necovek

This sounds like a great opportunity to use a crowd-funding site like gofundme to pay for a private boat or flight to take her home — either directly or through transit hubs she can legally enter.

I believe this is the usual tension that's present even in private companies: are professional managers better than field experts at managing work?

The pure ideal is to get a field expert who is good at management — but sometimes hard to attain!

The question then really becomes if — for a manager — a senior expert is better than an experienced manager who can detect exactly when to pull in the experts? A great manager would be great, but these are similarly rare (rarer than good experts in a field).

And this is probably always on a case-by-case basis: it completely depends on the circumstances, individual qualities, and supporting people around them to decide which is better for a given situation.

The same holds here: the best you can get is an expert with a wide grasp of the entire field they will be active in, supported by good, smart common-sense people to manage and guide their thinking and solutioning in the right way.

I believe this is also what colours our views of the general academic infighting — academics are rarely rotated out except in the lower ranks, so it's a different type of skillset of building long-term alliances that drives their progression through the academic field and available careers in a particular institution (not even talking about "academic points" through publishing in recognized journals, which is a different discussion altogether — even with that criteria satisfied, to move to the next rank of professorship, you need to be elected by your colleagues).

Basically, academic tenure is opposite from democracy.

I laughed out loud at this — my dad is a retired Uni professor, so I know exactly what you are talking about — but I'd point out that the "student list" has around 140 seats in the parliament, so 80 academics hopefully still has another 60 common sense people who are not all about being right all the time, and who bring other perspectives too.

That's if it was stolen from you directly.

If it's stolen from a bank, it's their obligation to recuperate you.

FWIW, most countries have a type of insurance if a legally operating bank goes under, at least some of your savings are protected (eg. in Serbia that's up to 50kEUR).

If it was filed as a security issue, most well-set-up projects with public issue trackers would keep it closed off only to a reporter and internal security audit team.

Perhaps it was never really declassified in the tracker.

Indeed, mixing all the language features and anti-features with non-native Python libraries is a big reason too — both because it mitigates many of the performance issues a JIT would solve, but mostly because it complicates or makes the implementation unfeasible altogether.

Perhaps it's worse that some even succeed in building very complex systems that can handle a lot of load too (see eg. Instagram)? ;-)

Python has a known set of trade-offs, mostly related to loop performance. But if you understand the trade-offs and available mitigations, it should not stop you from building good software. You know, just like any other ecosystem.

Obviously, I am not saying making a JIT for Python is impossible: both PyPy and GraalPy prove otherwise. We are talking about full ecosystem support, not just the base language and stdlib.

Can you just replace CPython with PyPy or GraalPy in every project? And why not? :)

The type of dynamic language gymnastics done with Python is huge: any sufficiently well known library basically employs some sort of meta-programming of the language:

  * Typing is a non-obligatory add-on to the syntax
  * SQLAlchemy and other ORMs override basic operators like "=" and employ metaclass programming heavily to create Python-like SQL query builders
  * Pytest rewrites all the assertions as it side-steps bytecode generation (so your .pyc files are different than what they would be without pytest)
  * Many libraries depend on monkey-patching live library calls, including ones to external dependencies
  * The way async was added in is another bolt-on where the same code behaves differently in different contexts
  * Decorators can introduce any side-effect you imagine, and nobody (including core libraries) follow the golden rule of "don't do, only decorate"
  * Many debugging and profiling mechanisms (including REPL) depend on these properties to function — including observability tooling like Sentry, Datadog etc.
  ...

JavaScript never had that level of flexibility (for better and for worse), and by extension, it's easier to build an alternative implementation and keep it compatible with the rest of the world that claims to be JavaScript.

Production of surplus value is what generally qualifies as a "job" — I certainly agree there is potential for tools to replace/augment any job we think of, but we'll simultaneously continue inventing new jobs.

Just like economies are mostly a service-industry today, a concept that barely made any sense 100 years ago.

Still, buying tooling companies' shares makes sense when that company has something which is hard for anyone else to replicate: but we are seeing that it really is not with a number of proprietary and open weights competitors who generally go head-to-head with minor differences in capability.

This only to say that believing valuations are unreasonable does not mean you can't even be an "AI maximallist" — but markets do not work in a simple cost/value-provided equation for a long time now.

A general statement I made is mostly to refute that people invest exclusively when the data is clearly supporting that investment with guaranteed returns: basically, the fact that people will buy does not mean that they have guaranteed returns.

Some might be looking to capitalize early and exit quickly; some are creating demand because they have other drivers in their portfolio (eg. Nvidia or Micron); some might really believe in the company; and some might be gambling with their disposable investment money for their high-risk/high-gain part of portfolio.

I find that HP/Palm Pre with WebOS was best even if we ignore the physical keyboard (sliding left/right on the touch area below the screen or on the screen with a button pressed really made it easy to select text easily and precisely). Nokia N9 with Maemo/Meego was second best but it excelled in the cards interface for multi-tasking.

Some of those were taken into other OSes but nowhere were they implemented so smoothly.

You might be surprised to learn that yes, regularly pointing a tool at the codebase and seeing it found no issues is indeed enough to claim compliance with cybersecurity regulations.

While we may use deterministic tools like static code analysis, dependency scanners and similar today, people are already replacing/augmenting them with LLMs.

While every breach will trigger a root cause analysis process in a compliant environment, the solution is never going to be "all code in a deployment was manually reviewed by someone at the company" because this would extend to tooling (like compilers, scanners but also packaging and deployment tools) and all dependencies.

