> There is no separation of code and data on the wire - everything is a stream of bytes. There isn't one in electronics either - everything is signals going down the wires.
Would two wires actually solve anything or do you run into the problem again when you converge the two wires into one to apply code to the data?
As long as LLMs have no true memory, this is expected. Think about the movie Memento. That is the experience for an LLM.
What could any human do with a context window of 10 minutes and no other memory? You could write yourself notes… but you might not see them because soon you won’t know they are there. So maybe tattoo them on your body…
You could likely do a lot of things. Just follow a recipe and cook. Drive to work. But could you drive to the hardware store and get some stuff you need to build that ikea furniture? Might be too much context.
Black holes have the same mass and information as the stars that formed them.
Unless the theory also breaks mass and information conservation, the star that gave birth to our black hole must have been as massive as our entire universe.
I doubt we have any theory how a star that size can have formed.
1. This theory requires a parent universe that can't have been formed inside a black hole. This means there must a be second "universe creation" mechanism that we can / may never know about from our child universe. For me, this doesn't really answer the true question: "How did our universe begin?" Yeah, it may the "unknown field with strange properties" but instead we get an unknown parent universe with strange properties.
2. The black hole in the parent universe must be much much bigger than anything we see in ours since it has to contain all the matter that we see. How is a black hole supposed to form that is 750 billion times bigger than the largest black hole we know about?
I agree with many posters in here, that the cause will likely be bad data one way or another. Maybe we need to take a step back and only use data, that are almost 100% accurate.
Like the time of death after the data was collected.
If a model could with a high accuracy predict, that a patient will die within X days (without proper treatment), it will be already very valuable.
Second, as Sora has shown, going multi model can have amazing benefits.
Get a breath analysis of the patient, get a video, get a sound recording, get an MRI, get a CT, get a full blood sample and then let the model do its pattern finding magic.
This is not something that is only a thing within google. Similar things are happening in a lot of companies and even public institutions like schools, universities and public media networks like the BBC.
It's Doctor who traveling to medieval Britain and showing a level of diversity that we see today. Or black Cleopatra. Or black Vikings. The list goes on and on.
In this case, they were overdoing it and so they will turn it down but I doubt they will "turn it off". Of course, the people who are doing it, will never acknowledge it and gaslight anybody who points it out as weird right wing conspiracy nut, but in cases like this, you can see it happening in a very obvious way.
That is not my point. Even if we had a model that could portray reality as objective as possible, a lot of people wouldn't like that and be actually offended by it.
This has also been going on a lot in the "representation" discourse.
A bohemian village 500 years ago would have been 100% white in almost all circumstances. Surgents would be male. Telephone scammers Indian and so on.
But in many ways, simply showing reality is not only not wanted but even offensive. What has to be shown is an idealized version of reality that we want to achieve and that is "more diversity". And what is maximum diversity? Zero white people.
> If you trained a model purely on past history, it would see a 1:1 correlation between "US President" and "man" and decide that women cannot be President.
Why would you think that? You and me also know the history but also realize that a woman can be president.
If you look at attempts to actively rewrite history, they have to because a hypothetical model trained only on facts would produce results that they won't like