Most OLEDs today ship with logo detection and will dampen the brightness on static elements automatically.
While it isn’t a silver bullet, it does help reduce burn in since it is strongly linked to heat, and therefore to the pixel brightness. New blue PHOLEDs are expected to also cut burn in risk. Remember that LCDs also used to have burn in issues, as did CRTs.
I’ve been using Nvidia under Linux for the last 3 years and it has been massive pita.
Getting CUDA to work consistently is a feat, and one that must be repeated for most driver updates.
Wayland support is still shoddy.
Hardware acceleration on the web (at least with Firefox) is very inconsistent.
It is very much a second-class experience compared to Windows, and it shouldn’t be.
Linux and Nvidia really need to sort out their shit so I can fully dump windows.
Luckily the AI hype is good for something in this regard, since running gpus on Linux servers is suddenly much more important.
It looks much better than elden ring in that all the models are much higher quality. Elden Ring was designed around relatively modest assets, and does wonders with what it has, but there is no comparison, DD2 wins hands-down.
As for art direction, that is subjective. Plenty of reasons to prefer looking at ER.
The Witcher 3 is almost a decade old at this point
Humans are intelligent animals, but humans are not only intelligent animals. We do not make decisions and choose which beliefs to hold based solely on sober analysis of facts.
That doesn’t change the general point that a model given the vast corpus of human knowledge will prefer the most oft-repeated bits to the true bits, whereas we humans have muddled our way through to some modicum of understanding of the world around us by not doing that.
But the most current information does not mean it is the most correct information.
I could publish 100 papers on Arxiv claiming the Earth is, in fact, a cube - but that doesn’t make it true even though it is more recent than the sphere claims.
Some mechanism must decide what is true and send that information to train the model - that act of deciding is where the actual intelligence in this process lives. Today that decision is made by humans, they curate the datasets used to train the model.
There’s no intelligence in these current models.
A token is not a concept. A token is a word or word fragment that occured often in free text and was assigned a number. Common words, prefixes, and suffixes are the vast majority of tokens, and the rest are uncommon pairs of letters.
The algorithm to generate tokens is essentially compression, there is no semantic meaning embedded in them.
Copilot is GPT under the hood, it just starts with a search step that finds (hopefully) relevant content and then passes that to GPT for summarization.
The Dark Souls 2 DLCs are some of the best content in all of Souls. While the original game has some level design issues, the DLCs are sublime.
The OG Crysis wanted hardware that still doesn’t exist. They built the game and engine under the assumption that clock speeds would keep increasing, and instead we moved to high core counts.
Even today, at 4K and max settings, the original (2007) release can drop below 100 fps on the best possible hardware.
Every billion parameters needs about 2 GB of VRAM - if using bfloat16 representation. 16 bits per parameter, 8 bits per byte -> 2 bytes per parameter.
1 billion parameters ~ 2 Billion bytes ~ 2 GB.
From the name, this model has 72 Billion parameters, so ~144 GB of VRAM
Role of thumb is an employee costs roughly twice their base salary, as the employee still needs to cover insurance, taxes, sick time, and other benefits.
That leaves an average salary of 190K for the 50 employees. That isn’t much for tech.
Explaining what happens in a neural net is trivial. All they do is approximate (generally) nonlinear functions with a long series of multiplications and some rectification operations.
That isn’t the hard part, you can track all of the math at each step.
The hard part is stating a simple explanation for the semantic meaning of each operation.
When a human solves a problem, we like to think that it occurs in discrete steps with simple goals: “First I will draw a diagram and put in the known information, then I will write the governing equations, then simplify them for the physics of the problem”, and so on.
Neural nets don’t appear to solve problems that way, each atomic operation does not have that semantic meaning. That is the root of all the reporting about how they are such ‘black boxes’ and researchers ‘don’t understand’ how they work.
They aren’t the good guys. A lot (too much if you ask the community) of the fiction is told from the perspective of the imperium/space Marines, but that doesn’t make them the good guys.
They go around saying things like “The rewards of tolerance are treachery and betrayal.” They clearly are not meant to be the good guys, even in their own stories.
The problem is media literacy is so poor that far too many people look at quotes like that and think “that’s a good point”. Even the creators have put out press releases about how all the fascists are missing the point.
Haskell isn’t really that hard to learn
A monad is a monoid in the category of endofunctors
You can fly in space towards the planets you can see. When you get there, you won’t be able to land and will be able to fly straight through the planet itself.
Planets outside of the fast travel menu aren’t really planets
In many cases, getting something out quickly is more valuable than having it be clean.
Part of being a senior is knowing when fast is more important than perfect. Not saying your senior did everything right, just that a single example of someone’s code isn’t enough to judge the value of a person to an organization.
A cleric can be a competent martial class for the beginning of the game. Falls behind true martials after those get extra attacks, but by then clerics have 3rd level spells.
In the language of classical probability theory: the models learn the probability distribution of words in language from their training data, and then approximate this distribution using their parameters and network structure.
When given a prompt, they then calculate the conditional probabilities of the next word, given the words they have already seen, and sample from that space.
It is a rather simple idea, all of the complexity comes from trying to give the high-dimensional vector operations (that it is doing to calculate conditional probabilities) a human meaning.
I’m not sure I’d trust modern CA to do Med3 justice. The new style of Total War is just a different beast from the sublime RTW/Med2 era.
Lots of little things changed, and it just ‘hits different’. Probably the biggest difference is just that every single fight after the first 20 turns will be a 20 stack vs a 20 stack, and every single battle is life or death for that army. It makes the campaign much faster paced - declare war, wipe stack, capture cities for 3 turns until the AI magics up another 20 stack.
In the original Med2, since there wasn’t automatic replenishment, there were often battles between smaller stacks, even in late game, as they were sent from the backline to reinforce the large armies on the front. Led to some of my greatest memories trying to keep some random crossbowmen and cavalry alive against some ambushing enemy infantry they wandered into. The need for manual reinforcement led to natural pauses in wars and gave the losing side a chance to regroup without relying on the insane AI bonuses of the modern TW games - and I do mean insane; they’ll have multiple full stacks supplied from a single settlement.