Don't get me wrong. I love LLMs and use them myself. But the biggest gain for me is easier context switch and text manipulation. It's not the: replace X with a bunch of LLMs every CEO is dreaming of. So yes, you have higher productivity, but is the eval of those companies legit? x doubt.
By the time you see the applications, the market will have moved on to value the next set of future cash flows.
If the market only valued the obvious, investors would jump in to buy the price up, until it met the average expectations.
The market might be wrong, but the question is not: "Have you yet to see?", but rather, "What do you see in the next three to five years?"
Otherwise, how could investors ever invest in a startup?
Startups never have revenues to justify their initial valuations.
It's a bet on the future.
Investors are future looking.
Consumers are present looking.
We didn't see LLM harnesses coming even two years ago. Now they generate billions per month.
Investors can't wait until reality materializes to make their estimations of the future.
That's why investing is hard.
You have to try to predict the future.
Sir, this is a casino/Keynesian Beauty Contest.
Markets value what the market participants think the other participants will value. On occasion, this intersects with reality.
I find it interesting that using lines of code as a metric is making a comeback.
How many millions of emails do you think are composed using ChatGPT? How many legal briefs were reviewed by AI? How many businesses use AI generated art? How many kids do their homework using ChatGPT?
The GP is arguing that AI has struggled to replace humans, but in so many roles AI is doing the heavy lifting and humans are copying its output.
The homework "help" industry (i.e. paying for answers) is dead. Chegg stock fell 99% because of ChatGPT.
Stock photography is rapidly dying, nobody will pay for shutterstock when ChatGPT can generate a passable image for free.
ChatGPT is killing studio photography, it can generate great looking studio photos for free.
Same with basic graphic design / custom art commissions.
SEO / copywriting has been almost fully replaced by AI. Companies no longer pay writers to churn out SEO slop, and now the web is full of AI generated SEO spam.
Customer service as a job is dying and is rapidly being replaced by AI chatbots.
I can go on, but these are the major ones.
On top of that, you are showing another stark bias in considering the US experience as the global experience. It is not, and education in particular works way differently, aka, it's not a business wild west.
Cognitive surrender in writing emails is another shaky ground: do you honestly think that AI's worth the tens of trillion the tech bros are claiming it'll be worth as a glorified email-maker?
I will add that my point still stands. If you say this:
>>ChatGPT is killing studio photography, it can generate great looking studio photos for free. Same with basic graphic design / custom art commissions.
the only point you're proving is that you don't understand shit about photography as a business, nor about design as a business. AI is being rapidly integrated, for sure, but it has not upended those industries, and the average mediocrity it produces (because of its very nature) is not even close to replacing what you claim it is.
You asked about data, and I have it, and here it is: Chegg's CEO explicitly stated in their earnings call that ChatGPT was directly responsible for their collapse. Chegg stock fell 99%. You can verify this fact yourself. ChatGPT led to the near-destruction of a $14 billion company.
On photography and design: your counterargument is entirely assertion. You're claiming I don't understand those industries without demonstrating that you do. There is demonstrable fact AI has absolutely upended both industries. AI has gutted the commodity tier that constitutes the vast majority of revenue volume. Product shots, website graphics, social media content, marketing material. AI produces this content for free, at a quality so good that millions of people don't realize it's created by AI. You only consider the high-end, professional market, which so far has been relatively untouched.
Your only valid criticism is that my argument is US-centric. Fair enough. But ChatGPT has 700 million users globally, and you've produced zero evidence that non-US markets are insulated from the trends happening in the US.
Chegg shares drop more than 40% after company says ChatGPT is killing its business https://www.cnbc.com/2023/05/02/chegg-drops-more-than-40perc...
Otherwise Github wouldn't have 14% down time in the last 3 months.
What is _the proof_ if all the proofs are not _proofs_?
I don't babysit my LLM based services which are used by coaches and clients around the world. One of my LLM based solution get 30-4k daily hits and I have users coming back on the regular to use it. without babysitting, doing things that would take them hours of manual work and research.
I don't babysit the developers I work with and our clients, which both use LLM's themselves and at scale with their clients, serving all kinds of LLM powered services to millions of users worldwide.
You are not "seeing" the large adoption because:
- The technology is "a few years old" in its usable state - The corporate adoption cycle is slow - You have to understand the technology to use it in a good way, which most corporate devs and PM's do not
So it will take a bit for the "obvious" adaptation on large scale.
But you won't "know" when the large adoption happens.
Silent inference is growing every day, and that is what real adoption looks like - not an LLM being in your face chatbox, but running in the background, sorting, finding, fixing things, aligning data, figuring out analytics, tuning the ads, cleaning the datasets.
