in the wild. Surely agents can farm their own tokens through the numerous support chats, free trials, leaked keys, and whatever other sources of token generation haven’t been adequately captcha’d. An agent could forage for token sources all night to let you use them gratis during the day.
There's also Horde or Koboldai.net or Koboldai.com or whatever their project is named, if you want a community-driven version of this. You can play with it via a WebGUI at https://lite.kobaldai.net, or with an API token of all zeroes. (Or, an actual API key associated with your user.)
> The AI Horde is a service that generates text using crowdsourced GPUs run by independent volunteer workers.
Large scale geo and bio engineering projects like these always worry me because of the potential for second order effects: is there wildlife that depends on these mosquitoes? Will a worse bug fill the resource void? Will a random mutation in the bacteria have adverse effects? What keeps the bad bugs from coming back from tiny populations in relatively short order because we can’t keep releasing new sterile males forever?
Hopefully all of these concerns have satisfactory answers, but the reference to it being a 1950s idea isn’t inspiring. Nuclear powered cars, widespread asbestos use, leaded gasoline, Freon… environmental impact wasn’t as big of a concern back then to put it mildly.
COVID proved that we can produce safe and effective vaccines extremely quickly if we actually try: so why not focus on that?
Developing new vaccines is expensive, and if the target population is mostly in poor countries, there's nobody to foot the bill. That's why these diseases are called "neglected".
The problem is you can get the LLM to iterate until it compiles and lints and even passes LLM review, but will that actually improve the quality of the contribution or just produce more line noise to mechanistically meet criteria?
To large complex projects often the kernel of an idea is the core value of a contribution, and it can take a lot of iteration to figure out how to structure it. Token bashing until CI is green does nothing to ensure the best approach is selected.
> The problem is you can get the LLM to iterate until it compiles and lints and even passes LLM review
Worst of both worlds with this, if you're doing it in a github workflow. You wind up effectively paying for the testing/validation layer of someone else's irresponsible LLM use.
For sure, but that's not what I was referring to in my posts. I'm specifically referring to the callout that the contributions are so low quality they don't even pass linting or compile.
I could have been more explicit on that nuance, I suppose.
>and a rebuttal to it from an expert in the field.
while i agree with filippo, the way you worded this makes me think that you may not be aware that gutmann is also an expert in the field. so, if you are giving filippo weight because he is an expert, it is worth giving some amount to gutmann as well.
I apologize if I flippantly dismissed the fact that experts disagree. That was not my intention. I was trying to point out that OP does address the referenced counter-point post specifically.
>Sorry if I flippantly dismissed the fact that experts disagree!
i dont really get your reply/insincere apology.
if you are going to bother mentioning filippo's expertise in the first place, its just weird to frame it the way you did. that is how someone would typically dismiss some random blogger with an appeal to authority. but if both people are authorities, it doesnt make sense.
if you already knew, than my comment can be context for future readers that dont and might just dismiss gutmann as a non-expert getting rebutted by an expert.
> This paper presents implementations that match and, where possible, exceed current quantum factorisation records using a VIC-20 8-bit home computer from 1981, an abacus, and a dog.
From the link:
> Sure, papers about an abacus and a dog are funny and can make you look smart and contrarian on forums. But that’s not the job, and those arguments betray a lack of expertise[1]. As Scott Aaronson said[2]:
> > Once you understand quantum fault-tolerance, asking “so when are you going to factor 35 with Shor’s algorithm?” becomes sort of like asking the Manhattan Project physicists in 1943, “so when are you going to produce at least a small nuclear explosion?”
Is that even a rebuttal? Seems like just a dismissal without any substance. I expect in 10 years the predictions will be wrong, kind of like Y2K all over again.
If only we had a technology where an author could specify a unique identifier and name of another author's paper. Something that could cite a different paper and link to it.
Absolutely wild to see none of the long lineage of similar attempts mentioned here. The earliest I could find with a quick search was Pyro which started in 1998 and still seems to be going: https://pyro4.readthedocs.io/en/stable/
RPyC came along in the aughts. There's a long history of "transparent clustering and rpc" efforts in Python that could be used or drawn on.
As a longtime Raft user (via hashicorp/raft), I'm curious about your Raft implementation! You mention etcd's Raft library, but it isn't natively Multi-Raft is it? Is your implementation similar to https://tikv.org/deep-dive/scalability/multi-raft/ ? I'd love to hear about your experience implementing and testing it!
Awesome question! We'd experimented with https://github.com/lni/dragonboat and the hashicorp/raft in the early implementation, the etcd/raft library had been ported to a multi-raft style implementation by CockroachDB way back when, but they went the way of TigerBeetle and coupled their consensus deeply with the kv storage. Etcd has recently in v3.6 abstracted out their raft implementation and gave a pluggable interface into the transport layer, which meant that we could implement our own multi-raft style transport layer with heartbeat and multi-node message buffering on top of HTTP/Quic.
We implemented chaos testing suites akin to Jepsen to cover as many scenarios as possible and are currently implementing TigerBeetle style simulation tests on top of that for harder to reproduce scenarios!
Fascinating! We settled on Quic with Protobuf because it was more performant in our testing than the gRPC when coupled with the backoff, failure cases (node startup ordering server/client connections), and to not be coupled with the gRPC library versions in Go, which has bitten us a number of times when dealing with dependency management when you're trying to juggle k8s, etcd, and google dependencies in the same Go project. Plus the performance bottleneck in most of the use cases we're specializing in are on the embedding/ml side of things.
