Curious to know why you think it's vaporware. Are the latest LLMs like 3.5 Sonnet bad at original programming based on your experience? It hasn't been the case for me when using it for real world projects lately.
This is cool. There is a lot of hesitation to move significant assets from my Charles Schwab brokerage account. That's going to be my main hurdle. I need to understand the safety, trust, trading mechanics, flexibility that I have with Charles Schwab, all of those things become very valuable when talking about high amounts for retirement purposes. I don't really know what you can do there to attract such clients? Will anyone move $5m from their top tier brokerage to Double yet?
"Will anyone move $5m from their top tier brokerage to Double yet?"
I have!
But I understand that yes this is a hard thing to get people to move and trust, safety and trading mechanics are incredibly important. We are trying to be as transparent as possible on all those factors. I would love for you to try us out with a smaller amount first to see observe all the mechanics before making a larger move. We support full and partial ACATS transfers of existing stock positions (meaning you don't have to sell anything).
>> There is a lot of hesitation to move significant assets from my Charles Schwab brokerage account.
I'm incredibly double-minded about this. M1 offers essentially the same service and they do it very well. I've compared M1 vs Fidelity Basket Portfolio (which also offers yet almost the same service.) Here are my takes
- M1 is easy to use (mostly, though same super-strange UX choices)
- M1 is a pleasure to use
- M1 doesnt fail on the main features
- M1 Baskets of Baskets gets complicated, but understandably so.
- Fidelity is better in some ways as it allows trading anytime, not just on specific windows as M1 does (this can also be a downside for itchy fingers)
- Fidelity Basket Portfolios is broken 30% of the time. Their OWN buy function fails any time they cannot get a quote for any 1 member of the portfolio
- Fidelity: It is absolutely a headscratcher how, in 2024, Fidelity can have trouble getting quotes for liquid public stocks during market hours (e.g., the other day, their buy of an entire pie failed because they could not get quotes for "DVY" which is highly liquid
- M1 fails absolutely miserably on back-office functionality. Selling losing lots is almost impossible without major Excel wizardry since the accounting info is held separately in APEX
- M1 fails dangerously on things they should never fail on -- for example setting beneficiaries has been a 4-month journey and still remains unresolved. If you dont have a will, get prepped for Probate! Worse, the failure is a silent failure as it suggests on the UI that beneficiaries are set. You get different answers from different people and each wants to help you but runs from "complex" issues (in M1's case, they are designed to have a single account, so their backend features fail if you have multiple accounts (e.g., a RothIRA and a non qualified account.)
The dangerous, infuriating, and befuddling experience with setting beneficiaries on M1 lead me to stick to the majors (Schwab, Fidelity) because at least I can rest assured they have the basics solidly figured out. It also makes me very hesitant to go to startups for this sort of stuff
So the good news is that M1 doesn't use apex for clearing anymore
The bad news is that... things got worse? After they swapped to doing clearing in house, they dropped like a month of incoming wires without reaching out at all, until I noticed on my monthly login. Turns out that they had changed the underlying wire instructions (makes sense), but sent an email saying that nothing would change on transfer instructions (not true).
Then the next month, they still dropped wires even with the correct instructions, because... ???? unknown reason. Again no contact, until I reached out and asked wtf. Third month, everything worked even though nothing was changed from the prior month.
So there's a reason why I won't put more than SIPC worth in M1 or any other new fintech. And yes, it's backend incompetence as the primary reason.
I'd love to understand why this feature/product requires an entire startup. I dont mean to be dismissive -- obviously it does, as shown by my experience with Fidelity Baskets given they cannot achieve it!
Also, I used FolioFN and ShareBuilder for years to do the same and they seem to have flopped despite having a compelling product. I'd love to understand why such an obvious feature/product with sound alignment to financial recommendations cant seem to do well in the marketplace!
The only thing I use M1 for is to automatically purchase a 60/40 split of VTI/VXUS with any available deposits, so if double can do that, then maybe I'll check it out. If y'all are gonna charge a monthly fee down the road though, it's probably not for me.
I love the science of evolution in that there's no need for an underlying model for such an invention to actually verify the science and the possibility of it, just that such an invention is possible. Basically anything and everything is possible with evolution and that doesn't really feel like science to me.
