Fairy Wrens are mentioned: https://fatbirder.com/ornithology/maluridae-australasian-wre... Pity they don't show them in their natural habitat: sitting on a car mirror, shitting on it.
2,805 karma · joined March 28, 2014
That equates to AUD$66/kWh, after shipping, installation and connection to the grid. It seems very low. Have you got citations for that number?
https://theconversation.com/big-us-style-trucks-are-killing-...
My understanding is the Wildcat lake 304 is that replacement, and it's been "released" for a while. It can be configured down to 10W vs 6W for the N100. Both draw about 7W from the wall when idle. The 304 is about 80% faster for the same power draw, has a better GPU in includes a 15 TOPS NPU.
Despite the 304 being released, it's not easily available yet.
The images out of Russia are a little different. Billions of dollars of plant and equipment blown up, hundreds of ships disabled, entire Wildberry warehouses covering acres going up in smoke. It doesn't seem to be in the same ballpark as a few days outage while you move stock and employees to a new location.
Maybe I'm missing something.
Because, to quote Jeff Bezos, your margin is my opportunity. And did he ever squeeze every drop from that opportunity. Just ask the brick and mortar stores in your street.
> I’m not convinced that basic economics works when output capacity isn’t fully scalable.
Economics works for land, which isn't scalable.
> Same reason no lawn care team tries to deeply undercut competitors
That works right up until Fred down the road loses his job, and then it dawns he could be making more money with his mower because of those sweet fat margins those other lawn care people thought they could keep all to themselves.
It is what I want.
If you own a mobile phone it's unavoidable. The physical SIM is a guarded area with secrets you can't know or touch - the secrets it holds prove you paid for access to their network.
If you want to carry a zillion others devices you can't access the innards of that prove something about you then good for you. But don't assume the rest of us think that's a good idea. We no more object to carving out a little bit of firewalled memory for the exclusive use of the bank than we object to the electricity meter in our houses. It's also a locked down piece of equipment we can't modify or touch that lives on our property. Most people are happy to grant that intrusion on their personal space in exchange for having the electrity connected.
It's no different on your phone. In return for your phone protecting its details from you, you no longer have to carry a credit card, or driver's licence, or prove you paid for ads to go away in some app, or access your works VPN. I honestly can't see much difference between carrying a credit card the hides some information from me, or putting the same info in the phone and it hiding the info. Except for having one less device to haul around, of course.
That one ruling took a huge toll on social discourse and civil society in Australia. It was a very sad day. Section 230 was a inspired piece of law making.
Norway is a smallish country (you can fit 24 Norway's in Australia - so less range anxiety), whose government pushed the transition to EV's hard. Australia has the worlds most competitive new car market and with one of the least restrictive emissions controls on ICE engines.
It's not that surprising that Norway's government engineered transition to EV's was successful. In Australia EV's became around the same price as ICE vehicles in the last 12 months, and it feels like we've hit a market driven tipping point.
If battery developments take their predicted path, with pricing dropping about 10% per years and range per unit weight doubling, it's difficult to see how it isn't all over bar the shouting - for USA car manufacturing.
Trump sealed the USA's fate, when his changes EV policies lead to $51B in direct write downs. I don't see how you can recover from that.
Formal proofs of code are almost beyond the capabilities of the best human programmers (3.7 lines per day!), but LLMs can bash out code at an amazing pace. It's often crap, sadly, but the proof they are bashing out is the hard bit. If possible at all, the task is EXPTIME. Verifying the proof is only P, so when it's wrong you tell the LLM to do it again. A stable agentic loop is what makes it possible. The results in the article I linked to speak for themselves.
Here I was thinking The Squid Game was a work of fiction.
If an article features a humanoid robot it's sure sign its a PR fluff piece. This one looks to be a recruitment ad. Tesla's Optimus is being used to pump some sort of investment scam. God knows China's humanoid marathon is about. Whatever it is, it isn't getting from A to B quickly and efficiently.
