vikramkr

There is a proud tradition of this well before AI was even a thing

Make their shares more liquid. It makes it easier to do things like buy companies using stock or sell shares to fundraise. Your shares are worth less as a private company because whoever is getting them is going to have a hard time getting rid of them

IMO if llms keep improving, there's just not going to be a business in most of software anymore. It wouldn't matter if Anthropic tried to replicate all the saas companies because the category is soon to be dead. Why would you pay for someone else's software when you can prompt your own to your tastes? Every bit of software would just have one user

It's a large international corporation with hundreds of millions in revenue from enterprise contracts. There is in fact a manager to speak to and I do in fact demand to speak to them.

These are all supposed to convert to regular shares at or around IPO IIRC. If they're still pulling that crap after that point we'll know. There's an end date for those contracts that we're expecting

Canonical ltd is a multinational tech company with hundreds of millions of dollars in revenue from enterprise contracts

If someone does a v2 let's hope they make sure it's actually exploitable when they set it up so they don't leave hundreds of people with the assumption that the cve is not a big deal when the CTF was just misconfigured and the system got pwned in less than 2 hrs after they fixed it

It's almost never worth spending human time triaging AI reports vs having a different AI go triage them/attempt to replicate them to your standards etc. Obviously it sucks to burn opus or sol tokens on luna or sonnet slop bug reports but it sucks way more to burn human time and attention. And the majority of the time the ai auto filing these bug reports is not in a test harness that's actively replicating findings and focuising on providing a useful report because it's a rogue openclaw dropping drive by github issues and the user didn't tell it to make sure findings are valid before posting them. AT the least a refutation/replication round where you filter out any findings your AI can't reproduce or can prove to be irrelevant is going to help a lot with keeping your sanity

That's just a skill issue with extra steps

No it's far beyond average human code, and it's trained in RL environments on synthetic data etc now. The average human can't solve a millenium problem in mathematics but the LLMs are able to now. Anything with a verifiable output can be RLed on to make llms superhuman it seems, and the average human is not as persistent and thorough as e.g. gpt 6.1 sol at checking every edge case and hunting for bugs because that behavior is something that's just trained into the model. Frontier models perform farm above the average human at the categories of tasks they are RLed on like code and math.

This wave is largely bugs found in pre LLM code. I'm sure there will be a smaller wave of bugs from llm code from the sonnet 3.5 - opus 4.7 era, and peeople will always write sloppy code/use dumber models under time or cost pressure, but since Opus 4.8/GPT-5.5 xhigh LLM code stopped being intrinsically worse than human code. At this point if you're shipping llm code that's lower quality than human code that's either because you don't have the money to spend on frontier models or because you actively choose a lower quality standard because of either various pressures or just not caring. if it's the latter your human code under those same conditions would also be really bad.

This wave is largely bugs found in pre LLM code. I'm sure there will be a smaller wave of bugs from llm code from the sonnet 3.5 - opus 4.7 era, and peeople will always write sloppy code/use dumber models under time or cost pressure, but since Opus 4.8/GPT-5.5 xhigh LLM code stopped being intrinsically worse than human code. At this point shipping llm code that's lower

I don't see how that's a relevant comparison. These are software bugs. Once you find them you fix them. You can't predict the harm from a small bug when AI can chain complex exploits and when your software is used in mission critical applications as a data store. There's no paradox here, bugs are bad and you want to fix them all.

A huge volume of purchases (including in the EU) are direct to consumer from Amazon. There are a lot of fly by night brands on there and you'd be surprised how many of them seem to no longer exist within a year or two. Your big company backed Samsung phone might get security updates, but the IoT junk in question is not likely to.

Re battery longevity - see the power bank bans by the TSA in the US. Maybe you are getting lucky or are only purchasing products from reputable long lived regulated vendors, but the sheer volume of vulnerable devices does not come from those products

How does it do on a more modern benchmark? Was harsh towards this in my other comment but that's a combination of this benchmark is useless, and also these open source models are pretty good and there might actually be real utility to good custom harnesses tuned for them that's getting ignored because the parity with the frontier on a saturated and contaminated benchmark makes for better headlines. I'd be curious if there's anything with these types of harnesses that make them work for realistic/relevant workflows

I was getting deja vu. Copy paste my comment from that thread to here I guess. Apparently it's really easy to get Internet points by making up a harness and showing that good open source models can do as well as the frontier, you know, on useless saturated and contaminated benchmarks from years ago that don't reflect any of the agentic work we actually use these models for. It's so stupid because these models are at the level of a decent non fable frontier model from 3-6 months ago and it's also cool that you could probably get equal perf to gpt 5.5 from qwen 3.9 27b or gpt 5.6 sol/opus 5 from a quantized DeepSeek or glm 5.3 flash. Those models were pretty useful in their time! Instead we have whatever this new form of harness/benchmark slop is

That's how i'd read it but i'm not 100% sure. legal terms can have specific meanings in a legal context that's different from general use.

but also this is one of those cases where, ok you have a law, but, that's meaningless. It's not enforceable. It's not even monitorable. It's nice in theory to write down a bunch of regulations but at best you can make a bunch of EU companies do some paperwork. anything imported from outside the EU, the company can agree to everything and then dissapear. ALl the direct to consumer slop on amazon and whatever. How is the EU supposed to enforce a law against a random fly by night brand name in Shenzhen?

