Ah, you are right, I've been misinformed this whole time! Not created by Cal Academy.
I am a little unclear on what you mean by not science. The secrecy around their models certainly makes them not open, but are you saying that any research based on the data is not science?
I am a huge fan of iNaturalist and the concept of citizen science. I am into herping, birding and scuba diving and I post pretty much all of my photos there. I have about 5000 observations and am approaching 2000 species. I have a private "project" with some good friends. Some of my observations are incredibly rare and one of them was even featured on their social media.
While I started using iNaturalist initially to satisfy my own curiosity about the animals and fungi I was seeing, and then expanded my usage to contribute to science in some small way, a huge unexpected benefit has been having my photos catalogued and findable by species, family, date or location. If I want to show a friend the monitor lizards I saw fighting over a huge fish in Thailand, I can find it no problem even if I don't remember exactly when that was. If I want to show someone all the cool frogs I saw in Indonesia, easy. If I can't remember where it was that I encountered a gray fox casually strolling down the trail, I can find it. Google photos and other AI tagging solutions are never going to be accurate and detailed enough to be useful in this way.
It is really an amazing tool with a shockingly friendly, welcoming and helpful community, in stark contrast with the eBird community which I find is quite unwelcoming to beginners. For example, if you make a questionable ID on iNaturalist, folks from the community will suggest what they think it might be. If you claim a rare bird on eBird you can expect a gruff email demanding evidence, or you may have it removed from your list pre-emptively. That experience may not be universal, but I have seen it multiple times. Telling people on the internet they are wrong is a favorite activity of many so I really think it's commendable the culture that iNaturalist has been able to foster.
For those who don't know, iNaturalist was created by and remained a part of the California Academy of Science until relatively recently when they were spun off into their own nonprofit entity.
For a while now the long term vision, product and engineering decisions they are making have been a bit questionable to me. The web version feels like abandonware and has some very clunky experiences. The iOS and Android apps function differently and have separate longstanding bugs, don't support all the functionality of the web version, and are also mostly abandonware while the eng team focuses on a new app that is a rewrite. Seek feels like it's trying to be Pokémon. iNat next, the new version of the iNaturalist app, has a nicer look and feel but seems like it will be released missing functionality both from the old apps and from the website.
I am not sure how important my own gripes are as a power user, perhaps in the end it will be better for new users, but it sort of feels like iNaturalists goals as an organization may not be as aligned with the original charter as they once were. For the purposes of financial stability it is probably most important to grow the user base. For the purposes of supporting citizen science initiatives it's probably more important to grow geographic distribution and the number and diversity of observations submitted, so a more balanced approach to growing the user base and supporting power users (and converting new users into power users) would probably be the approach more aligned with their original goals.
This is the norm at large tech companies and, IMO, a huge problem and major detriment to productivity within organizations as the cost of that added complexity is paid by everyone.
BUT, at least very occasionally I have seen people get promoted for simplicity, I've even successfully made the case myself. With a problem that was itself so complex that it was causing fires on a regular basis, and staff & principal engineers didn't want to touch it with a ten foot pole. When a senior eng spent a couple of weeks thinking about the problem and eventually figured out a way to reframe it and simplify the solution, melting away months of work, making the promo case was actually quite easy.
The problem is, the opportunities to burn down complexity like that don't present themselves nearly as often as the opportunities to overcomplicate a thing, which are pretty much unbounded.
I had a neighbor who mounted his TV directly on the shared wall to my bedroom in violation of the lease terms. The wall was hollow and seemed to not only conduct the sound into my bedroom but act as a natural amplifier.
I offered him a nice speaker system I wasn't using but he said he didn't know how to connect it to the TV. I offered to do it for him but he refused. I offered to pay a professional and he still refused. I was forced to move my bed into the living room so I could sleep through the night as he started his day by watching the news at full blast at 3am.
Naturally, in response I propped those speakers to the same wall and played whale calls at a low volume any time I wasn't home.
My hot take is that AI is shaping up to be a tax on big tech.
Yet another round of layoffs being blamed on AI. As with last time, this is not due to productivity gains from AI, rather it's due to wanting to reallocate budget towards investing in AI. (and maybe an excuse for something they already wanted to do)
I think some productivity gains from AI are real, and I've experienced some firsthand, but reductions in force being ENABLED by AI are not, and I don't think we will see much of that for a good while still.
AI is attracting a lot of investment dollars because it's seen as disruptive; the capabilities it potentially unlocks for people are enormous. The problem is that general intelligence is still far away (fundamentally cannot be reached with the current approaches to AI, in my opinion), and the level of investment required is so high that the only way folks are getting that money back is if it does enable a level of layoffs that would be crippling to the economy.
Additionally, there is not a huge difference between the top models, and thanks to the massive investments the models are incrementally improving. It seems obvious from the outside that AI models are going to be a commodity, and good free models put downward pressure on prices, which they are already losing money on. So I think it's going to be a race to the bottom, and is very unlikely to be a winner-takes-all situation.
I think this means that the reward for big tech companies pouring insane amounts of money into AI will be maintaining their current position, or maybe stealing a bit of business from each other. That's why I think AI is more of a tax on big tech than a real investment opportunity.
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