I'm fine with that. Going by the comments here, most people are fine with that. Given the choice between LLM-generated text or not seeing these sorts of novel ideas from different parts of the world on HN, they take the former.
I don't think the HN guideline "Don't post generated text or AI-edited text" is going to age well. My guess is it's already broken more than it's observed. The next bit: "HN is for conversation between humans" will be ageless. The mistake they make is "AI-edited text" is often net positive when humans converse, particularly if they come from very different backgrounds (language or culture).
This isn't a poetry forum. Bad spelling, bad grammar, inappropriate metaphors are all very human - but they get in the way when humans are just trying to communicate rather than create written art. The rule "Don't post generated text or AI-edited text" looks to fall into the category "there is always a well-known solution to every human problem — neat, plausible, and wrong".
This anti LLM crusade on HN is driving me nuts. It means I have to view with showdead on, because otherwise I miss clear, insightful and consequently interesting posts because someone to an dislike to am em dash. Dead posts are so faint I often have to copy and paste them into a comment box to make them readable.
Everyone hates LLM generated "ideas". But LLM phrasing of a humans original ideas is a different thing. Not ideal perhaps, if the alternative is not to hear the ideas and opinions of different cultures and countries, I'll take it every time. For fucks sake, learn to tell the difference between the two - don't just moronically down vote because of LLM tells.
If you use recursion, both the absolutely necessary state and the temporaries are pushed onto the stack (along with the stack frame the language runtime wants). If you use iteration, the programmer just pushes the necessary state onto the stack, and reuses the temporaries in place.
The rest of his claims follow from those facts. Space consumption is less because you are saving less. Cache locality is better both because the temporaries aren't scattered across the stack, and because you are reusing the same locations over and over again.
The downside of iterative solutions is stacks are more efficient memory allocators than heap algorithms - especially if you are forced to grow the array your pushing things onto many times. But if you know that in advance so you can allocate the full amount up front, then at the limit when N -> ∞ iteration will always win over recursion.
Maybe, but "maintainable" has a simple definition: minimising the effort to incrementally grow a software system as its size grows to infinity (while maintaining some defect ratio). Humans (called senior software engineers) figure this out over decades by working on a number of large software systems.
So far models haven't figured the same thing out. I can only guess why. All their learning comes from examining code on the internet. Somehow whatever the patterns are that make large software projects like the OSs maintainable by large groups of people working independently has escaped them. Maybe the bulk of code they look at is in the small so they miss it, maybe the patterns are just hard to discern in big systems.
My theory is there are anti-patterns which the larger projects somehow manage to keep to a minimum. It's hard to learn something that's not there. Instead, you learn these anti-patterns by doing them, and watching a system all fall apart over the course of years, and if you're good you manage to pin the blame on the right thing.
If you want to wrap it up neatly in a package, models have learnt how to program, but programming is not the same as design. Design requires very different skills to using a programming language. At a very high level, big systems are sets of interconnected modules. The things that matter are narrow APIs with minimal coupling, and where coupling is unavoidable making it explicit and easy to reason about. Concrete examples of the anti-patterns to be avoided are global variables, leaky abstractions and APIs that require complex sequences of interconnected calls.
Those things don't bite hard until you program in the large. The current crop of LLM's seem to be useless at all of them. If you've got a big context window and you are only writing 100s of kloc, a budget of kilowatts to understand the complexity, it doesn't matter. But humans don't have a budget like that, and so far everyone I've seen who reads large chunks of vibe coded software recoils in horror, gives up, and walks away.
Even with that budget, the models fail anyway once the size gets way beyond their context window - it's just that they fail much later than humans. Which I guess makes learning the lesson so much harder - perhaps near impossible as your "they need labeled examples" hints at. Oddly the solution would be to train with smaller context windows (a less powerful model in some ways), so the failures become apparent much earlier.
It looks like they have been going with your solution for now - giving engineers cheap tokens via flat-rate plans, and watching how they do things. I don't think that will work. Engineers who chew through the billions of tokens offered by these plans are vibe coding. The code they produce is so poor it can't cross the threshold from small to large. There is nothing to see there about programming in the large.
