Apples have some of wildest biology that I've seen as a non-professional biologist. At many genes, they carry two different alleles instead of two matching ones. They're almost all self-incompatible. A Honeycrisp flower cannot pollinate a Honeycrisp flower.
This means that you can't breed them in the traditional sense that we do with other plants. Outside of Granny Smith apples the ones you eat are mostly the results of mutations in the grown plants that we cut off and graft.
Heterozygosity and self-incompatibility are common to fruit trees in general, not specific to apples.
I think ancestral citruses (not the crosses) are the primary exception, as well as a few citrus hybrids which create clone seeds asexually.
> Outside of Granny Smith apples the ones you eat are mostly the results of mutations in the grown plants that we cut off and graft.
Honeycrisp is a chance seedling, though it stems from a horticultural crossbreeding effort it was grown from seed. And commercially useful sport mutations tend to come from popular chance seedlings to start with, since it is necessarily a more limited evolution of the basal cultivar, which needs to exist and in sufficient quantity that you’ll roll out useful mutations eventually (also useful is in the eye of the beholder as we can see with the red so-called delicious).
> Outside of Granny Smith apples the ones you eat are mostly the results of mutations in the grown plants that we cut off and graft.
Not sure where you're located, but this isn't true in the US. The vast majority of apples available here are seedlings of crosses by two other varieties. Examples:
Golden Delicious, one parent is Grimes Golden, the other unknown.
Fuji, Red Delicious × Ralls Janet
Gala, Kidd's Orange Red × Golden Delicious
There are certainly some sports (the technical term for for the spontaneous mutations) like you mention. Royal Gala, available in NZ, is a sport of Gala. But most are not.
An enormous amount of industry effort goes into crossing known varieties, growing the seedlings, and looking for the apples with the best traits. Cosmic Crisp is a great example of a recent one.
The coolest thing about some apple cultivars is how their story is "someone found an apple tree at the side of a road with tasty apples", and people kept grafting them to this day. Boskoop, for example.
Oh wow you may have just answered a question I been having. I planted some apple trees in my backyard. The AI helping me suggested 3 trees, one of which was a crab-apple tree that it said will be used to pollinate the other two. Maybe it lied to me. But i did follow its instructions. I was wondering why the other two (Honeycrisp and another delicious variety) could not just pollinate each other.
The GP comment is overstating the genetic differences and pollination difficulties. Most apples are not self-fertile. Pairing pollinators together has more to do with bloom times; some trees bloom earlier/later than others and trees need to have flowers out simultaneously.
> I don't see how any government or business (especially the former) can justify using X at this point
If your logic is that some citizens won't be able to read what is posted there, then I assume you similarly object to other social media platforms, newspapers, cable TV stations, etc.
If my local government or some local business was limited to using one specific newspaper, this would indeed be a problem.
And in reverse, having a concentration of readers (users) on one platform, means that whoever controls that newspaper (platform) gets to be kingmaker for the government and the businesses.
Free speech as a constitutional requirement binding on a government to allow it is great; that government then using one specific private corporation that can use its own status as a non-government actor to have free speech rights rather than free speech responsibilities, means it is a de facto loss of free speech for everyone else.
There is no constitutional entitlement to receive government information through one's preferred newspaper, website, or social network.
> it is a de facto loss of free speech for everyone else.
You seem to be confused about what 1A is and what it guarantees. It is a restriction on government action against your speech, not a general requirement that everyone have equal access to every privately owned communications channel.
OP's point is that creating a favored restricted platform natrually allows for restricting of free speech because of a private "compnay policy". ("allows for" is doing heavy lifting here btw)
Should a government choose to communicate essential facts only through a restricted medium it is obviously no longer serving the larger public interest and thus no longer a government of "a people for a people".
Musk and fellow techoligarchs can have their private platforms.
Free peoples' governments and responsible social organizations must treat them as 'for profit entertainment channels' and not give them any legitimacy in the political space.
Having the chat logs enter the training data and having them have a meaningful influence on the ultimate result the model produces are very different things.