So I am pretty sure your example is already used in a number of places especially with "LLMs are better at security than humans" marketing being pushed around — this really makes it easy to sell that excuse to the gullible management who wants to believe this.

People participate in betting and chance games even if the odds are against them.

Sometimes, there is no logic behind what people do, ultimately hoping to strike gold once while wasting money otherwise.

Or nothing since there is no market or spending with no jobs for people?

  @model(Example.HTTP.Request)
  def request(url):
      (res, status_code) = magic()
  ...

Ouch — I understand this is magic by design, but this is exactly the type of non-explicit code that quickly devolves into unmaintainable mess.

A reader who might have 2 decades of Python experience will not be able to follow the logic, and would need to pause and read up to be able to debug and test this.

Where does the magic start and where does it end? What's up with that "url" parameter, how does it relate to the declared model and how is it passed into it?

At the very least, I'd consider passing the "model" argument from the decorator into the decorated function to make it explicit at very low increase in keyword count (token count?).

It is not really a party — it's a nomination list by the protest-organising students — and the people really voted against the ruling party.

The idea is for this to enable true democracy to re-appear, and then actual parties would battle it out in the next elections.

I'd say the risk to political stability in Serbia remains, but just like in any functioning democracy, what matters is that there is regular change and politicians understand that they are soon to be replaced (this avoids the levels of corruption that is multiples of base government project costs and actually cost lives).

There are certainly different levels of oppression and autocracy.

Here it was designed and made to look like a democracy, but it really required a 70% turnout and 50%+ of people voting against the ruling party for them to accept defeat, especially as there are still large vote thefts going on (to the order of 5-10% of the entire voting population). Basically, anything less than 50% would have put the country in turmoil and violence — again.

As a tidbit, we've got 6.4M registered voters (18+) in a country of 6.5M people. There are a few explanations about how that works, but I'll let you draw your own conclusions.

You are missing the point: GenAI is here to stay. When and if it will bring a positive RoI for anyone other than those in related businesses, remains to be seen.

Internet has allowed a new type of businesses to appear and prosper. Some old-style businesses got the hang of it, some did not (look at all the newspaper businesses trying to figure out how to stay funded without falling under oligarch's rule).

It was a gold rush because gold was already "adopted" in the world for a mere couple millenia.

Generally, banks try to get as much of the interest early on, and move the base to later. This is why it usually makes no sense to pay off a debt after 5 or 10 years when you paid 80% of the interest already (but also why refinancing works for banks: more upfront interest which they put into books as profit right away).

On some things, governments put the cap on how much can early payments be loaded with interest and how much at least should be paying off the base debt — otherwise, you'd be paying only the interest for the first 15 years of a mortgage.

Though, these things work slightly differently in different countries.

See legal treatment for murder vs attempted murder, burglary vs attempted burglary...

Penalty is based on the impact, and while even attempts can have significant impact, software systems are non-feeling entities that endure attempted exploitation all the time. Just check your logs if you run any public service.

I had the same question and read through it to get an answer but it is indeed not there :)

My guess is that they brought Germany example of doing GeoIP as the model they'll use but mostly noted as a fun quirk that even that solution received a weird challenge which they managed to fight off (at cost, though).

Obviously, it'd be nice to get a direct response from them as it is unclear.

It's called copyright as things change when works are easy and cheap to copy.

Replicating work of an electrician or builder is very similar effort to their original work.

Making a copy of a novel or software program or art today is practically free.

In case of work for hire, things pretty much work the same way already — company owns the copyright, except in some jurisdictions where actual humans keep "moral rights" and reserve the right to renegotiate the fee if the work produces disproportionate earnings (one cannot even transfer these rights away).

But if you did the work out of pocket, how should it work? Any recipient could trivially and cheaply produce a copy and distribute it. If you do not get any exclusivity at all, others would profit a lot more and you'd get nothing at all.

So in general, there are multiple things:

* exclusivity lasts too long (I understand some motivation like supporting your children off it, especially if work only became profitable late in your life or in death, but you could have different mechanisms too — akin to moral rights, exclusivity could run from the moment it turns a significant profit like an average annual salary, and for a fixed, much shorter period after)

* types of works which are utilitarian (like software tools) should have entirely different treatment

* it should ensure both transferability and perpetuity of use (no licensing bullshit and your games/music are gone because our service does not offer them anymore)

...

How would you imagine this could work?

A recursive DNS resolver is identified just by an IP address for your system level DNS resolver to use (eg. in /etc/resolv.conf). Even if you assigned a random, secret IPv6 address for every individual user, they could simply share that with anyone else too. In IPv4, pretty much impossible.

Can you explain how you got from "attempts to exploit it" to "exploited in the wild"?

As pointed out, the fact that it is so does not mean we should not put the foundations in.

The school system needs to provide not just the essentials — though most of that comes from the family and environment — but a window into opportunities.

By however much we invested into mathematics, it put a number of people on this AI track, and through their contributions, here we are — for better or for worse.

Maths, while it is only to be practised by few, has such broad applicability to our entire world — I honestly believe we step straight into Idiocracy in a couple generations if we stop teaching fundamental sciences, among which mathematics is the first of.

Why does that formula work? ;)

I did not say "derivation of the formula" by accident: this is about why would this produce something that makes sense as "interest-as-percentage"?

> Whether the infinite-series summation limits are worth knowing is questionable, though. That's more of historical interest.

A very common example is compound, continual interest accumulation. As a mathematician, I had trouble understanding how banks calculate it (as they would obviously not point me at the derivation of the formula), but it's actually a limit sum over infinitely small interest terms.

Similarly, these techniques work to explain and derive numerical methods for calculating many natural constants like e, pi etc.