I've been using the XReal One Pros for coding work for a few months now, and have had a great experience.
For me, the ergonomic benefits are the selling point, not the display quality. Not having to sit hunched over a laptop screen for several hours means I can work almost anywhere. Sometimes I'll use it in a cafe. Other times I just lie down in bed. I also make use of speech to text, so I just need to be able to press a hotkey and reach the track pad.
On the topic of display quality, it's important to use Better display to upscale the output to the XReals to high DPI - that gives noticeably better quality when it's downscaled to the (lower) native resolution of the XReals.
It's probably not got the entertainment factor of Guitar Hero, but I'm working on an Android app that connects via Bluetooth/USB MIDI and teaches you sight reading. It starts with individual notes, then progresses to intervals, triads and more complex chords. All of these are exercise based, so you can pick and choose areas to focus on.
The notes are all rendered according to conventional music notation standards as per Elaine Gould's book "Behind Bars". Writing this code was not straightforward, but worth the effort as it's very flexible.
Progress is tracked intelligently, i.e. accuracy and response times are recorded per note, and exercises can be directed towards improving weak spots. This was all borne out of a frustration I had with how long it takes, and how much material is needed to make progress with sight reading skills.
I'm hoping to release it soon (next few months - it's mostly finished), but slightly concerned it's too niche. I guess it will mostly appeal to serious but beginner/intermediate pianists who want to put in the hard yards to develop sight reading abilities to an advanced level.
There's a library Valve made for spatial audio for games (inc. VR). I've played around with it a bit, it's incredible. I'm surprised more games haven't adopted it.
Keep in mind that the present value depends somewhat on the discounted future earnings, which by definition extends to the end of time. That being said, the associated time discounting heavily reduces the impact of earnings envisaged say 100 years from now (a 5% discount rate would mean ~13k USD in 100 years is worth about 100 USD now, and that's probably generous given historic market returns).
So, the US doing extremely well 100 years from now vs. the US doing very badly 100 years from now could have a non-trivial impact on the perceived value of US assets. I suspect that the large uncertainty about what the world will look like in 100 years means there is just some sort of seldom changing value baked into assets to account for this, but it nonetheless exists, and could change if there was some huge geopolitical shift.
And before you mention anyone on earth would be dead in 150 years, yes that's true, however you can always sell it to someone later on who will be alive in 150 years (or sell it to someone who can later sell it to someone etc. etc.).
To provide some contemporary evidence to support your hypothesis that there were "luxury rocks" and that humans would be interested in such things, here is a gallery of various skins for a handheld rock in the videogame Rust. One of them costs $68
Just FYI, there is a fairly widespread issue with Nvidia drivers causing a slowdown (no matter how fast your PC). The game was basically unplayable for me until I found the solution.
The fix is to run 'd3d_windowscursor' in the game console.
You should look at Unity's high definition render pipeline. It uses physically based lighting so you can just e.g. look up the brightness of a particular light, enter it in, then it will render as you would expect.
And yes, you're right about it being enabling. Anecdotally, I've heard that people coming from e.g. photography background find HDRP insanely easy to get good results and pick up quickly.
This is wrong. Unity has frustum culling enabled by default. You are correct that it only operates at whole model level though.
Occlusion culling in Unity is fairly straightforward. Simply requires a bake. It also supports 'occlusion areas' where you can give it a hint to do a higher resolution occlusion bake e.g. if you think the player will likely be in that area.
Edit: originally misread parent as stating Unity didn't frustum cull by default. Parent comment is correct.
I'm not really convinced nor reassured by their supposed tests to prove the physics will work. The test involving the iPhone? That's like saying "well, a marshmallow can withstand 1g of forces without being crushed therefore I can build a 3 story apartment building out of them".
I disagree. I regularly downvote comments whose purpose is largely for humour. Not because they aren't funny/witty/clever, but because this is Hacker News, not Reddit. Let's keep it that way.
This is totally incorrect. Individual options contracts are indeed written against 100x of the underlying asset but this has absolutely nothing to do with the relationship between the price (premium) paid per contract and that of the underlying share. To given an example, you could find a put option whose premium is actually equal to the current market value of the underlying (i.e. a merely 1 to 1 relationship) or one that's so far out of the money that it's a 1 to 1000 relationship. Without knowing more details about the precise options SoftBank bought, we cannot infer how much market cap in underlying shares the $4bil corresponds to.
I agree, and the proposed solution which is to limit point gains/losses to one point per game feels like throwing the baby out with the bathwater. Specifically, convergence takes a long time, the result of which is that a very good player on e.g. a new account (smurf) will end up being the cause of a lot of unbalanced games for an awful long time.