The text for all the Goosebumps books are certainly in the training data and to some small amount influenced the solve. But their contribution was so vanishingly small it would seem absurd to say R L Stein should have recourse for contibuting to the solve.
The equivalent would be taking a (fully offline) LLM and asking it about the ending of one specific Goosebumps book, and it revealing the twist. And although that specific book was (probably) only once in the training data, a high parameter LLM can usually "remember" the twist.
The only way it would be able to tell you the ending is if it was somehow given more importance in pretraining, loaded into context, or represented in multiple sets of training samples. I have a blog that I make very LLM friendly and usually load posts up into context when I’m working on something relevant. I’ve also opted to improve models for everyone. Despite this, the model can’t recognize my site or any of my posts when I ask it to recall without internet usage (I also turn memory off btw).
That's not correct for a SOTA model with trillions of parameters. Those have immense amounts of knowledge trained into their parameters. Try it. It "remembers" the ending of random books, Goosebumps and otherwise.
That's the entire point of why knowledge cutoff is so important (if you use them offline).
I find it entirely believable that the Navier-Stokes conversation was auto-flagged as high value training data, and burned-in the models knowlegdge base.
Once they capature enough marketshare prices and restrictions are both going to skyrocket. The difference between the subscription usage and API pricing are stark.
This is interesting to think about. There's so much competition among the frontier labs and from outside via open source it just doesn't seem obvious to me they could maintain elevated prices
You’re going to get multiple tiers (as we already are). You’re always going to pay top dollar for frontier models, but you’re going to find things highly discounted if you’re willing to move off the frontier. See GLM 5.3 Flash, for instance.
Say things are going to suck and they suck. You look brilliant.
Say things are going to suck, and they don't suck. Nobody cares because it doesn't suck.
Say things are going to be good, and they're good. A few attaboys for getting it right, but nobody cares.
Say things are going to be good, and they suck. You look like a moron.
Because of negativity bias everyone is leaning towards predicting DOOOOOOOOOOM. People aren't even consciously doing this, it's just a factor of the medium, because looking like a moron hurts way more than a few attaboys.
I think in about a year, we're going to see a scad of these ASICS like chat jimmy running year old models on dedicated hardware. Imagine racks and racks full of Astra but running at 15,000 tokens a second or whatever? Imagine swarms of them running the models we have today essentially for "free." That's where we're going to be. The bottleneck will be production, tbh, not demand.
"Hey Astra-Silicon, solve the Goldbach Conjecture!" Sure, it might take a few hours and be totally un-readable to a human being, but the 6m lines of Lean or whatever will be correct. Then what? What can we start doing then?
I mean, kind of yeah? But like, there are already people working on the chips, there are already people designing the next hardware, etc. I'm sure we're going to get to a plateau in capability soon-ish? Exponentials are actually all sigmoids. But what does that look like? If the plateau in capability is 100s of times smarter than the average person (arguably we're already there in many many but not all domains) then in 10 years time last year's reasoning model etched into an ASIC or some crazy monstrosity built out of FPGAs but for LLMs is probably way more than enough for 99.999% of use cases?
But yeah, doomerism is the dominant narrative of the day here right now. There's a sort of eschatological poisoning that's happening presently. Nobody can even seem to imagine a world where things get better. It's crazy. Maybe it's because I recently went through a major illness, maybe it's because I hit my head one-to-many times along the way? But I've never been more optimistic about the future than I am now.
Crypto never did anything is the difference? The only people it did anything for were speculative investment types.
That said bitcoin is still at like $80k per bitcoin though... so while it's not a good investment IMO (and I don't really mess around with crypto except for the time I got drunk and bought doge and made money), but there are people out there still using it. There's a bitcoin ATM less than a mile from my house.
Ya, setting aside any judgement about what's "right", this strategy doesn't seem profitable. There's no real moat between one model/provider to another, switching is relatively easy. I don't understand how this is supposed to work for them.
It strikes me as similar to UPS / USPS / Fedex -- everyone uses the mail, and they mostly use whichever is cheapest for their requirements. I don't think there's much loyalty to specific services, and people are happy to switch between the options
just dont fall in love with goofy memory style features and its likely gonna be fairly easy to just plug and play whatever model for a ton of use cases.
