Just saw a video today about how on steam roughly half of the best rated games are indie titles. Needless to say that the 2D graphics are not photorealistic.
Maybe, instead throwing money on graphics alone, focus on making fun games?
Video: https://youtu.be/qiNv3qv-YbU
Isn’t the added cable resistance small enough to not cause issues so soon? In case you just chain a few ( < 10 ) together.
All I want for Christmas is you, Satan.
You have a psychiatrist? Must have been coo coo before.
The artist needs to use the brain and translate a lot, and I mean an awful lot, of the information seen in the model (3d space) into 2d.
Close one eye or put an eyepatch on. I’d expect this makes 3D -> 2D transformations easier after a while.
Interesting idea. I am eager to see whether this can be further confirmed or not.
There are alarm clock apps which can help. You may configure how unforgiving the alarm becomes.
https://play.google.com/store/apps/details?id=com.kog.alarmclock
Changed my life.
Rebranding a Markov Chain stapled onto a particularly large graph
Could you elaborate how this applies to various areas of AI in your opinion?
Several models are non-markovian. Then there are also a lot of models and algorithms, where the description as or even comparison to Markov-chains would be incorrect and not suitable.
Doubt that for the next decade at least. Howver, we can already replace CEOs by AI.
A chinese company named NetDragon Websoft is already doing it.
https://www.independent.co.uk/tech/ai-ceo-artificial-intelligence-b2302091.html
If you want to play with fire, Mr. Amazon Guy, don’t be surprised to get burned. :]
If we’re speaking of transformer models like ChatGPT, BERT or whatever: They don’t have memory at all.
The closest thing that resembles memory is the accepted length of the input sequence combined with the attention mechanism. (If left unmodified though, this will lead to a quadratic increase in computation time the longer that sequence becomes.) And since the attention weights are a learned property, it is in practise probable that earlier tokens of the input sequence get basically ignored the further they lie “in the past”, as they usually do not contribute much to the current context.
“In the past”: Transformers technically “see” the whole input sequence at once. But they are equipped with positional encoding which incorporates spatial and/or temporal ordering into the input sequence (e.g., position of words in a sentence). That way they can model sequential relationships as those found in natural language (sentences), videos, movement trajectories and other kinds of contextually coherent sequences.
There is a neat Firefox addon which makes visits to yubbtub more tolerable by getting rid of unrelated suggestions:
RYS — Remove YouTube Suggestions
It has a lot of options to tailor it to your needs.
Meanwhile in the EU alone over 59 million tonnes of food are wasted each year.
What a gruesome world we live in.