That formulation seems deliberately ambiguous.
That formulation seems deliberately ambiguous.
So what’s the frustration here? That it didn’t have 256Gb? I can’t see it in the photo.
In iOS you can use Yattee and link to an alternative Frontend. Works well for me.
I have the Ascaso Uno PID for it’s through-flow heater. There is virtually no heat up time needed so you can get an espresso when you want. I was aiming for a machine that allows me to be lazy and short-sighted and the Uno delivers that for me. I use it at least once a day but of course you have to decide if the investment into machine and grinder of around 1,4-2k$ is worth it for you. It is for me but I treat it as a hobby. You definitely need some time to tune in the grind setting, temperature, pressure and bean. But once you have your settings you usually only need to change the grind setting for each bean. I would go with an automatic burr grinder for consistency and ease of use since you sometimes have to redo a shot.
True to a degree but you can do similar things with thinkpads and keep them longer. The company can always extend lifetime by enabling repairability and upgradeability. But this goes against their profit since they then can’t sell a new product every two years. The consumer shouldn’t have to find ways around planned obsolescence and feel superior if they manage to solve this puzzle.
I believe this to be true for nearly all products. It has to be super simple to test, because you need to assess if it fits your needs. The mental model for a priori assessment is not strong enough usually.
How is jetbrains AI integration into their IDEs? I assume not perfect since you have more than one system.
LLMs don’t have live longterm memory learning. They have frozen weights that can be finetuned manually. Everything else is input and feedback tokens. Those work on frozen weights, so there is no longterm learning. This is short term memory only.
The term embodiment is kinda loose. My use is the version of AI learning about the world with a body and its capabilities and social implications. What you are saying is outright not possible. We don’t have stable lifelong learning yet. We don’t even have stable humanoid walking, even if Boston dynamics looks advanced. Maybe in the next 20 years but my point stands. Humans are very good at detecting miniscule differences in others and robots won’t get the benefit of „growing up“ in society as one of us. This means that advanced AI won’t be able to connect on the same level, since it doesn’t share the same experiences. Even therapists don’t match every patient. People usually search for a fitting therapist. An AI will be worse.
There is the theory that most therapy methods work by building a healthy relationship with the therapist and using that for growth since it’s more reliable than the ones that caused the issues in the first place. As others have said, I don’t believe that a machine has this capability simply by being too different. It’s an embodiment problem.
No shit.
This is kind of by design since these books are all criticisms of the status quo.
just saw after you replied :) but unfortunately that is only available on desktop.
I may need to add, that I use Obsidian across Win/Linux/iOS/macOS via remotely save. the sync solution needs to be able to work on all platforms. Logseq doesn’t have mobile plugins yet and iOS makes filesystem access a pain.
Thanks for the heads-up. I see that it has an auto-commit feature, that may be interesting, if it also works on iOS.
Would love to but I’m not going to pay a subscription for sync (one time would be ok), or have my data on a random aws instance. And last time I checked there is no plugin for your own self defined sync storage like Nextcloud. Once there is, I’m having a go.
Incremental approach when the task seems too big to grasp. I agree!
Not a loss. You can make an AI startup with the goal of being profitable yourself.
They look exactly golfball-sized, wtf. This is the default measurement unit for hail!