:( what a rant - it looks like an LLMs CoT as it thinks through things. Which is what I was doing, I guess.
Like the others here I know almost nothing about bio weapons, but I think perhaps the fact that smallpox's genome sequence has publicly available in scientific databases like GenBank for 30 years is relevant. That horse bolted a long time ago.
Time have changed. This should be:
Closed-source: You point an LLM at it, and get back source that's often easier to understand than the original.
Given the USA companies have been loudly claiming the Chinese models are distillations of their models, also claiming "no access to source materials" seems dubious. As it was dubious anyway with because the Chinese publish lots of papers on how their models are designed, I'm left feeling I'm looking at the south end of a north bound bull.
> The Lean library isn't just tested and validated, it's proved correct. This allows us to let AIs loose optimizing the code, requiring that they update the proof whenever the implementation materially changes.
To me it's a "that's obvious in hindsight, so why didn't I think of it?" thing.
If you can write a zlib compressor in it, you can write anything in it - so this is a technique that could be applied all problems amenable to formal proofs. Formal proofs are almost never worth the cost when they only prove the absence of bugs. Adding another payback, "you get speed as well", alters that equation.
Definitely merits more than 2 points after 20 hours. It feels like some readers can't look past an LLM being involved.
Turns out most authors and publishers suck at their respective jobs. Most books produced by authors are things nobody wants to read. If a publisher's job is defined to be finding works the public likes, they suck at it too. Instead they just publish lots of stuff, mostly at a loss. They make their money from the occasional hit. But only way they can make money from it is if they have a monopoly over publishing it for a while - which is exactly what copyright gives them. Looked at in another way, this "publish lots of stuff and see what sticks" is the way our society discovers what new works are popular. And copyright funds it.
If you take the view that copyright is paying for the discovery and publishing of new works, then consumers paying monopoly prices for 70 years or more is a bad idea. By far the majority of works are commercially dead 1 year after being published. The publishers tend to make their money from the remaining 1%. They might last five years. Very, very few last 20. I don't see how copyright lasting beyond 20 years can be justified with anything other than: "because of the good work he did 20 years ago, he deserves to be paid for sitting on his arse for the rest of his life". In reality, he didn't sit on his arse - he donated to a few politicians - but the outcome is almost the same.
They are both government enforced. The USA administration is using early access and export control restrictions to do their enforcing.
As for the effects: while I'm told the Chinese government is sensitive to some internal political topics, I've never seen it myself. I guess that's because I don't write code dealing on Tiananmen square or similar topics, and I don't know anyone who does. In contrast the restrictions on the USA models are a right proper pain in the arse. Hugging Face being forced to swap Chinese models to defend against the OpenAI GPT attack is a good an illustration as any.
That said, these USA restrictions are a new thing that seemed to start with Mythos - which means around 6 months ago. The Chinese models are (pull number out of the air) 6 months behind, so maybe in 2027 the Chinese models will start behaving like the current US SOTA ones.
Isn't this what everyone does in the same situation? "I need a screwdriver finer than any I have in my toolbox - so I'll sharpen a nail" is something every handyman has done. Given that "I need to build a vision pipeline I've seen many examples of in my training" isn't new or surprising.
In fact, all models have been doing similar things since I started using them - they regularly build Python tools to do odd jobs. Those tools are more impressive to me in some ways, because unlike a vision pipeline they are not just regurgitating something from memory.
The gob smacking amazing thing for me isn't the decision to build the tool. It's the fact that it remembers the exact shape of it. But I was gob smacked by that a "long" time ago, in far smaller models - like when it dawned on me 16GB Gemma 2 seemed to know most of everything on the internet, along with the ability to converse in numerous languages about it. I still struggle to comprehend how that is possible.
Now I think about it, Opus 5 fitting everything it's seen into what I guess is a couple of terabytes of parameters seems far less remarkable.
