Just trying to get him to see that the IF and TSS would be the same, so what Nate said on the podcast was true.
I thought
was a little misleading 
What me? misleading not really, clearly stated and clarified original post, because like I said you dont add the recovery valleys to the end of the session, in reality you add some Z2 or even Z3 which then gives you a higher TSS
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I’ve been thinking (uh oh). I would be really hesitant to adopt Adaptive Training until other rides/workouts can be accounted for. I really don’t think it should be publicly released until this is available.
I’ll get this out the way - I’m training for an Ironman. However, I’m not necessarily asking for the runs and swims to be supported off the bat. It’s a cycling platform that offers very basic multisport stuff as an aside. I know that, I can’t wait until it’s integrated more but until then I’ll keep this cycling focused.
Since it’s announcement, I’ve been more mindful of my training. My worry is the AT system is being beta tested with TR staff and, as they said, specific TR users “you probably know who you are”. Surely this is an oversight. Maybe this is still very early beta but the way I see it, to prove your concept you’re going to need a much more diverse beta group other than just hardcore TR users.
I point this out as I, like a lot of people, have been using TR for my structure but using zwift and going outside for races and greater interaction. Just last night I did half of my plan builder prescribed workout intervals before I jumped on to Zwift with my TTT team for a course recon and finished my workout there. Yes, not as structured but it was a similar effort. As I understand it I’ll need to justify why I stopped that workout early with the new platform and it will in someway effect future workouts until the zwift ride that I did straight after is accounted for. The same goes for the long rides outside. Am I hell doing 3+ hours on a turbo, just not going to happen.
As far as I understood the timeline, it’s closed Beta (full AT system), mostly for basic bug testing and other obvious issues. Then, once they grow more confidant about stability they keep adding more and more users to the beta (which should also be more diverse).
But for the public release, as I understood it anyway, it won’t be switched to full on AT overnight at some point. Instead they will release smaller subsets of features slowly one by one. Presumably the full system will be active behind the curtains, but I guess the effect on the user will be limited at first.
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That was my take as well.
If everything’s going well, but not to well 
the ‘standard’ plan won’t be modified by AT until something is detected that indicates a requirement for change. Which is probably less likely until more features are in place.
There are many here who only train indoors and on TR. 
They are sitting on over 100 million rides. I would argue that’s as diverse as it gets.
If you mark the right category it shouldn’t be an issue.
As a fellow triathlete I would argue you should do that. You won’t get more bang for your time which leaves you with more time for the swim and run.
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This might be true but what percentage is useful for AT and more importantly how do you identify and create a subset of data that can realistically be used for AT? It must be pretty difficult or at least time consuming.
It also worth noting that pretty much none of this data has subjective feedback, that will start to be collected going forward. I would suggest this is true for a lot of ML features particularly the more advanced ones and it is going to be a fair while before there is a decent data set for these.
The majority for it will be useful and likely also used. In terms of setting it up you start with a small sample and go from there.
Subjective feedback is helpful though not required. They could simply pick a subset of athletes and track their career. The context provided will help to detect patterns. Like when athletes fail workouts and how they fail (as discussed in the podcast).
We did the same thing with our branch network. AI and ML ultimately enabled us to sharpen our product profile which lead to a significant increase in revenue and customer satisfaction. We did it without subjective feedback.
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True. You’ve go to have decent amount of data to get those smaller sets.
My point is there is a lot of potential ML features they have no data for at all, they are going to have to find ways to collect it. I think it has been mentioned in a round about way during the youtube video and in various threads.
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100 Mio. should be enough to derive those subsets.
In terms of data sources you are right. Though the power and heart rate data along with workout compliance is already a lot. Sleep, HRV, RHR, steps, stress, fatigue, weather, weight, yada yada yada would also be super useful. I am sure they will find a way to consider that when moving forward. The subjective feedback could be a good proxy in the meantime.
