The front camera is the best thing I added to my 2004 Prius. The hood on that car is very good for visibility, but with the birds eye cameras I can roll it up within centimeters of things in front of me (there's a slight risk that you can absolutely poke the nose under stuff but at that point it's quite obvious out the windshield too).
Maybe so but what here really would've prevented this? The information involved is necessarily public: bank details and credit card numbers need to be shared otherwise why have them?
Writing a rule that says the government can't do this is just the government writing a rule it can simply remove it ignore when inconvenient.
The banking information belongs to the account holder and the bank. Google knows it by coincidence but should not share it because it isn’t theirs. If the government wants to know my banking details they can ask my bank. If they can’t figure out who my bank is they should get better at investigating. This approach is just exploiting Google’s wide reach.
The most interesting thing about everyone trying to position themselves as AI experts is the futility of it: the technology explicitly promises tomorrows models will be better then todays, which means the skill investment is deflationary: the best time to learn anything is tomorrow when a better model will be better at doing the same work - because you don't need to be (conversely if you're not good at debugging and reverse engineering now...)
the best time to learn anything is tomorrow when a better model will be better at doing the same work
doesn’t that presume no value is being delivered by current models?
I can understand applying this logic to building a startup that solves today’s ai shortcomings… but value delivered today is still valuable even if it becomes more effective tomorrow.
I think it also presumes that the skills of today won't be helpful in making you better, faster, stronger at knowing what to learn tomorrow. Skateboarding ain't snowboarding but I guarantee the experience helps.
I'm pretty much just rawdogging Claude Code and opencode and I haven't bothered setting up skills or MCPs except for one that talks to Jira and Confluence. I just don't see the point when I'm perfectly capable of writing a detailed prompt with all my expectations.
The problem is that so many of these things are AI instructing AI and my trust rating for vibe coded tools is zero. It's become a point of pride for the human to be taken out of the loop, and the one thing that isn't recorded is the transcript that produced the slop.
I mean, you have the creator of openclaw saying he doesn't read code at all, he just generates it. That is not software engineering or development, it's brogrammer trash.
I think the rationale is that with the right tools you can move much faster, and not burn everything to the ground, than just rawdogging Claude. If you haven't bothered setting up extra tools you may still be faster / better than old you, but not better than the you that could be. I'm not preaching, that's just the idea.
> That is not software engineering or development, it's brogrammer trash.
Yes, but it's working. I'm still reading the code and calling out specific issues to Claude, but it's less and less.
You're reading it though, and I imagine you are applying comprehension to it based on your experience. It's not vibe-coding any more at that point, I'd call it rapid application development. That's what Rails did in, what, 2010? Maybe earlier? Except it was generated scaffolding code created through reflection and not machine learning.
It's when you take yourself out of the loop and trust the process that it goes in the wrong direction.
That’s true for “tips and tricks” knowledge like “which model is best today” or “tell the model you’ll get fired if the answer is wrong to increase accuracy” that pops up on Twitter/X. It’s fleeting, makes people feel like “experts”, and doesn’t age well.
On the other hand, deeply understanding how models work and where they fall short, how to set up, organize, and maintain context, and which tools and workflows support that tends to last much longer. When something like the “Ralph loop” blows up on social media (and dies just as fast), the interesting question is: what problem was it trying to solve, and how did it do it differently from alternatives? Thinking through those problems is like training a muscle, and that muscle stays useful even as the underlying technology evolves.
It does seem like things are moving very quickly even deeper than what you are saying. Less than a year ago langchain, model fine tuning and RAG were the cutting edge and the “thing to do”.
Now because of models improving, context sizes getting bigger, and commercial offerings improving I hardly hear about them.
> what problem was it trying to solve, and how did it do it differently from alternatives?
Sounds to me like accidental complexity. The essential problem is to write good code for the computer to do it's task?
There's an issue if you're (general you) more focused on fixing the tool than on the primary problem, especially when you don't know if the tool is even suitable,
You nailed it. Thats exactly how I feel. Wake me up when the dust settles, and i'll deep dive and learn all the ins and outs. The churn is just too exhausting.
I don't get the pressure. I don't know about you, but my job for a long time has been continually learning new systems. I don't get how so many of my peers fall into this head trip where they think they are gonna get left behind by what amounts to anticipated new features from some SaaS one day.