Indeed, evolution is basically trial and error, where the trial is life, and the error is (untimely) death.
I'd argue that it's not science at all, because what's missing is the coordination behind it. To me, evolution is not a product of conscious effort, but an emergent behavior or the individuals and systems that participate.
Taking the "science" definition from Wikipedia: "Science is a rigorous, systematic endeavor that builds and organizes knowledge in the form of testable explanations and predictions about the world". With evolution, testing definitely happens, but it's not a systematic endeavor, or at least I'm not convinced that it is.
I am still glad they exist. If this thinking was very prevalent among AI pioneers (which it probably was for companies like Meta and Google, that's why failed to innovate here), we wouldn't have gotten revolutionary products like ChatGPT.
For me the fundamental question remains if it's a matter of the right input data (beyond language) or is there something about our brains that cannot be replicated by artificial neural architectures for it to discover new knowledge and invent new things for humankind.
I mean are we as humans planning ahead of the new few words? I certainly am not. But what matters is a deeper understanding of the context and the language model itself, which can then produce sensible spontaneous output. We as humans have the advantage of having a non language world model as well as abstract concepts but all of human language is a pretty strong proxy for it.
The spontaneity of it isn't the issue, it's what's driving the spontaneity that matters. For e.g. 1M context window is going to have a wildly more relevant output than a 1K context window.
> I mean are we as humans planning ahead of the new few words? I certainly am not.
For me, sometimes either way. At least, that's my subjective self-perception, which is demonstrably not always a correct model for how human brains actually work.
We also sometimes appear to start with a conclusion and then work backwards to try to justify it; we can also repeatedly loop over our solutions in the style of waterfall project management, or do partial solutions and then seek out the next critical thing to do in the style of agile project management.
Many of us also have a private inner voice, which I think LLMs currently lack by default, though they can at least simulate it regardless of what's really going on inside them and us (presumably thanks to training sets that include stories where a character has an inner monologue).
> I mean are we as humans planning ahead of the new few words? I certainly am not.
Sometimes we do, sometimes not.
Sometimes we just say stock phrases such as "have a nice day", or "you too" that are essentially "predict next word", but if I asked you something you'd never done before such as "how can we cross this river, using this pile of materials" you'd have to think it though.
Some people may use their inner monologue (or visualization) to think before speaking, and others may essentially use "chain of thought" by just talking it though and piecing together their own realizations "well, we could take that rope and tie it to the tree ...".
Curious if they survey the drivers too, the people who are affected by this. I see no mention of this in the article. I'd think they should have a major say.
Drivers I've talked to seem supportive, at least so far. They're used to uncertainty with their income. Apparently Lyft and Uber have been squeezing driver pay very hard recently. I wouldn't be surprised if this is directly related to fed policy and VC funding dry up.
Do you know the amount she was consuming and the brand? Total Dosage, dilution and the per unit strength of the ACV brand can really matter, like anything else we might consume.
The paper does do a good job of describing this pretty important detail:
"Groups 1, 2 and 3 consumed 5, 10 and 15 mL, respectively, of ACV (containing 5% of acetic acid) diluted in 250 mL of water daily".
I can almost guarantee if that amount went up to 30-50ML and without any kind of dilution, effects can be pretty adverse.
I've been consuming it by diluting a tablespoon of ACV heavily with some warm water that I can barely taste it. It's really helped fix my acid reflux while all the prescription drugs from my PCP didn't seem to do anything.
The placebo was dilute lactic acid of similar pH. So one might imagine that the acidity didn’t cause the effect and try neutralizing the vinegar. Add, for example, calcium carbonate (cheap and safe) to convert most of the acetic acid to calcium acetate, leaving a neutral solution with extra calcium. Whatever magic other compounds in apple cider vinegar are beneficial seem likely to survive that process intact. The net result would be similar to drinking the vinegar and eating an antacid, minus the tooth damage.
I thought this article was about copyright. Turned out it was about them having growing pains. Though the jury is still out if a truly general purpose and truthful LLM can exist one day. And how far can this tech be pushed.
