EVs are still a bit underwhelming wrt range - ideally either 450miles/700km or 5 minute 20->80% recharge at an acceptable price (35k EUR) should be the norm. For cities it doesn't matter but for longer vacation trips it's a must, nobody wants to waste 3 hours on a 1100km trip recharging. Chinese EVs might be able to deliver it at this price point (BYD) but EU adds additional (up to) 45% in extra fees to penalize Chinese EV makers and to prevent collapse of EU car makers.
1 in 4 vehicles sold globally last year were EVs, and they are >50% of the monthly sales in China, the largest market in the world. EVs are mostly solved, even though they will continue to rapidly improve, both range and charging infrastructure. Norway is at ~100% monthly EV sales, other countries will get there eventually.
Importantly, we should expect to go faster as EV sales reach a point where combustion sales have declined to a level where they can no longer support combustion vehicle manufacturers as a going concern. Peak global combustion auto sales occurred in 2017.
The trend is clear but right now they aren't able to replace ICE cars due to what I mentioned above. Either they lack range/recharging convenience or they don't but are too expensive. They need a few more years of scaling or EU to stop penalizing Chinese EVs.
ICE =! NEVs (which includes BEVs and PHEVs, with BEVs still the majority). If folks want to buy PHEVs until BEVs steamroll them, whatevs, the BEV cost decline and uptake curves speak for themselves. Combustion isn't getting cheaper anytime soon.
The issue with radiologists is that on average they are able to spot ~35% of correct diagnoses, while the world's best radiologists ~45%. AI might get us to ~50% which is ~15% better than an average radiologist (who still needs to review it).
Maybe radiologist mean something different in my country, but here radiologist don't diagnose (i mean, except you see them for a broken bone or something), oncologist do. I did an observation internship with a radiologist when i was 20 (95% of my family are doctor/nurses/PT, i wanted to know what a degree in physics could help me do in the field, and radiologist was the only path to medecine from my initial formation where i only lost a year, and not two). You spend your time calculating doses, finding patient history, and calibrating machines, it's much more a technician role than a MD. In any case, and even if in the US radiologist diagnose cancer, that's such a small part of their job it shouldn't matter.
Its fine to ask for sources. It's also fine to not give sources when relaying information in freeform comments. It's not fine to ask for sources in the tone you are using though, as though you are annoyed and simply expect sources to always be included with claims. There are better ways of accomplishing your goals.
Someone drops very specific percentages about diagnostic accuracy....numbers that, if true, have serious implications for patient outcomes, and your concern is that I did not ask nicely enough for a source? I could not think of a more HN typical response...
I did not even call the claim false, even if it almost deserve it...I said, essentially ...let's see the references so we can treat this as fact rather than opinion.
What you did is write a longer and more prescriptive comment about my tone than anything anyone has written about the actual substance :-)). You tone policed a one line request for evidence while giving a complete pass to unsourced medical statistics presented as fact.
If we are ranking things that erode discourse quality, I would say you are higher on the list.
My tone attacked a passive aggressive, entitled, and lazy comment. Calm down and just learn a better way to approach things. Other commenters skeptical of the claim approached it in a much more mature manner.
Three comments in... and you still have not said a single word about whether radiologists actually catch 35% of diagnoses. But you have found time to call me passive aggressive, entitled, lazy, and immature. For one sentence. Asking for a source...
You are now, multiple comments deep, doing the thing you accuse me of...being more invested in tone than substance.
^ Knowing this, I would believe the best course of action for a hospital administrator would be to implement a "blind workflow" to reduce risk & lawsuits.
A radiologist should separately review a scan, an AI separately review it, and then combine the 2 results for review.
I worry that rational takes like this end up completely lost in the battle between motivated parties who yell far louder, but have minimal investment in actual outcomes for those who will be depending on these technologies. The debate over self-driving vehicles is another example.
If your original argument was “it could be useful for more difficult/niche observations” then I think most of us wouldn’t have objected.
I also really don’t understand why you still aren’t sharing any links. Is this all LLM-generated without citations or something? Where are you getting your numbers?
How about we started replacing all companies that are replacing humans with AI using AI as well? As they decided to one-way participate in the economy (suck the money, not give anything back), we can make sure the one-way trend is done with rapidly. The cost of running a company will approach zero in the future. We now have massively profitable companies that are making record layoffs; something doesn't compute.
It would be interesting to start a co-op or non-profit run by AI for the benefit of the employees and customers. If it worked it would have a huge competitive advantage. I guess the question is where would the capital come from, but as a co-op the employees could buy in and just take the profits as a distribution.
