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Wired linked to this tweet as their source: https://x.com/binance/status/2116089661408108712

> Our initial investigation suggested that the security incident may have involved a compromised laptop, however our subsequent investigation has uncovered additional points of breach.

That seems to be their most recent update on the matter afaik (30 Oct, 8:47am UTC)

Binance explicitly said it wasn't just the compromised laptop.

I'd be surprised if it were. Crypto exchanges have been targeted by hackers since forever, and Binance is one of the top. If it was so easy to exfiltrate crypto from them, I'd have expected a heist before now. (Unless controls have just gotten worse recently.)

When we see a breach of AWS or GCP or leading banks, basically any org that has good security, I'll believe technical security is impossible.

Otherwise, I think this is a issue of vendors, even if potentially most vendors fit into the basket of having insufficiently good cyber posture in AI-era.

Yeah... Given that everyone else seems to make models available either immediately or within days of announcement, idk why Google feels it's competitive or acceptable to do these 'available at some point' releases.

Capabilities are also improving so fast that this fomo doesn't really keep people excited. If I can't run it, I'll sorta just click off. And given how they handled the Argon release, I've not even bothered look at this Carbon one. Fully expected it to not be usable yet.

I too could not figure it out. Also a shame the Vertex API format is sorta different to OpenAI's, which everyone but Anthropic uses. The sanest way to use Google AI models is via OpenRouter tbh.

Small business self-employment doesn’t care that much about saturation, I think, only the supply-demand relationship. See everything from Fiverr to coffee shops.

But yes, self-employment often is a lot of work.

The HuggingFace hack isn't OpenAI's responsibility because they hosted it. It's their responsibility because they directed it; it was part of their own internal benchmark run that they fully controlled.

If a third party uses a model created and hosted by OpenAI, I don't think OpenAI should be liable so long as they implement acceptable security controls. Same as if a site hosted on Cloudflare or GCP is doing something dodgy, Cloudflare/GCP aren't held liable so long as they respond to abuse reports.

Yeah, so long as China exists and wants to keep releasing open models, it's not feasible for Western labs to stop releasing frontier models to the people.

I don't believe this is true with current frontier coding agents. Or at least, it's becoming increasingly less true, such that I think it will effectively be nullified in ~6 months.

> replies to comment about training to use word processing software, and compares it to three life-critical highly complex fields

Entrepreneurship 101 imo is that great companies only come from people who sufficiently care to see something through.

Unlikely the people that start these 100 companies, across totally disparate fields, and care enough to take them to market are staff members at OpenAI.

And it's already obvious a single company can't split its attention enough to do tons of disparate things well (see OpenAI's previous attempts at Atlas, the social network, Dots, etc)

Starling also has a disaster recovery system across cloud providers, although it is implemented differently to Monzo's (I used to work there on multi-cloud).

Multi-cloud is really tough, tbh. It's easier said than done, especially if you care about data consistency at all.

It's a pretty good source ime (at least, massive spikes tend to correlate well with issues). Traditional organisations aren't as transparent as SF tech companies about service downtime. Plus, if the service isn't working for its users, I wouldn't say it's actually up.

Don’t think Russia is likely to bomb Germany, or any of Western Europe. Ireland, UK, France, Netherlands also seem like safe places to house datacentres.

It sounds like Jev is not a generative model. If true, I don’t understand these clones which fine-tune a generative model, which appears to not be what Jev is doing.

This news is about the UK. Across the channel, the EU has effectively outlawed anonymous currency. I believe the UK FCA also has such rules in force. So your post is rather moot.

Yes it's definitely not SOTA, and is worse than all the chatbots I use. But it's correct frequently enough that the convenience + speed does it for me.

Although there are companies trying to work around that too, from PhysicsX to some of the world model co’s.

tbh I also use google AI tools frequently. It’s convenient (search bar is top of my window), and extremely fast at generation. For quick Qs, opening a chat bot and changing the default reasoning from my coding settings, switching from Work to Chat, etc etc, is too much of a faff.

