This was my immediate reaction as well.

For those who like living a messy life, there’s always Visual Studio (the original beast, not VSCode)

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

VSCode supports it also for other shells. This repo is not about vscode, it’s about actual shells. You are the one incorrect in this case

When someone brings points in the discussion, you react like a fan boy student that just bought the new gaming laptop.

Could you please reply about the discussion or go back to school? I am too old for your “no, you shit, you stoopid”

I wonder myself why I keep answering to your comments and that’s why this is my last comment

Unfortunately… That is why I commented above…

Powershell is a shell that pretends to be an OO language and that fails dramatically at both.

It was a design mistake. Much better having a real separation, a real shell and a real OO language. As even Microsoft has recently understood. As you can see also in this case, where Powershell is the last entry

What is a real advantage compared to plain autocomplete? Was it trained to know command flags?

It is anyway nice to see that even in Microsoft the abomination of Powershell is the lowest in the list of shells. It is probably time for them to drop it completely

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

ML/AI is a huge field. If you don’t like 1 side of it, there are millions others.

ML/AI. Everything else has been eaten by agile/product owners/MBAs/micromanagement. Luckily those people still don’t understand AI… And AI is still stochastic, pi planning and burnout charts don’t work.

If agile bites your ass… Run away, you are too young for wasting your life

All scientific computing is built on top of fortran. Even cutting edge AI runs on top of high performance libraries written in fortran and c. Simply there is less need for fortran developers because high performance subroutines are wrapped to be called by higher level languages, such as python

First time I see “cool” and “c#” on the same sentence. I’ve always thought stereotype of c# is that it is the language for corporate, extremely uncool projects.

Just a comment. Cobol nowadays is heavily outsourced. There are jobs but not so lucrative as in the past. Fortran is still strong in scientific computing, but nowadays it is wrapped in python. All people I know who were strong in fortran (me included) are nowadays mostly working with python or scala, most of us on ML/AI related stuff.

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

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

Have you thought asking support from a counselor? It might help to cope

You are most probably wrong. How old are you?

Time really cures such feelings. In 20 years you’ll watch back to these events with a very different perspective

What I am saying is that it is very common. All manual cars I have had with the exception of one have the R on the left

It is pretty common to have R on the left, to avoid accidental shifts while car is in motion