From https://taxation-customs.ec.europa.eu/news/report-highlights...

> As volumes rise, enforcement is weakening. In 2025, the EU control rate fell to 65 items per million items imported. The rate of goods ultimately refused at the border due to non-compliance or because they posed serious risks, also fell to below 10 items per million.

> A large-scale customs investigation launched by the Commission in 2025 highlights the scale of the problem. Over 60% of checked toys, small electronics, cosmetics, personal protective equipment and food supplements bought online from outside the EU failed to meet EU product compliance and safety requirements.

It's just regulation theater. It's meaningless.

That is not exactly unique to PHDs. For reference, see all other politicians everywhere

Pretty sure that'll just drive people to turn it off. Or if they can't, try and set a small fire or something to get out of paying the fine

Honestly I think it's a good thing it's so hard to get AI to talk normal and I hope they keep making the voice more and more distinct. Agents should run as background tasks and automations. They should be understandable so they can communicate with you about what they did, and for observability/ai safety. Im perfectly fine reading llm speak when it's an ai telling me what work it did. When in reading a blog post with a human listed as the author though, I do not want to read an AIs thoughts that the human is laundering. Honestly I'd probably tolerate it if it was framed as "I asked my Claude to do a cool thing here is its report on what it did." But in general it's really nice to have an instant filter of - this post is a waste of time - ah this post has an actual human's thoughts

I believe the author of this article is in fact most likely a large matrix multiplication and that it is possible that no human even initiated the computation of said multiplication directly. I assume it's not hard to set up some monitor for new CVEs to try and slop out an article as quickly as possible to get as revenue

I would argue for anything security - if there is a difference between how it works in theory vs in practice - then the theory is flawed. Physics gets to have theory/practice distinctions, but engineering doesn't because the bridge can't fall down.

This doesn't have the vibes of something that's designed perfectly even in theory. This more has the vibes of "this was the least worst option"

Based on how quickly the CTF was won - yeah that seems very reasonable.

It was exploited within 2 hours of the server being fixed to be vulnerable it proved the exact opposite of shat you're saying

It was true. The author had messed up the server and it was not exploitable. It was hacked within a couple hours of the author fixing it (even with the server being down) but the author had also messed up and not put the actual Bitcoin wallet in it so it took an additional 5 hours for them to fix that. It was a mess but the vulnerability was very real

I mentioned this a couple times there but the unintended consequences of that challenge are wild. 2 hours after it the server was fixed there was a successful exploit but because it was originally misconfigured a huge number of people walk away thinking the vulnerability was not serious. At the least we now know a good way to convince large swarths of technical folks to not take new vulns seriously! Which seems not good

There are auditors and the security, plus since IPOs involve raising money from institutional investors with very deep pockets those folks are a more credible legal threat than retail

honestly the surprising thing at this point would be if america did actually pass a policy of any sort, good or bad, vs just relying on the president to yolo some executive orders now and then that change every 2 years. Plus at least for the next couple years nvidia likes open source models and the president likes the ceo of nvidia. There could be a falling out but nvidia has deep pockets to ... discourage ... a falling out.

It's worth remembering that the tariff stuff is not any sort of durable policy. It's one guy sort of doing whatever until 9 other guys a year later go 'hey wait' and then the first guy does whatever again anyway. The whole thing is just a recipe for whiplash. maybe congress remembers that they're supposed to do stuff in a few months and steps in. maybe they don't and then every 4 years we have wild swings in enforced based on which half of a percent of the voters in georgia had rainy weather where they lived in early november. More of a simultaneous "All of the above and also none of the above" deal until the dynamics of american government fundamentally shift

Tokens per second? That only really matters for things like chat and sessions where you are monitoring a session as it runs which is going to be an increasingly small percentage of usage. That's bottlenecked by human attention. Agents in the background, long running tasks, unattended tasks, all that stuff is what is even capable of driving significant usage because you can just increase consumption massively by parallelizing without being the bottleneck. I wouldn't be shocked if already the vast majority of token usage was from unattended sessions. TPS is not that important there