How do you both hold that the technology is so revolutionary because of its productive gains, but at the same time so esoteric that you better be ontop of everything all the time?
This stuff is all like a weird toy compared to other things I have taken the time to learn in my career, the sense of expertise people claim at all comes off to me like a guy who knows the Taco Bell secret menu, or the best set of coupons to use at Target. Its the opposite of intimidating!
I may just be a "doomer", but my current take is we have maybe 3-5 years of decent compensation left to "extract" from our profession. Being an AI "expert" will likely extend that range slightly, but at the cost of being one of the "traitors" that helps build your own replacement (but it will happen with or without you).
> the technology explicitly promises tomorrows models will be better then todays, which means the skill investment is deflationary
This is just wrong. A) It doesn’t promise improvement B) Even if it does improve, that doesn’t say anything about skill investment. Maybe its improvements amplify human skill just as they have so far.
I have a reading list of a bunch of papers i didn't get through over the past 2 years. it is crazy how many papers on this list are completely not talked about anymore.
I kinda regret going through the SeLU paper lol back in the late 2010s.
We really need a rule in politics which bans you (if you're an elected representative) from stating anything about the beliefs of the electorate without reference to a poll of the population of adequate size and quality.
Yes we'd have a lot of lawsuits about it, but it would hardly be a bad use of time to litigate whether a politicians statements about the electorate's beliefs are accurate.
The thing is... on both the cited occasions (Nixon in 1968, Morrison in 2019), the politicians claiming the average voter agreed with them actually won that election
So, obviously their claims were at least partially true – because if they'd completely misjudged the average voter, they wouldn't have won
When there are only two choices, and infinite issues, voters only have two choices: Vote for someone you don't agree with less, or vote for someone you quite hilariously imagine agrees with you.
EDIT: Not being cynical about voters. But about the centralization of parties, in number and operationally, as a steep barrier for voter choice.
Two options, not two choices. (Unless you have a proportional representation voting system like ireland, in which case you can vote for as many candidates as you like in descending order of preference)
Anyway, there’s a third option: spoil your vote. In the recent Irish presidential election, 13% of those polled afterwards said they spoiled their votes, due to a poor selection of candidates from which to choose.
That’s much more true for Nixon in 1968 than Morrison in 2019
Because the US has a “hard” two party system - third party candidates have very little hope, especially at the national level; voting for a third party is indistinguishable from staying home, as far as the outcome goes, with some rather occasional exceptions
But Australia is different - Australia has a “soft” two party system - two-and-a-half major parties (I say “and-a-half” because our centre-right is a semipermanent coalition of two parties, one representing rural/regional conservatives, the other more urban in its support base). But third parties and independents are a real political force in our parliament, and sometimes even determine the outcome of national elections
This is largely due to (1) we use what Americans call instant-runoff in our federal House of Representatives, and a variation on single-transferable vote in our federal Senate; (2) the parliamentary system-in which the executive is indirectly elected by the legislature-means the choice of executive is less of a simplistic binary, and coalition negotiations involving third party/independent legislators in the lower house can be decisive in determining that outcome in close elections; (3) twelve senators per a state, six elected at a time in an ordinary election, gives more opportunities for minor parties to get into our Senate - of course, 12 senators per a state is feasible when you only have six states (plus four more to represent our two self-governing territories), with 50 states it would produce 600 Senators
Currently minimum 4% of formal first preference votes, which gets you $3.499 per a first preference vote (indexed to inflation every six months)
Then you automatically get paid the first $12,791, and the rest of the funding is by reimbursement of substantiated election expenses.
This is per a candidate (lower house) or per a group (upper house). And this is just federal elections - state election funding is up to each state, but I believe the states have broadly similar funding systems.
Note the US also has public financing for presidential campaigns, which is available to minor parties once they get 5% or more of the vote. But in the 2024 election, Jill Stein (Green Party) came third on 0.56% of the popular vote. The only third party to ever qualify for general election public funding was the Reform Party due to Ross Perot getting 18.9% in the 1992 election and 8.4% in the 1996 election. There is also FEC funding for primary campaigns, and I believe that’s easier for third parties to access, but also less impactful.
And the Parliamentary Joint Committee on Intelligence and Security definitely gave the literal thousands of submissions due consultation before recommending the original, un-split bill pass.
Combined with the quirk in Australia’s preferential voting system that enable a government to form despite 65% of voters having voted 1 for something else.