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I think you’ve slightly missed my point here. I’m saying lots of people use the platform in different ways. If the closed beta group consists of just one type of TR user, that being the indoor and TR only user (I think it’s actually more diverse than this) then you’re only getting a narrow viewpoint as feedback. Hence the post ride survey in the announcement doesn’t have a “finished ride elsewhere” option (I know that’s a bit ridiculous but I think the points still stands).
I agree with @Pasque, however, the closed beta is probably for a more technical stand point bugs etc. and a more open diverse beta group will be included at some stage. And a staggered roll out of features makes sense. If you ride indoors on TR only then the new features might be useful to you sooner, but as I do not fit into that category I would need to wait until they are able to analyse all rides to feed in to the new system, otherwise I would be concerned that the AT system wouldn’t be learning correctly as my training data would have blind spots that it’s not taking into account.
To be fair to them they have said they are going to address this I’m just stating that I don’t think it’ll worthwhile for me and many others until they do.
I just don’t enjoy 3+ hours on a turbo so I’m not going to do it. I’d rather put a jacket on and ride for 4+ hours. Everyone’s different and that’s a good thing and exactly what AT is trying to address.
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TSS and IF are simple mathematical formulas. It might be useful to take a step back and realize how much experience you are using to derive:
Yes to someone who is familiar with TSS and IF. But the fact remains that these measures describe neither the difficulty nor the training load of a ride, and they do nothing to describe the targeted energy system.
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I disagree with this but we are all just speculating until we get our hands on the goods 
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That could be the case.
I get that but what influence would it have on AI and ML. As long as you don’t categorize the early end due to failure it shouldn’t affect the magic behind the scenes. They sure will offer a time-crunched or other option to select.
Yup.
I get that but they could still release it anyway. You could simply ignore the AT bit while others could already benefit from it. Delaying the release until it delivers value for everybody seems like a waste to me.
That’s all good. Though it would still be beneficial. 
We are in agreement I think.
My comments originated from a comment about IF being “worthless”
(Not yours)
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Haha, yeah I think we’re pretty much on the same page now. Enough to close the debate anyway 
. Apologies, I see how my statement reads, I’m just saying you can’t force the new platform on people if all rides aren’t accounted for. By all mean fire on and get it out before that though as long as the legacy option is still available, I think it will be useful for the TR only athletes.
You can keep your super long turbo rides though!
Here is one question I have for the smart people here in regards to the inclusion of outdoor rides: Do you guys think weather conditions could “muddy the waters”, so to speak, for the ML? Because in the datasets there is essentially only heartrate and/or power (And I guess maybe temperature, depending on the head unit). Presumably performance is quite impacted by weather conditions (it for sure feels that way), so I wonder how much that impacts the ability to implement outdoor rides into the system?
Guess we always were.
Meh, was about to invite you for a group workout. Bandeira preferably.
Needs a long answer, but the more data variability the harder it may be to fit a model and produce useful outputs (training guidance). If a riders data is all over the map, it will be hard to tell what is going on. You are perhaps describing a rare ride? It would perhaps be easiest to exclude that data and not use outliers or rare events to guide training plan modifications.
By analogy, say I have a race and have an amazing day. Produce a 20 min power PR. Am very happy with that performance, but I don’t immediately take 95% of that number and call it my new FTP. It’s an outlier ride not representative of training conditions.
Perhaps a different question is how much variability can the current model adapt to? If it works great for a homogeneous indoor training setting (meaning well controlled environment) that is a great step. Huge accomplishment. The next questions are how much and what type of data and environment variability can the model tolerate without breaking? Or rather, how much variability can it take and still be valid and useful?
TR should be able to produce guidance for what good data input looks like. Riders wanting to use the early iterations should probably stick to those guidelines. TR can automate some aspects of data cleaning. Part of asking the rider questions post-ride is to help with that data cleaning or data weighting process.
As the algorithm or model evolves, the applicable use cases and acceptable data inputs will (may) expand. Without throwing shade, that’s the important GIGO discussion.
First step of a journey - its going to be very interesting.
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You don’t need to test every duration every month. If you have some hard group rides or races that is enough to keep the short stuff ‘tight enough’.