Your assumption is that all meat tastes the same. Try eating a free range Argentinian steak and a cheap Tesco value steak… They are not the same.

I cannot judge grown meat, but meat taste greatly varies

Teeth are absolutely not cosmetic. Infection of a tooth can lead to dangerous consequences up to sepsis. Your parents didn’t have teeth because they had them removed by a dentist to avoid abscesses.

Guys, please don’t underestimate dental health

They are often on purpose, as political decision. So that it is easier to push for privatization

I am a complete amateur, and I do better jobs

Because he was ceo of a company in a critical position to define the future of economy. Currently the tech field is the biggest and most influential of all economic fields. And by tech here we talk about digital world. There’s absolutely no comparable sector at the moment for importance, not even pharma.

It literally defines the modern economy. In the field, openai is an incredibly important company for future relative success and power of big tech companies.

This is why it is so important for world economy

Millennials as well. I get bored with modern games. Grinding all day for a pink weapon skin. Tf, I don’t care what color are my skins. Give me a good old challenge

How is it useful? Dessert vs food?

“At the end of the lunch nowadays everyone want to have a dessert, but this is wrong because they should have food”…

The sentence AI vs algorithms sounds pretty much like this

AI is a broad family of statistical and simulation algorithms.

They don’t replace algorithms, they are algorithms very powerful for some cases. For other cases they are less powerful, or overkill and they shouldn’t be used. But there is no dichotomy, as one (AI) is part of the other (algorithms)

It’s not an average machine though. It’s a non-linear predictive system. Averages suck in non-linear predictions

They missed the recording where he said to the female journalist in his team: “to work here you have to f*ck”

Powershell one liners are uglier than the worst winner of Obfuscated Perl Contest. Super cringe…

No, its taste isn’t something that Italians would appreciate. It tastes like a cheap mix of a cheap German frankfurter and cheap calabrese 'nduja. It’s almost impossible to find it in Italy.

I have never seen it in my life in Italy

Thanks, so I don’t have to be that “actually” guy mentioning that 99% of Italians have never seen pepperonis in their life. You saved me

In the easiest example of a neuron in a artificial neural network, you take an image, you multiply every pixel by some weight, and you apply a very simple non linear transformation at the end. Any transformation is fine, but usually they are pretty trivial. Then you mix and match these neurons to create a neural network. The more complex the task, the more additional operations are added.

In our brain, a neuron binds some neurotransmitters that trigger a electrical signal, this electrical signal is modulated and finally triggers the release of a certain quantity of certain neurotransmitters on the other extreme of the neuron. Detailed, quantitative mechanisms are still not known. These neurons are put together in an extremely complex neural network, details of which are still unknown.

Artificial neural network started as an extremely coarse simulation of real neural networks. Just toy models to explain the concept. Since then, they diverged, evolving in a direction completely unrelated to real neural network, becoming their own thing.

No, what you describe is a basic decision tree. Let’s say the simplest possible ML algorithm, but it is not used as is in practice anywhere. Usually you find “forests” of more complex trees, and they cannot be used for generation, but are very powerful for labeling or regression (eli5 predict some number).

Generative models are based on multiple transformations of images or sentences in extremely complex, nested chains of vector functions, that can extract relevant information (such as concepts, conceptual similarities, and so on).

In practice (eli5), input is transformed in a vector and passed to a complex chain of vector multiplications and simple mathematical transformations until you get an output that in the vast majority of cases is original, i.e. not present in the training data. Non original outputs are possible in case of few “issues” in the training dataset or training process (unless explicitly asked).

In our brain there are no if/else, but electrical signals modulated and transformed, which is conceptually more similar to the generative models than to a decision tree.

In practice however our brain works very differently than generative models

There is not a single if/else in a neural network. You are confusing it with decision trees that are used for classification

NTA, you should leave your husband

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“Life is long, I’ll have plenty of time to do it in the future”. Spoiler: life is short

Mine was a comment to say that llms are not just fancy auto complete. Although technically an evolution, it is a bit like saying humans are fancy worms because evolved from worms