But it isn't always that simple. I have a work laptop. It has a MDM installed, so I can't trust it. I don't run my personal password manager on it, ever. But occasionally I go to a web site I don't care too much about, whose credentials are stored in my password manager. It's not an issue; I just type that password in. That doesn't work with passkeys.
Then there is backup. If I lost my password store I'd be toast. Which means if the company that manages my passwords took a dislike to me and banned my account, I'm in a world of pain. I deliberately choose a password manager that makes that unlikely, but not everyone knows to do that. Many people use Google, Apple or Microsoft as their passkey manager. These companies have seen fit to ban accounts without warning and no recourse.
My password manager lets me export all my passwords as plain text, so for my passwords this potential for lock-in is a non issue - I just export, encrypt, upload the result to a few places, I'm safe. I can always upload the data to a another password manager. As that doesn't work for passkeys, I don't use them.
Passkeys will become acceptable to me once multiple independent storage providers become available for passkeys, and they allow me to freely choose other certified others as a backup. Until that happens, they only solved half the problem. It looks to be the half that locks their customers into their platform.
PS: this doesn't require much. Just Google/Apple to implement CXS along with government providers, and we are there. But it won't happen any time soon.
The Chinese are open-sourcing these models - meaning they are literally giving them away. That's starkly different behaviour from that which drove patents and copyright.
There are all sorts of other differences too. If you develop a drug or publish a novel (which are respectively areas where patents and copyright have strong justification), you have to kiss a lot of toads before you get a prince. Once you have a potential prince drug, it takes years and billions to get it into the market. But right now, AI labs are seemingly churning out new prince models almost weekly, on hardware that will be obsoleted in a few years by hardware that makes finding princes faster and cheaper. In fact they rent the hardware, as Moonshot apparently did here.
When innovation is happening at that rate, patents and other IP restrictions just slow things down. If AI patents are aggressively granted and enforced in the USA, I suspect the outcome would be the same as batteries. China swept the market with LFP, and one reason was because while the USA developed them, there was no competition forcing the manufacturing price down because in the USA the patents weren't re-licensed cheaply. China had the foresight to secure a deal allowing them to develop and sell LFP domestically royalty-free. Natural competition within the domestic market took care of the rest. It looks like they are using a similar strategy for AI.
To me it looks like they have come up with a better formula for using capitalism to drive innovation than the one the USA is using.
I doubt it. Greek letters convey almost no information, whereas (one hopes) the function and variable names are chosen by a programmer to help the reader. The Greek letters used by mathematicians (and physicists) weren't used to convey information, they were used because typesetting, publishing and paper were expensive. They are optimised for brevity over readability.
It was a perfectly reasonable trade-off at the time, but times have changed.
As an aside, some programming languages (such as APL, and to a lesser extent Perl) did emulate the old Greek letter style. "Line noise" is a typical description of the result. No computer language aimed at software engineers and computer scientists does that now.
Errr, no.
You can transfer a password from one manager to another. Those very same password managers won't let you transfer a passkey they hold.
And if you know the password, you can use it anywhere by just typing it in - no complex technology or protocols involved. But using a passkey involves your secure computer talking to another computer, using a complex protocol that can't go via eyeballs and fingers. If you don't have a way to connect the device holding the passkey to the computer wanting your id - say your USB A Yubikey isn't recognised by your phone, then you are out of luck - you can't use that passkey, even though it's sitting in your hand.
And you can't work around that by copying the passkey to a device that can communicate with the service you're using, because you aren't allowed to copy.
It's an unworkable mess. The mess is not created by passkeys themselves, because, as others have said elsewhere the protocol is pure elegance. The mess is created by vendors choosing lock in over transportability. I'm hoping it's a passing phase.
This didn't set off your alarm bells? https://www.theblock.co/post/392765/ There have been a few of these now. Maybe it's my imagination, but they seem to be becoming more frequent.
So far, they all look to be accidents. But we can't be far from someone deciding its a good way to rob a bank, or disable a country.