> Business minded folks are already starting to deeply question where the value is relative to the amount of money spent on training
Kinda. In my experience, the bigger issue is the skillset has largely been diffused.
Overtraining on internal corpora has been more than enough to enable automation benefits, and the ecosystem around ML is very robust now - 10 years ago SDKs like Scikit-learn or PyTorch were much less robust than they are now. Implementing commercial grade SVM or <insert_model_here> is fairly straightforward now.
ML models have largely been commodified, and for most usecases, the process of implementing models fairly straightforward internally.
IMO, the real value will be on the infrastructural side of ML - how to simply and enhance deployment, how to manage API security, how to manage multiple concurrent deployments, how to maximize performance, etc.
And I have put my money where my mouth is for this thesis, as it is one that has been validated by every peer of mine as well.
I agree with you. My reference in business questioning value was on the flood of money going into building new models. That’s where we will see a significant and painful culling soon as it’s all becoming quite commoditized and there’s only so much room in the market when that happens. Tooling, security services and other things to build on top of a commoditized generative AI market opens up other doors for products to be built.
In my experience, there really hasn't been that significant of a flood of money in this space for several years now, or at least not to the level I've seen based on discussion here on HN.
I think HN tends to skew towards conversations around models for some reason, but almost all my peers are either funding or working on either tooling or ML driven applications since 2021.
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I've found HN to have a horrible noise to value signal nowadays, and people with experience (eg. My friends in the YC community) deviating towards Bookface or in person meetups instead now.
There was a flood of new accounts in the 2020-22 period (my hunch is it's LessWrong, SSC, and Reddit driven based on the inside jokes and posts I've been seeing recently on HN) but they don't reflect the actual reality of the industry.
I agree that the quality of the posts has decayed dramatically since the start of the COVID pandemic and lots of the Reddit type memes and upvotes have added horrible levels of noise. I can still find gems in it and it’s still miles ahead of Twitter, but I do question my time using it passively and would much rather have a smaller and more focused community again.
Been on HN off and on for about 9 years with different accounts. I do believe the comments are getting more difficult to parse (find the good vs noise) but still the best site I have found - is hand curated links and people willing to offer solid advice given a question in the comments. I use Reddit from time to time but only for pure time killing purposes. I have learned more from the comments on HN than any course, book or (other) web site. Hopefully it will stay that way for years to come. A smaller community could offer more quality responses but less chance of finding the person who has the answer to your question.
I’ve been in crypto since 2010 and HN hasn’t predicted anything. At least with AI the congnoscenti here is on board. With crypto / blockchain the current plan is to pretend it doesn’t exist and never speak of it, as the industry never imploded as was long predicted.
Deep down I fundamentally believe it's a solution searching for a problem. That said, if people want to put money into it, who am I to judge.
That said, IMO crypto as a growth story is largely done. Now that Coinbase has IPOed and the industry consolidated or wiped out (eg. Kraken, FTX, OpenSea), it's not as attractive an industry anymore unless some actual fundamental problems are found that can't be remediated by existing financial infrastructure (legal and illegal).
Hard disagree but even if all of the growth is done, you never would have captured a penny of it reading HN. It went from “scam” to “ponzi” to “government will surely ban it” to “ok it’s over no need to look at or speak of it”.
I'm not denying that there's money in the industry - every portion of the software industry can rake cash due to the extremely high margins that software has compared to just about any other industry.
The magic is finding which subsegments might have even higher margins than others.
Crypto used to have fairly high margins, but all the easy gains have been claimed by larger firms as it's a much more mature industry now, but portions of the ML space still have much more opportunity for growth, so it makes sense to deploy capital there (this is a very high level view so take with a grain of salt - B2C and SMB B2B and Enterprise B2B have entirely different GTM motions and path to profitability).
But at least for me, I can't justify participating in a Series A round for a crypto startup compared to an MLOps startup today.
It's still a scam even if bitcoin is currently benefiting from the creation of institutional ETFs. FTX was one of the largest financial frauds in history and the founder was disgraced and convicted. There's clearly a large amount of appetite for regulatory action in government right now and afaik the funding in the space has completely dried up. What did we get for all that trouble? A really inefficiet payments system? "Digital Gold"? A fun way to fund terrorists and drug running? Crypto proponents are delusional if they think they can just shake off the reputational damage they brought onto themselves in the past several years.
VCs learning nothing or cynically continuing to try and cash in on this scam isn't exactly an airtight argument, even if my original statement was wrong. FTX also raised a ton of money.
It’s just further proof that people commenting on HN confidently about crypto, do not have any idea what is happening in crypto. This website is not plugged in and you won’t pick up any information about it here.
Meh. Crypto is still a waste of resources that had no reason to exist. The modern art market hasn't crashed yet either, and homoeopathy is booming, too last I checked. Just because it's stupid and useless doesn't mean you can't sell it. (And if you underestimate the possibility of selling useless things, you end up incorrectly predicting the demise of the market a lot.)
Not wanting to be part of that is just having some morals. Grabbing money where you can isn't a sign of a successful life.
There are definitely still homeopathic treatments that work, but have not received the investment necessary to go through clinical trials (or haven’t caught on due to lack of recognition from insurance companies).
Kinda. In my experience, the bigger issue is the skillset has largely been diffused.
Overtraining on internal corpora has been more than enough to enable automation benefits, and the ecosystem around ML is very robust now - 10 years ago SDKs like Scikit-learn or PyTorch were much less robust than they are now. Implementing commercial grade SVM or <insert_model_here> is fairly straightforward now.
ML models have largely been commodified, and for most usecases, the process of implementing models fairly straightforward internally.
IMO, the real value will be on the infrastructural side of ML - how to simply and enhance deployment, how to manage API security, how to manage multiple concurrent deployments, how to maximize performance, etc.
And I have put my money where my mouth is for this thesis, as it is one that has been validated by every peer of mine as well.