I dont see a lot of love for weird memory like features on HN, but on provider subreddits its constantly talked about.
Every project I have tends toward coding agents over time partly for this reason - if nothing else, I want have both control, visibility and portability over memory and a log of the reasoning that went into the current state of things.
There is so much competition among frontier labs, but it is a competition to see who can burn the biggest pile of cash. Once your competitors flame out, they are gone, and you are free to raise prices. Think WalMart/Uber tactics.
This would need to be a collusion across most of the providers (which I think is likely to happen) otherwise OpenAI would get ditched for Anthropic or vice versa, depending on who raises the prices more. If it happens across the board then enterprises that can use Chinese models won’t have that many options but to pay up.
Harness and data seem like two vectors. It's also not clear to me that at some point we won't get a snowball effect from the platform that has the most use and thus the most training data just running away with a positive feedback loop.
Lol as far as I know that post was the origin of that claim and it's clearly just a guy predicting something that will happen in the future with no information about it.
Yeah, can't read anything on xitter due to the gigantic dickover they put over the content when you don't have an account. A screenshot would've been more helpful than an xitter link.
Most American military planners assume that if China invades Taiwan they'll use smaller "tactical" nuclear missles to do things like destory carrier groups to test the will of the US on MAD. Predicting, probably correctly, that the US will not respond with a full scale nuclear strike in response to the destruction of a military target just because nuclear weapons were used.
For me something the likes of: design a CDM for integrating these 5 logistical systems, with full docs and examples provided for each, as well as modeled transports specific to our business. Prompt was of course much longer.
Both failed spectacularly. But sol's output at least contained interesting findings and some useful parts, as well as not being 20000 words of unbearable language.
I have both set up with full access to all the repos at the company, infrastructure, deployment pipelines, etc.
I can tell Sol, "Hey we need to update this core database schema to handle this new use case" and it will masterfully handle the update, version the API, roll the consumers over, including versioning the Kafka schemas, deploying things in sequence, watching the deployments to make sure the new services act actually active before cutting over consumers, exercising the website and mobile apps in staging environments before releasing to production, etc.
Fable just falls over on long horizon tasks, it does partial implementations, it cuts corners, it gives up, it doesn't verify it's work, it loses track of what it's doing, etc.
It's fine for specific well scoped tasks but can't take high level guidance for complex updates.
Because Claude doesn't allow third party harnesses on their subscriptions I doubt the majority of signals you're getting are actually that significant on pure model quality.
I suspect you're right on Sol not outperforming Fable; but i've not used Fable that much.
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But, fwiw, in my custom harness between Sol & Opus 4.8 - then Sol wins by a ridiculous margin as Opus keeps claiming slightly wrong things with certainty much more.
what i found to work well with me is Fable for design / ideas and Sol for implementation. Codex models just tend to be more attentive and follow through instructions. Whereby claude models are weaker on this area (they tend to cut corners).
Claude models tend to cut corners during design/ideation too. It becomes especially visible once you pair Sol as advisor to Fable. Sol will start going crazy - "hey, you said this, and it's actually false, i checked that", or "you need a hash chained, triple encrypted, secure-enclave backed storage for this".
But I actually prefer it this way. Sol is a master of overengineering and being overly scrupulous, so Fable balances this out, and I can always say "don't listen to Sol's advisory" about 50% of the time.
I assume it cascaded from one provider to the other as people who lost claude access for instance moved to openai who moved to grok when it went down, etc.
Louis Rossmann said this too after he left NY but I feel that his content created when he was still in NY was "sharper". Perhaps a shitty government makes for better content even if they ruthlessly tax-milk the people there.
The local code enforcement situation is not great compared to a lot of other states due to how funding works (causes incentive to be predatory) but you probably won't notice coming from NYC.
This means that you can't breed them in the traditional sense that we do with other plants. Outside of Granny Smith apples the ones you eat are mostly the results of mutations in the grown plants that we cut off and graft.
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