Valve emailed in today to let us know about the new Steam Labs, a dedicated section on Steam for Valve to show off some experiments they're doing and for you to test and break them.
Behind the scenes at Steam, we create many experimental features with codenames like The Peabody Recommender and Organize Your Steam Library Using Morse Code. For the first time, we're giving these works-in-progress a home called Steam Labs, where you can interact with them, tell us whether you think they're worth pursuing further, and if so, share your thoughts on how they should evolve.
The first three experiments Valve are showing off to the public are up now, which are:
- Micro Trailers - A six second trailer for each game
- Interactive Recommender - A "machine learning" recommendation system to suggest games you might like
- Automatic Show - A daily auto-generated video to show off popular games
All interesting ideas and I do appreciate Valve being a lot more open in the past year or two. This new recommendation stuff is interesting, since the last time they tweaked their algorithm some indie developers were hit hard by it (I see complaints on Twitter daily), so this time they're doing it entirely separate to get it right and co-exist with existing features.
Valve did say this new recommendation system cannot suggest new games that don't have players yet, since there's no data on it. However, once it has a few days of data it can. This time around, the recommendation system is based on what you play and seem to enjoy, rather than what developers can do on Steam like tags, reviews and so on.
See more on Steam Labs. You can give them feedback on it here.
Do let us know what you think in the comments.
Also doesn't look like it can be filtered by OS? I use Steamplay, but it would be nice to be able to look at the Native Linux stuff first.
Ah yes, Dragons, that classical game genre.
The machine learning part is... not ideal. I have the opinion that, if my personal data is going to be used to generate recommendations I should be the one controlling that. Which means it should run locally, with no one else having my data, and I should be able to change the parameters as I wish - granularly remove any data I don't want to be used, filter what games can be recommended (by price, OS, DRM and etc), and so on.
But can I have a new Valve ARG?
Please.
QuoteThe first three experiments
So they CAN count to three...
The Quad video thing was my favorite.
I think a partial solution could be to look at the average playtime for the entire user-base for a game, and then see how my time compares to that of the average user. If I spent more time than average, then I probably found it compelling. Some games are intentionally short, others can be huge time sinks. By looking at a ratio compared to an average instead of absolute playtime we can ensure the former category isn't treated as unfairly as it currently seems to be.
Edit: Turns out they are already doing something like this :)
Last edited by Brisse on 12 July 2019 at 10:32 am UTC
Quoting: BrisseA problem with the recommendations presented by the ML feature "Interactive Recommender" is that some of my best gaming experiences have been from short and focused interactive experiences which didn't take as much time to go through as some of my top games by hours played. Seems these games are not treated fairly by this algorithm. The recommendations makes sense in comparison to my most played games, but most hours played does not always mean most compelling game, and some of those most played games I'm actually done with and I'm burned out on those genres.Hmmmm . . . but what if everyone, or even just most people, who ever bought a game thought it kind of sucked and didn't put much time into it? I see the problem you're trying to deal with but I'm not sure your solution does the trick either, because it would give a boost to low-quality games.
I think a partial solution could be to look at the average playtime for the entire user-base for a game, and then see how my time compares to that of the average user. If I spent more time than average, then I probably found it compelling. Some games are intentionally short, others can be huge time sinks. By looking at a ratio compared to an average instead of absolute playtime we can ensure the former category isn't treated as unfairly as it currently seems to be.
Not sure there's a simple rule that would handle the issue. But isn't it supposed to be a learny thing? So if so it shouldn't be working by a simple rule, it should be refining as it gets used.
Quoting: BrisseA problem with the recommendations presented by the ML feature "Interactive Recommender" is that some of my best gaming experiences have been from short and focused interactive experiences which didn't take as much time to go through as some of my top games by hours played. Seems these games are not treated fairly by this algorithm. The recommendations makes sense in comparison to my most played games, but most hours played does not always mean most compelling game, and some of those most played games I'm actually done with and I'm burned out on those genres.
I think a partial solution could be to look at the average playtime for the entire user-base for a game, and then see how my time compares to that of the average user. If I spent more time than average, then I probably found it compelling. Some games are intentionally short, others can be huge time sinks. By looking at a ratio compared to an average instead of absolute playtime we can ensure the former category isn't treated as unfairly as it currently seems to be.
Yeah, using time played as a metric for preference is deeply flawed. But I don't think looking at averages instead is a solution, for some of the same reasons: maybe you put more hours than average, but it doesn't mean the experience is better than that from another game where you put less hours than average.
Ultimately, the ideal metric is asking users "do you want more games like this or not".
Edit: it looks like they already normalize for time played like you suggested.
Last edited by eldaking on 11 July 2019 at 11:05 pm UTC
Quoting: eldakingQuoting: BrisseA problem with the recommendations presented by the ML feature "Interactive Recommender" is that some of my best gaming experiences have been from short and focused interactive experiences which didn't take as much time to go through as some of my top games by hours played. Seems these games are not treated fairly by this algorithm. The recommendations makes sense in comparison to my most played games, but most hours played does not always mean most compelling game, and some of those most played games I'm actually done with and I'm burned out on those genres.
I think a partial solution could be to look at the average playtime for the entire user-base for a game, and then see how my time compares to that of the average user. If I spent more time than average, then I probably found it compelling. Some games are intentionally short, others can be huge time sinks. By looking at a ratio compared to an average instead of absolute playtime we can ensure the former category isn't treated as unfairly as it currently seems to be.
Yeah, using time played as a metric for preference is deeply flawed. But I don't think looking at averages instead is a solution, for some of the same reasons: maybe you put more hours than average, but it doesn't mean the experience is better than that from another game where you put less hours than average.
Ultimately, the ideal metric is asking users "do you want more games like this or not".
Yes, letting the users interact with the inputs could help a lot. If there was a checkbox next to the top 50 list of games used as inputs then I would definitely uncheck some of my most played because I feel like they are no longer relevant to my current preferences. I've had my Steam account since august 2004, so it's almost 15 years old. Mostly played Counter Strike and HL back then. Recent years not so much. I guess some people change over time :)
the video thingy is a direct: nope! never!
and they recommender thingy would be oki-sh if it did replace the current recommendation lists with a single page solution
Also where is my Linux/steamplay indicator on any of the pages?
Here is the big but: But why do I feel SteamDB becomming the only sane and fast option to navigate the shop?
Age of Wonders 3 is free to keep on Steam currently (11-15th of July) get it it a great game
Last edited by Schattenspiegel on 11 July 2019 at 11:32 pm UTC
Quoting: Luke_NukemWell, the recommender got me down to a T. Added a few to the wishlist.Yep. I share the reservations others have expressed, yet it does seem to work surprisingly well. It isn't to know that I've already played GTAV and Just Cause 2 to death on the XBox 360, and 200 hours or so of The Witcher 3 from GoG. Mind you, it should know I'm running Linux and JC3 (its top pick by default) doesn't work under Proton. But it's certainly a game that'd be near the top of my own list if it worked. And if I fiddle with the age controls, restricting it to games released more recently, it comes up with Red Faction: Guerrila Remarstered, the original of which is definitely one of my top 5 360 games.
That's pretty impressive.
Last edited by Dunc on 12 July 2019 at 1:26 am UTC
Quoting: Duncthe original of which is definitely one of my top 5 360 games.
Wow, that's a lot of games. :D
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