What a story this is
I am a radiologist and researcher predominately focused on AI.
You could also look at the market, one of the biggest players, Paige, was acquired for about 30% of the money they raised.
Anecdotally, my practice has most FDA approved AI deployed as we are an evaluation site and very rarely is the AI result useful. Over the past few months we have been cancelling contracts as these cost quite a lot of money (in some cases eating >50% of the study interpretation cost) for little to no benefit and a LOT of noise.
Do you think this will result in more routine/boring/tedious tests? Is the bottleneck on these things the human time to analyse them?
For some things, like 3D volume segmentation of structure or disease (e.g. CVA/stroke volume, cardiac muscle mass, iron quantification) the bottleneck is the time it takes so we currently use approximations like single longest dimension, circular regions of interest, etc. AI will dramatically increase accuracy allowing for more accurate treatment and easier large scale research with quantitative endpoints.
Other things people think of like detection of aneurysms, fracture, lung nodules are not “hard” but AI has already added and will continue to add the second-reader benefit which will reduce detection errors. For this category the clinical benefit is as of yet unclear and we know that increased detection does not necessarily translate into improved patient outcomes and can in fact make them worse from over-diagnosis which means investigation related harms and over-treatment.
We were already in a phase of “over detection” in much of radiology with advances in imaging technology so the incremental benefit of current AI remains to be seen and I personally think is going to be much more limited. I had a case recently where a 2 mm brain aneurysm was missed on 3 CT scans over 10 years but was picked up by AI so now is being followed annually. This is too small to treat considering the risks and a serious argument could be made that 10 years of stability is proof enough that this is almost certainly clinically irrelevant for this patient.
Far more interesting areas of AI in imaging are in acquisition of acceleration (i.e. the medical equivalent of upscaling) which can dramatically decrease costs and increase accessibility as well as analyzing imperceptible features.
It may not be a popular take here but in my opinion the future of radiology is like what we see in software engineering today - a skilled human equipped with AI will outperform humans without AI and AI without humans, the latter of which we are still several years away from prototyping due to various technical hurdles.
> in my opinion the future of radiology is like what we see in software engineering today - a skilled human equipped with AI will outperform humans without AI and AI without humans
I suspect this will be the case across the board. It's a useful tool, but it's just a tool. It's not a replacement.
They will never beat the human instinct tho, but they can be great tools sometimes. Unfortunately, LLMs mostly produce garbage.
In real life pathology is a spectrum not a binary and physicians are not trained to be 100% accurate instead optimizing sensitivity and specificity considering pretest probability as well as the harms of overdiagnosis and under diagnosis for a given scenario.
For something like melanoma which is relatively easy to diagnose with a superficial, extremely low risk skin biopsy and where early staging dramatically improves outcomes you would want to design around overcalling (high sensitivity) rather than maximize accuracy given the significant harms with false negatives and minimal harms with false positives.
An AI may be more accurate at classifying melanoma/not melanoma but if it does not meaningfully improve on the clinical threshold of biopsy/no biopsy or result in less biopsies that accuracy is wasted and may even be detrimental.
Note: I am just using this as an example to illustrate the considerations.
Essentially the cutting edge reaches up to 99% of human performance on the task it is trained, which is good enough for triage but not for a final diagnosis. However, magic sometimes happens when you train a model to detect something, which you already know is there, on an examination that is cheaper, faster or less invasive than the human"gold standard". Conveniently, this dataset exists since it's common to first do a cheap examination like an X-ray, and then escalate if nothing is found (or if something is found that you want to see better, or a number of other possibilities).
Examples of AI outperforming humans like this includes AI detecting sacral fractures on x-rays better than radiologists (who normally take a CT to conclusively exclude it), detecting potential precursors to pancreatic cancer on non-contrast CTs (where contrast or an MRI is usually required) and detecting an occluded coronary artery on an ECG without the archetypical "ST-elevation changes".
See the link below for references: https://pmc.ncbi.nlm.nih.gov/articles/PMC9478257/ https://www.nature.com/articles/s41591-023-02640-w https://rebelem.com/a-winning-hand-in-cardiology/
So AI, as a general rule, doesn't usually match or exceed the upper bound of the "gold standard" medical performance. But it tends to carry the quality of the upper bound downwards towards the faster, less expensive and invasive methods. In some cases, like in the case of EKGs, that's huge. In some cases it saves time, in some cases it decreases miss rates from tired radiologists or triages their review feed. And in some cases it's not very useful.
