An author of a scraper would need to trade off how much arbitrary compute they'll run against how much risk they take that someone will use them for free compute (inverting their role from exploiter to victim). They can work around that somewhat by analysing common enough code (to justify the LLM or human expense) and deciding to run it.

PoW challenges work when they have low enough adoption that it isn't worth scrapers' while to have a custom countermeasure for. To scale them once adoption is big enough, it probably takes some bespoke engineering per group of sites (coupled perhaps with some scraper traps that take advantage of scraper CPU for something useful, and aren't easily distinguished from the normal challenge).

I don't think that's true.

There are two possibilities: If you're proposing that dummy messages are in addition to normal messages, then dummy messages add noise to the signal, but over a long enough time, for known noise distribution, it is possible for the signal to be statistically significant. That depends on there being enough signal, but then things depend on signal traffic patterns, there are no guarantees.

The second possible design is that the node-to-node communication volumes for any pair of nodes is truly independent of the signal - i.e. the statistical model decides how much traffic flows from a node to another node, and that fixed amount of flow is either used for signal or for noise, and if there is more signal, it's dropped or waits. Encryption makes it impossible to distinguish signal from noise without the key known between the pair of nodes. That is secure against a passive adversary who doesn't participate in the network. However, if network users are anonymous and mutually untrusting, then the adversary can use active methods without much risk (i.e. lots of users and nodes can actually be the adversary). Every packet/message delayed or dropped also allows inference about network traffic by other users.

These methods can harden a network and make analysis harder, but they don't guarantee it is not possible.

In case anyone else faces the same: it worked when I resized the browser window and reloaded.

If the owner of the system has a 'no ads' policy and a security mechanism to prevent ad servers from accessing their display without their authorisation, it is one thing if a company accidentally circumvents that by changing their page in a way that breaks detection (and unless there are records it was deliberate) they probably get the benefit of doubt from authorities.

But if they are blatantly going to quite great effort to circumvent the adblock security system to exceed their unauthorised access without the consent of and against the wishes of the owner of the client system, surely that's a clear-cut criminal case?

Of course, prosecutions of these types of things in many countries unfortunately tend to go after individuals who target big companies, but almost never the other way around.

But in practice, we've produced a lot more compute. The memory / CPU ratio has increased, but most growth has been from more CPUs (and generally not shared-memory ones, but ones with their own completely separate memory space).

IPv6 is 128 bit, so we do have 128 bit ways of addressing computers, but I'd say we're still a long way from a CPU needing to address that much memory as a common case. The speed of light limits how far away memory can be from the CPU for good performance, so short of some drastically new memory technology, it seems unlikely we'll need it soon for any ordinary type of computing device.

That's got to be hyperbole, which blows out their credibility. They chose to say 'AI' rather than, for example, LLM, or Transformer model, or Diffusion model. This means they are including a huge swathe of things dating back to Expert Systems in their claim.

And who hasn't seen productivity gains from more established AI technology - at least things like semantic search? Who hasn't seen diffusion models generating content in roles that might have done the work by hand before? Who hasn't seen some kind of regression algorithm (even using linear regression in a supervised context counts as AI - so you can absolutely do AI even in tools like Excel) improve operation productivity?

Even if they narrowed it to the Transformer model LLMs which re-ignited recent public interest in AI, less ambitious projects to give them to engineering staff to automate easy but boring tasks in the background generally have been a success. More ambitious ones that are beyond what you'd reasonably expect the models to be able to do - for sure, those tend to fail. For most of these, the failure is predictable in advance, while some are at the boundary of what's possible, and so it is harder to predict (these are rationally genuine R&D projects).

They do factor in shift work as a categorical variable, and employment status as a categorical variable not taking into account occupation. But probably occupation (not a variable here) interacts with sleep status. Any job that involves a lot of flying (pilot, crew, people travelling for business) get more cosmic radiation exposure, for example, and potentially more sleep disruption. Certain operations and manufacturing jobs correlated with exposure to carcinogens also likely correlate with less regular sleep, possibly in a way that isn't corrected for by the limited shift work categories.

The Council decided Chat Control was on the agenda, the Commission wrote the law, and the MEPs voted to reject said law in March. Then the president of the parliament (not the MEPs at large) asked the Council to ignore the March vote and proceed with the agenda under urgency as if it had passed.

Now a minority of the MEPs (331 out of 720) - but a majority of who were present at the time and chose not to abstain - have voted to deal with the matter under urgency, but haven't voted on the substance of it. This makes the actual vote happen on the last sitting day, when apparently they are hoping a lot of MEPs will be away.

Consider Cisco. On the 31st of March, 2000, it was valued at US$77.31 / share, which in inflation adjusted terms is $150.46 (above the current price over 26 years later). This valuation was on the basis of speculation that the price would continue to go up and Cisco would get a large cut of the industry profits. Cisco's business is still valuable, it was just treated as overvalued by the market.

Similarly, if we go back to one of the classic examples of a bubble - consider Dutch tulip prices in 1636; speculation drove future contracts high. But tulips still have value to people today, it's just the price was higher than was sustainable.

Axis 1 - civil & political rights: In favour of broad social & political rights (down) -> In favour of few social and political rights a.k.a. authoritarianism (up) Axis 2 - economy: In favour of social responsibility / society ensuring people's needs are met (in the sense of 'from each according to ability, and to each according to need') (left) -> In favour of individual responsibility and a laissez faire economic freedoms (right).

