This is something that I have been harping upon. Quite frankly, I am surprised that more aren't talking about it on LEO.
When it comes to Web 2.0, recommend engines are commonplace. We know the algorithms are working overtime on sites such as YouTube and X to provide people with content it things they want. The goal is to get people to engage more, hence remaining on the site.
We would be remiss, of course, to exclude Meta from this conversation. Zuckerberg might be the king of this, bordering on a psychop that it uses on people.
Either way, this is something we really do not see in Web 3.0. This is especially true on Hive where data enters and is buried.
For example, when was the last time you were able to easily pull up a thread from two years ago?
It is not easy. This is why the recommend engines are crucial.
Showing The Power of the Recommend Feature
Things are improving. Hopefully, we can see a massive step forward in some areas. That said, I do have some reason for optimism.
Here is an article I was replying to earlier.
Notice the date on it. This was from two months ago and was located at the bottom of an article. While the recommendations can be wonky, this one was actually somewhat related to the topic.
When I clicked through it, this was something that I had voted up but did not comment. Hence I was able to drop a comment on an older thread.
Is this a big deal?
On its own, not in the slightest. However, when we step back, it can have a major impact in the aggregate.
As more content gets in front of people, it can stimulate activity. If nothing else, this generated another page view.
The key is to think about this across the entire platform. What if everything that is entered through Leo has the potential to show up. That means we will be accessing what is in the database instead of just having to depend upon the most recent additions.
Of course, a lot of stuff submitted is time sensitive, such as the price of Bitcoin on a given day. Quite frankly, we do not care about the price of a coin 3 months ago.
There is, however, a lot of content that falls outside of this. We can see how the stickiness of music, movies, motivation, and success can apply. The same is true for entertainment.
Is a joke less funny if it is two years old? If it is time sensitive, then it is. Outside of that, it still applies.
Shorts: TikTok Style
Over the last few days, the stability of shorts have improved. It appears we are about to move onto the next phase of this development.
Here is a short that was put out by @khaleelkazi:
https://inleo.io/threads/view/khaleelkazi/re-zsxnixldhp
As we can see the shorts feed page should go live. There were some bugs, especially on mobile that still require attention. It seems the team is on it.
Here is what the page will look like.
https://inleo.io/threads/view/khaleelkazi/re-leothreads-2mrhhmvlv
This is obviously an video that was posted horizontally, when shorts prefer vertical. Hence we can see how it was adjusted to fit the layout. Just like TikTok or YouTube, the page is scrolled down, with a new short appearing.
Here is what it looks like in action.
https://inleo.io/threads/view/khaleelkazi/re-puoykvfqxu
Having a page like this is crucial. When it comes to getting content in front of others, it is a must. As stated, this is a natural part of Web 2.0 yet is absent for much of Web 3.0.
Leo, it appears, is changing this.
The next question is how the algorithm is trained to feed into this. For the moment, since there aren't a ton of videos, it probably doesn't matter. But over time, if this is a heavily utilized function, we are going to need the engine to sort through the content.
Here is where things can change completely.
When shorts were mentioned as being in testing a few weeks back, I mentioned that it was a 3 step process:
- shorts
- dedicated page
- recommend engine
According the one of the videos, we will have the second one implement soon (hopefully tomorrow). After that, we will have to find out about what the machine learning capabilities are.
Posted Using InLeo Alpha