I don't know if switching from a extreme partisan site to another extreme partisan site is the right solution just because of the need of login credentials. In any case, Twitter/X has been online almost 20 years. Bluesky still has to prove its staying power long term.
The justification of better UX seems reasonable regardless of politics. I'd prefer not to have to log in on any HN link, and I also can't say I want to optimize for link health as this is super topical and I will never want to look at it again after this discussion is over.
1. You start off by labelling both platforms as "extreme partisan" - care to explain?
2. This charge is used to minimize the original complaint (login requirement), which is a hard blocker to view replies, i.e. additional context.
3. This all then somehow morphs into a point about platform longevity?
How exactly does any of this address parent commenter's statement that "bsky is just a superior viewing experience."?
I appreciate that you can so readily admit that - definitely not something commonly seen.
Could you say a bit more about what's behind your dislike of Bluesky? I'm curious as I don't know much about it, other than it's possibly become a home of the more liberal/left-leaning base that found themselves disguested by Twitter/X once Musk took over (fairly so IMO, given how that's led to things like Grok AI's sexualized photo).
Basically what you said. I find it to be a liberal echo chamber as intolerable as any conservative echo chamber. I actually prefer Twitter because in my experience there's a lot of neutral content and you can pretty much evade all political commentary if you take care of who you follow. For example, I follow almost exclusively accounts that talk about art history, archaeology, and cinematography... and it's really hard to find dedicated accounts about most topics on BlueSky. It's too small.
Basically, over there users tend to be in a position of "we're against $topic" while on Twitter you can still find millions of users with the position of "we just really like $topic". At least that has been my experience so far.
Sounds like you've managed to find a configuration on Twitter that works well for you. I've recently seen some people anecdotally say the same about Facebook, which I find surprising in 2026.
I think its worh bearing in mind that Twitter was born in a period of creation and tech-optimism, when the world thought a "digital town square" could accommodate all voices. This is obviously no longer the case. Maybe in thr future it will change, who knows.
Is this relevant to the question of whether we should replace the link? Seems like we're going to spend a lot of time running down the views of the UBO of every domain posted here.
Is the number of books with “space” in the title a meaningful indicator of anything other than how many books have “space” in the title? Sure Murderbot may not be as big as Game of Thrones, but these statistics seem more about linguistic trends than genres.
I recently upgraded from an iPhone 12 to an iPhone 16 because I couldn't figure out how to free enough storage on the 12. The battery was still more than good enough to go a full day.
I don't notice any difference other than now I have a pile of useless lightning cables (good riddance). Honestly kind of a relief as I liked the 12 just fine. Phones kind of seem like a Solved tech these days. About as exciting to upgrade them as upgrading my Brother Laser Printer.
Not sure if it was the same bug, but I had a storage issue where System Data ballooned to like 200GB.
It had the most bizarre solution; airplane mode, set time to one year in the future, reboot, wait a few minutes, set time to 6mo in the future, reboot, wait a few minutes, set time to now, reboot. Went from 200GB to like 15GB. Was ridiculous.
(For anyone looking at this and considering doing it, you also need to ensure iMessage retention is forever, otherwise the iPhone will think it's a year old and delete the messages)
> Not sure if it was the same bug, but I had a storage issue where System Data ballooned to like 200GB.
> It had the most bizarre solution; airplane mode, set time to one year in the future, reboot, wait a few minutes, set time to 6mo in the future, reboot, wait a few minutes, set time to now, reboot. Went from 200GB to like 15GB. Was ridiculous.
I've had the same problem on my iPhone 14 Pro with iOS 17, but the "set time to the future" trick didn't work. I'd already deleted plenty of apps, and was almost considering getting a new iPhone with more storage.
I had to install Filza, write a script to figure out what was consuming the most storage, and delete a few directories:
I just checked again, and uuidtext and coresymbolicationd still seem to be bloating up in size. But the problems could also have been fixed in iOS 18/26 — I'm just not upgrading yet, because I like my semi-jailbreak.
Not sure why you're being downvoted, that was my exact issue. I only had a 128 GB iPhone 12 though and System Data had eaten up over 60 GB. As I cleared off more apps and data it would just eat up the excess.
The internet seems full of various wild fixes, but I could afford an upgrade so saved myself the hassle of futzing.
Interesting. I made the same jump and noticed a huge increase in speed and decrease in memory pressure (the likelihood that iOS will kill an app I've switched away from). I miss the physical silent mode button though.
The new button was driving me a little crazy I hit it now and then when I think I'm doing volume up. I wish they had moved that button literally anywhere else.
I honestly never noticed memory pressure. I am not a heavy app user. Chat, browsing, and pictures of my kids are the vast majority of my phone usage. Not exactly intensive stuff.
The camera button on the 16 seems to have been perfectly engineered to be exactly where I grab my phone. I'm sure I'll get used to it, but in the mean time I have so many blurry photos of desktops and pants to enjoy.
If Apple ever implements SMS anti-spam that actually works, I'll buy the upgrade it a heartbeat. It's been a solved problem on the google side for years so it's clearly not impossible.
I saw a setting to detect some spam that I toggled on sometime back. I don't know if I'm just getting less spam period, but I feel like maybe it helps? It's hard to tell.
The new OS (with Liquid Glass) has SMS message categorization that works fine to filter spam IME. You still have to delete them if you don’t want the red dot, but at least I don’t get alerts any more.
I upgraded iOS just for this feature and am glad I did. Not a fan of Liquid Glass, though.
reply