LLMs doesn't come close to specialized radiology models at the moment, because LLMs are more about applying knowledge than creating new correlations. Of course that's also hugely useful, but that's a bit of a different topic to unpack.
A self driving car doing better than a drunk on the freeway doesn't reassure me that it'll do better than sober me in a snowstorm.
I also question if the kind of person who actually drives while drunk - knowing perfectly by thousand of society inputs and peer pressure that it is wrong - will care enough to buy a self-driving car.
A whole lot of doctors, if not most, didn’t pick their profession out of an interest in medicine…
Also, keep in mind that a stock price discounts expected future cash flows. Is it likely that SpaceX will have a near-peer competitor within a few years? No, it's not, and that market share is being priced-in.
If there exists sufficient demand for the product of space launches then it's probably reasonable to expect their to be a near-peer competitor soon, but that's only if SpaceX were to be profitable, which it isn't, even with the subsidization by Starlink on the order of many billions.
Space is not that easy. Even with unlimited money, it'll probably take 10 years to build a rocket like starship. Going from nothing to orbit needs a lot of money but more money doesn't make that faster.
But other than that, yeah - outside of China, progress has been horrendously slow & Blue Origin, the only other US company that demonstrated a partially reusable rocket just had a devastating pad explosion, destroying one of their 2 rockets and their only launchpad.
This can't be treated as meaningful, given other projections and goals (Mars colony, etc.).
Although realistically this will be built from lunar materials, you still need to lift a lot of mass to build the necessary industrial processing and mass drivers to launch it from the Moon to some Lagrange point.
And there are many other useful space megastructures that can be built in space from common materials, like giant solar arrays beaming power down via microwaves: https://en.wikipedia.org/wiki/Space-based_solar_power
Most of these proposals date from even 1980s.
Were we struggling to do this before? Was the overall percentage reduction in costs? Was some other achievement held back because we couldn't accomplish this? What is now enabled?
> to get any payload into space.
A limited set of payloads into space. No vehicle can get "any payload" to space at a fixed price.
> The benefits are easy to miss,
You've listed a bunch of reasons to publish papers. What is the actual ground level change that's occurred? Are those antibiotics produced? Do they actually work just as predicted? Why is that first world problems are exclusively listed but basic problems like world hunger are never even approached?
> or wouldn't have within our lifetimes.
And your life, your actual life, benefits, how?
We literally couldn't.
> Was the overall percentage reduction in costs?
Starship will bill NASA 1/20th what SLS does.
> What is now enabled?
LEO. Artemis. Out of all of these companies, being confused about SpaceX is super weird.
But now he's also trying to get the indexes to pay for the giant cash fire called X.ai and the far right huddle Twitter too.
I have zero interest in owning anything of either of those companies.
Is that before or after the program achieves profitability?
Yes. The thing that’s going public is almost entirely an AI play.
Starlink has made connectivity cheaper and more available. Earth imaging has made various food production processes more efficient. Weather forecasts have become more accurate.
If you’ve genuinely missed the massive economy that LEO has become, it will be a fun thing to catch up on.
Yeah that's working out great for the average American isn't it (https://natlawreview.com/press-releases/2026-consumer-trust-...)
> Earth imaging has made various food production processes more efficient.
I'm not even going to bother sourcing the fact that food prices have only massively gone up negating any gains in productivity. The average American struggling to buy basics like eggs and meat aren't feasting on more efficient food production.
> Weather forecasts have become more accurate.
I'm sure the growing homeless population is happy to know they can better predict the weather they'll be sleeping in.
This is all totally worth supporting a nazi billionaire
Yeah. It did. My neighbour’s rates went up. He switched to Starlink.
> not even going to bother sourcing the fact that food prices have only massively gone up negating
This is like arguing fertilisers are useless because prices went up.
> homeless population
Not super relevant!
> all totally worth supporting a nazi billionaire
Nobody said that. But it doesn’t mean the benefits go away.
SpaceX’s main customer is Starlink. With that in mind: if Starlink takes over all the ISPs in the world its market value should be comparable to Comcast - $89 Billion.
It has massively improved both. The cost, resolution and frequency of imaging has decreased alongside launch cost.
> if Starlink takes over all the ISPs in the world its market value should be comparable to Comcast - $89 Billion
Why? Comcast isn't "all the ISPs in the world." (And Comcast doesn't get defence contracts to build and maintain military networks.)
Reusing rockets reliably rather than "throwing them away" is a great achievement and I'm surprised people have to justify it on HN
You can milk a cow only a set number of times!
What probability you assign to arrive at that expected value and how you adjust for risk is on you.