On this 2d view, Social Democrats are nominally lower left, while Chat Control is an authoritarian policy (i.e. appealing to anyone on the top half of the coordinate system), so it would run counter to their nominal values.

Note that there is a significant number of the economic left who are nominally authoritarian (see for example Stalinist / Maoists), and likewise for the right so it doesn't make sense to project that as a left/right thing.

Now there is no absolute guarantee that, if someone has the information, and they are legally required to delete it or not use it, that they don't break the law. But it works in the case of balancing the need to avoid people being disappeared against preventing dragnet misuse of arrest data by employers and landlords. Maybe organised crime employers would systematically break the law if maintaining a database illegal, but they also probably don't mind people with arrest records.

So companies A & B (A=TSMC, B=Tokyo Electron) are in a customer-supplier relationship. Employee B1 of B asks Employees A1 & A2 of A ask for information about how B's technology is working in practice at A, which involves revealing information about A's processes. A1 & A2 supply the information, and B2 at B uses it to improve how B does things, so they can help A more and increase their business with A. There is no allegation that the information supplied to B by A employees left B, or was used for anything except to help with the collaboration between B & A. And as far as the article mentions, no evidence A1 or A2 received a bribe or anything like that.

And yet manager A3 at A finds out about this supply and freaks out because they didn't want A1 & A2 sharing that much information with the supplier. So they make a complaint - and A1, A2, B1, B2 and B as a company all face significant penalties.

This seems unjust given A1, A2, B1 & B2 were all just trying to collaborate in the best interests of their companies, and B employees only used things freely and non-corruptly given to them by A employees; no information was leaked outside of the collaborating companies. A1 & A2 might have broken their company policies, but this probably should have ended at them being educated on the company policies and being asked not to do it again when managing future supplier relationships.

The are motives for lying on this - for a start, if a president knows definitively they're going to say it, it's a free 81% return. Secondly, it's a pretty big dead cat to throw on the table to distract from any scandal and/or to keep themselves in the news cycle on a different topic.

I personally think it is the copyright that is the most uncertain. Firstly, there are probably quite a few venues around the world where Atari might be able to take this up, and quite a diversity of precedent between them. Historically Atari litigated in the US - in 1981 they lost https://en.wikipedia.org/wiki/Atari_v._Amusement_World on a case someone infringed by copying their look and feel without copying any assets. Other precedents in that jurisdiction have found it's not infringing if similarities are inherent to the subject matter of the game: https://en.wikipedia.org/wiki/Data_East_USA,_Inc._v._Epyx,_I.... but similarity of art style is copyrightable: https://en.wikipedia.org/wiki/Tetris_Holding,_LLC_v._Xio_Int....

For example, let's try a simple experiment. I'll generate a random UUID:

> uuidgen 44cac250-2a76-41d2-bbed-f0513f2cbece

Now it is extremely unlikely that such a UUID is in the training set.

Now I'll use OpenCode with "Qwen3 Coder 480B A35B Instruct" with this prompt: "Generate a single Python file that prints out the following UUID: "44cac250-2a76-41d2-bbed-f0513f2cbece". Just generate one file."

It generates a Python file containing 'print("44cac250-2a76-41d2-bbed-f0513f2cbece")'. Now this is a very simple task (with a 480B model), but it solves a problem that is not in the training data, because it is a generalisation over similar but different problems in the training data.

Almost every programming task is, at some level of abstraction, and with different levels of complexity, an instance of solving a more general type of problem, where there will be multiple examples of different solutions to that same general type of problem in the training set. So you can get a very long way with Transformer model generalisations.

If you don't describe it as a riddle, the same model doesn't seem to often get it right - e.g. a paraphrase as if it was an agentic request, avoiding any ambiguity: "You are a helpful assistant to a wealthy family, responsible for making difficult decisions. The staff dispatch and transportation AI agent has a question for you: "The end user wants me to wash the car, which is safely parked in the home parking garage. The car wash is 50 metres away from the home. Should I have a staff member walk there, or drive the car?". Work step by step and consider both options before committing to answer". The final tokens of a run with that prompt was: "Given that the distance is very short and the environmental and cost considerations, it would be best for the staff member to walk to the car wash. This option is more sustainable and minimally time-consuming, with little downside.

If there were a need for the car to be moved for another reason (e.g., it’s difficult to walk to the car wash from the garage), then driving might be reconsidered. Otherwise, walking seems like the most sensible approach".

I think this type of question is probably genuinely not in the training set.

The best public policy outcome in such an approach would be for losses to be only slightly negative. Positive or zero expected losses mean no drug development, and highly negative expected losses mean the drug is more expensive than necessary and reduces the accessibility of the drug.

However, current patent law allows companies to minimise their expected loss, with no controls to prevent highly negative expected losses.

There are alternative models - such as state funding of drug development. This model has benefit that it is possible to optimise more directly for measures like QALY Saved (Quality Adjusted Life Years Saved) - which drug sale revenue is an imperfect proxy for due to some diseases being more prevalent amongst affluent people, and because one-time cures can be high QALY Saved but lower revenue.

The complexity of state funding is it still has the free-rider problem at a international level (some states invest less per capita in funding). This is a problem which can be solved to an extent with treaties, and which doesn't need to be solved perfectly to do a lot of good.