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Trains-Planes-2023 t1_j55ce1v wrote

Progress towards _a_ singularity, not The Singularity. But very interesting nonetheless. Approaching near-perfect, real time translations to multiple languages.

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DadSnare t1_j57egqm wrote

Exactly. Seems like there can be a singularity in one very specific thing without a paradigm shift of everything else…i think lol

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Trains-Planes-2023 t1_j5alclu wrote

I have some (very little) experience with the under-the-hood end of machine translation, and people should not mistake this for the machine actually "understanding" language. It's literally looking at patterns of 1's and 0's and doing pattern matching based on context relative to other patterns of 1's and 0's. The machine doesn't "know" anything about language, or even what it is. It is a very fancy set of gears, that's all.

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DadSnare t1_j5bthjr wrote

So are we! Just different, with biological architecture!

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Code-Useful t1_j6j7ja3 wrote

I completely agree. I have limited experience with ML which is a fascinating topic but I believe all experts agree AGI is still far off.

linear regression=statistical analysis on the fly. Nothing special just number crunching to make predictions on future inputs.

Supervised learning=spoon-fed human curated information to make basic inferences, but over fitting is an issue.

Unsupervised learning=better than a human for spotting unseen relations in inputs, but not always useful or correct in correlation, overfitting is a huge problem just like in humans.

Reinforcement learning=reward learning but also requires tons of training data, may not provide anything useful.

There are some great uses for ML in it's current state, and ML does amazing amounts of number crunching and statistical analysis, but humans still need to mostly supervise all the data and inferences, and under the hood the ML hasn't really learned anything quite how a human brain does over many years, but chatbots are able to fake it very well. AGI seems way off still honestly, but again I am not deep in the industry so idk.

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