Thinking about this some more: US tax laws really favor income from investment over income from wages. So ideally a co-op member would put something in to join, get a wage, and have an appreciating asset in a tax advantaged account.
"The Helios 44-2 is a very popular Soviet-era lens among cinematographers" - yeah, not like there were any other Soviet lens available there. Legendary in this context means the only ones anyone there could get their hands on. I bought Zenit ET with those and can't say they were amazing compared to my Nikon or Sigma lens. Exotic factor is likely in the play here.
If it was just a simple matter of "what was available" these lenses would be an interesting footnote in Photography history. But that's not the case, people still buy them for their unique properties 50 years later and the fact a company exists to re-house them more than proves their legendary status in my mind.
There is a phenomenon I observe with people being fascinated by russian/soviet things even when in reality the subject of interest is pure shit.
Being it either a low quality lenses in which people see a artistic quality of manufacturing defects or text from Dostoevsky which ruminates in extended length the inner thought process of a moronic character which some mistake for a mysterious russian soul.
I own Helios lenses with Zenit camera I inherited from my father which is of the sentimental value as it was a first significant purchase after my parents wedding, and most of my childhood photos are done with it, but even my dad will trade it for a good Nikon lenses without a second thought.
The swirly effect is certainly unique, though I always considered it a bug as it's not even, some parts look oversharpened, some diffused. Like some weird algorithmic filter in Photoshop.
There are still many major oversimplifications in the core of math, making it weirdly corresponding with the real world. For example, if you want to model human reasoning you need to step away from binary logic that uses "weird" material implication that is a neat shortcut for math to allow its formalization but doesn't map well to reasoning. Then you might find out that e.g. medicine uses counterfactuals instead of material implication. Logics that tried to make implication more "reasonable" like relevance logic are too weak to allow formalization of math. So you either decide to treat material implication as correct (getting incompleteness theorem in the end), making you sound autistic among other humans, or you can't really do rigorous math.
People keep getting hung up on material implication but it can not understand why. It's more than an encoding hack--falsity (i.e. the atomic logical statement equivalent to 0=1) indicates that a particular case is unreachable and falsity elimination (aka "from falsity follows everything") expresses that you have reached such a case as part of the case distinctions happening in every proof.
Or more poetically, "if my grandmother had wheels she would have been a bike[1]" is a folk wisdom precisely because it makes so much sense.
Material implication was not the default implication historically; it came as a useful hack by people who hoped that by enforcing it they could formalize the whole math and knowledge and have a sort of a "single source of truth" for any statement, and evaluate all statements purely syntactically. This proved to be futile as incompleteness theorem showed, and which material implication directly enabled by allowing self-referential non-sense as valid statements. There were many attempts to reconcile this with different logics but they all ended up weaker and unable to formalize all statements. We are now entering the next phase of this attempt, by using hugely complex reasoning function approximators as our "single source of truth" in the form of AI/LLMs.
I used to do a lot of proofs coming all the way from Peano arithmetics, successor operators and first-order tableaux method.
Rigor is one solution to mutual understanding Bourbaki came up with that in turn led to making math inaccessible to most humans as it now takes regular mathematicians over 40 years to get to the bleeding edge, often surpassing their brain's capacity to come up with revolutionary insights. It's like math was forced to run on assembly language despite there were more high-level languages available and more apt for the job.
> It's like math was forced to run on assembly language despite there were more high-level languages available and more apt for the job.
I'm not a mathematician but that doesn't sound right to me. Most math I did in school is comprised concepts many many layers of abstraction away from its foundations. What did you mean by this?
My math classes were theorem, lemma, proof all day long, no conceptualization, no explanation; low-level formulas down to axioms. Sink or swim, figure it out on your own or fail.
This has some grain of truth though companies would only execute your ideas if they don't destroy their own business. Imagine creating your own Bloomberg Terminal/Capital IQ using agentic AI - you'd directly attack incumbents and not give them more profitable ideas. For potentially profitable ideas one could just look at all companies Google/Meta bought in the past and killed, then just redo them using AI.
I've recently bought 3x32TB (new) and 2x28TB (recertified) drives for a new NAS as my old one started running out of space on some drives (local LLMs and datasets or media for dataset preparations are huge these days) as I expect the prices to go up considerably due to most HDD manufacturers being booked years in advance already. Some drives don't even make it to retail at all (44TB Seagate).
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