Many VCs also dislike these examples, I believe. I'm doubtful this is what they're being pitched.

As for public releases: I wonder if it's because these examples are easy to relate to. Many websites are just a long tail of industry or use-case specific stuff. What's valuable to me probably means nothing to you. This is unlikely to resonate with people-wit-large (and LLMs are marketed broadly) or requires the reader to think (and marketing that requires thinking is bad these days).

Second, it's arguably a good litmus test. If it still can't do the worn out examples of plane tickets and shopping, which would be a good assumption since we've been demo'd these use-cases for 2 years at this point, then ...

I recall them saying they use models to write CUDA kernels and whatnot. Makes sense, and unsurprising that models are good at writing code.

But I think calling this “automating AI research” is misleading. I’m not sure there’s evidence yet that they do creative research work. Even in mathematics, but they are finding counter-examples by intelligent brute-forcing. Not to downplay the results, as they are incredible, but this is one very specific kind of proof and not the most creative type, which arguably requires generalisation.

I did, at least until Fable 5.1. Grok’s models are excellent, amazing price-performance and speed too.

In essence. But if you have a chain PR1 > PR2 > PR3, and PR1 gets merged, all the others (ime) seem to not cleanly rebase on main. They end up with conflicts that require manual fixing. I've not really figured out why, tbh. It'd also be nice to see a coherent link in the UI between PR1, PR2, PR3.

GitHub's PR workflow doesn't nicely support being able to review individual commits, realise which comments are associated with which commits, etc. Or shipping individual commits to main, while working on some others (unless you allow cherry-picking and direct push to main). Or amending a certain commit with respect to feedback and seeing a diff from the previous patch of that commit to the next.

If GitHub's unit of change were a diff, and not a branch, then that would work pretty well.

I think it's telling how long it took GitHub to release a v1 of this feature. Folks have wanted this for a long time. Graphite came along and did it years ago (and I'm sure they pondered whether GitHub would do this).

And the v1 is also a bit... basic, and buggy. And I'm surprised there's not clear documentation for agents (given using GitHub stacked PRs CLI won't be in models' training data yet).

It does feel like GitHub hasn't been great at shipping new features for a few years now. Nonetheless, I'm glad to see this rolling out. Once polished, it's going to be exciting to use.

I presume such US legislation isn't going to try claim worldwide jurisdiction to block all persons worldwide from using Chinese models. In which case, the French guy wouldn't be violating American law.

As for the American company, it's pretty difficult to check the provedance of open weights. It's even difficult to check the provedance of open source code, because chains of attribution aren't always clear. I posted elsewhere that Anthropic's MCP Python SDK is a fork of an open source project with the attribution removed. We saw the same with Cursor's Composer model, which didn't attribute its Chinese base. It's very hard to claim an American company should be liable for using a purportedly European model with attribution removed.

Because it's not losing money on each token? Aside from most global people using American inference providers to run the models, I suspect the cloud inference products of the Chinese labs are profitable, at least on the inference costs (ie: not including model training, salaries, etc).

Probably just the US. But the US could do what EU has done with e.g. GDPR, Digital Services Act, USB-C regs, where they force any company trading in their region to follow those regulations for domestic customers.

And basically any AI company has to sell to US companies or consumers. That'd probs be sufficient to force them to use US models.

Step 1: Chinese company publishes open weights on HF

Step 2: European company distills or just adjusts the model slightly, and publishes its model on HF

Step 3: American company uses model from step 2. Has to testify under oath where they got it from. "We got it from these French guys"

How long did it take from the first DBMS to get to Postgres? The first OS to get to Linux? The first compiler to get to LLVM? For Postgres and Linux and LLVM to become mature enough to hold the revered reputation they have now?

The jury's still out on AI, but coding agents have only really worked for about 6 months now. It's not exactly a fair statement to make. Obviously good things take time and thought. And understanding the full implications of technological advancement also takes time and thought.