Having played a lot of ranked LoL, I saw a few recurring but irrational gripes players had with the Elo based system:
- "I get matched with bad teammates and they drag me down". On average your teammates are the same Elo as you. All players get their fair share of games where they are/aren't the underdog side. On average, it averages out. Deal with it.
- "I've been stuck at the same Elo for ages but I should be higher". Nope, Elo only cares if you win or lose. It doesn't care about kill/death ratio, creep score or how many ganks you pull off. Focus on winning more. Incidentally, focusing on winning instead of secondary metrics like kills/CS was one of the biggest mindset differences between high/low Elo players.
"I should be higher Elo but I play support roles so can't climb". It may be true that you climb slower but here's the rub - think of your matchups as you being compared to the enemy team's support player. The other four roles on each team are actually a constant factor (by symmetry arguments you could not consistently find that your four teammates are any better/worse than the enemy support player's teammates). As a result, the only remaining factor in the statistical equation is you weighed up against the enemy support player. If you can provide even a slight statistical advantage towards winning vs them then you will climb the Elo ladder.
The Sharpe ratio should be mentioned here. It allows an apple to apples comparison between the performance of different assets in terms of expected return against variance (risk). In an efficiently priced market, assets will be priced to lie on a straight line of unit return vs unit risk. The line itself passes through the y-axis (zero risk) at a point called the 'risk free rate'. This is a hypothetical point but a close proxy in the real world is e.g. US treasury bills. In the game, I assume the bank always pays interest on deposits so it _is_ the risk free rate (0.05%).
Plotting the different strategies, then fitting a straight line (passing through the risk free point) would allow us to say "strategies falling above the line have market beating Sharpe ratios and strategies falling below are underperforming".
I am going to suggest you watch a few episodes of 'Only Fools and Horses'. It's an 80s sitcom set in Peckham, South London. The show is practically considered a national treasure in the UK and most people who grew up in the UK are very familiar with it.
The reason I suggest it is that it showcases a very particular dialect of British English that many people struggle with (even native English speakers) if they aren't familiar with it. The show was so popular in fact that many modern colloquial British English phrases/words can trace their appearance to this show, not because the show invented them, but because the show exposed so many people to this dialect.
Some examples of words/phrases popularised by OFAH: dipstick, wally, cushty, lovely jubbly.
I propose a less effective, but easier to implement, way to optimise who to test. It relies upon a simple result from network/graph theory that I will outline here.
Assume, if you will, that typical social networks contain a small number of people who are highly connected (hubs) and a large number of people who are much less connected (spokes). The hubs could be e.g. your GP/physician, your teacher, or even just your popular friend. It would not be surprising if these people have a much high transmission rate for a virus than people who have a much smaller social circle - all other things being equal, and also crucially, they often connect mutliple sub-networks (GP is a good example here).
We would of course like to ensure that we test (perhaps regularly) the people who are at the center of these networks - the hubs. How do we find out who these people are? It turns out that you can do this probabilistically. First, I pick someone at random from the population. I then instruct them to pick a contact/friend at random. The person they pick is statistically much more likely to be a 'hub' than a 'spoke', even though we have no explicit knowledge of the network and carried out this process randomly. A good way to visualise this is to imagine a toy network of say one person in the middle, connected to everyone else, and 10 other people, all connected to the person in the middle but nobody else. You can see that in 10/11 cases, a 'spoke' is selected who then goes on to select the 'hub' (what we want) whereas in only 1/11 cases the hub is initially chosen, who then chooses one of the other 10 contacts at random.
A practical implementation of this could be to choose N people at random and send them a letter or text message instructing them to pick e.g. the (modulo) 5th person from their contacts list whose name begins with R. They would then contact this person and inform them that they should present themselves at a doctor and be tested should they develop any symptoms. There are obvious optimisations to be made here in terms of name distributions and other subtleties of course, and certainly providing a list of fallback randomiser instructions, if they can't find someone fitting that criteria.
Bottom line is, even if many people don't comply, you can increase the probability that you end up prioritising testing of people who are very connected, and thus likely to spread disease, which can be invaluable when your testing capacity is constrained.
For me, the ergonomic benefits are the selling point, not the display quality. Not having to sit hunched over a laptop screen for several hours means I can work almost anywhere. Sometimes I'll use it in a cafe. Other times I just lie down in bed. I also make use of speech to text, so I just need to be able to press a hotkey and reach the track pad.
On the topic of display quality, it's important to use Better display to upscale the output to the XReals to high DPI - that gives noticeably better quality when it's downscaled to the (lower) native resolution of the XReals.