As a result, Australia tends to end up with governments formed by the runner up, because no one party actually ‘won’ as such.
I can think of an exaggerated scenario though in which that sounds reasonable depending on the goal:
say preferences are 1 (low) to 5 (high).
suppose 65% of the population ranked candidate A at 5 and B at 4, and the other 35% ranked A at 1 and B at 5. the majority doesn't get their favorite choice, but they do get an outcome they're happy with, and the minority doesn't have a horrible outcome. Exaggerated, but I don't think situations like this are unrealistic.
Absolutely, of course there are secenarios where it can work well.
Where it fails is when one major party is saying: we will drive up energy prices with Net Zero ideology, make housing unaffordable, import foreigners at a ratio of 5 to 1 local births…
And that other party is offering the same to a higher degree.
There are other options. Pauline Hanson’s One Nation party is polling strongly. Let’s see if that results in actual votes.
South Australian state election coming up 21st March this year - I’m encouraging everyone I know who lives there to at least listen to Michelle Grattan podcast.
18.9% as recently as 1992. I predict we will have a similar viable third party showing sometime in the next few elections due to the radical shift in the party system that AI is causing as we speak. I really hope Yang Gang can rebuild itself and try again, maybe without #MATH.
"The reasonable man adapts himself to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore all progress depends on the unreasonable man" - George Bernard Shaw
In the US, there are tremendous structural barriers for third parties. They exist, it is just extremely difficult for them.
The centralization of power of each of the two dominant parties nationally at the expense of a more decentralized parties with strong state variability as in the past, makes it even more difficult for third parties to gain traction against all that coordination.
Perot had the best chance, but managed to blow it by bowing out and then back in.
I do think you are right, that times of great dissatisfaction are rare openings for third party candidates, if someone special enough appears. 2020 would have been a great election for that - but an inspiring third party candidate can't be manufactured on demand.
People have a choice between being rational and optimizing the alignment between the outcome and their preferences, or being irrational and doing something else, like not voting, spoiling their ballot, voting for a probabilistically infeasible candidate, voting "on principle", "sending a message", etc.
I don’t recall the circumstances under which Morrison ended up Prime Minister.
Like most Australians, I’m in denial any of that episode ever happened.
But, using the current circumstances as an example, Australia has a voting system that enables a party to form government even though 65% of voting Australia’s didn’t vote for that party as their first preference.
If the other party and some of the smaller parties could have got their shit together Australia could have a slightly different flavour of complete fucking disaster of a Government, rather than whatever the fuck Anthony Albanese thinks he’s trying to be.
Then there’s Susan Ley. The least preferred leader of the two major parties in a generation.
Hmm. Actually, I think the suggestion of a law puts this whole thing on bad footing where we need to draw an otherwise unnecessary line (to denote where this type of rhetoric should be legal). I suspect XorNot just put the line there because the idea that true statements should be illegal just seems silly.
Really it just ought to be a thing that we identify as a thought-terminating cliche. No laws needed, let’s just not fall for a lazy trick. Whether or not it is true that lots of people agreed, that isn’t a good argument that they are right.
The case of Nixon really brings that out. The “Silent Majority” was used to refer to people who didn’t protest the Vietnam War. Of course, in retrospect the Vietnam War was pretty bad. Arguing that it was secretly popular should have not been accepted as a substitute for an argument that it was good.
> We really need a rule in politics which bans you (if you're an elected representative) from stating anything about the beliefs of the electorate without reference to a poll of the population of adequate size and quality.
Except that assumes polls are a good and accurate way to learn the "beliefs of the electorate," which is not true. Not everyone takes polls, not every belief can be expressed in a multiple-choice form, little subtleties in phrasing and order can greatly bias the outcome of a poll, etc.
I don't think it's a good idea to require speech be filtered through such an expensive and imperfect technology.
The more important question is, are you content with simply dismantling any progress in accelerator science at all for the next century? Because the LHCs successors won't be online till the 2050s at least. If you don't fund them now though and start the work, then no one does the work, no one studies the previous work (because there's no more grant money in it) and the next generation of accelerator engineers and physcists doesn't get trained and the knowledge and skill base withers and literally dies.
Because the trade off of no new accelerators is the definite end of accelerator science for several generations.
Plantation lumber is a very sustainable industry, and plastic's environmental impact is highly context dependent.
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