Thanks for the answer. All I wanted to ask the AI were questions about definitions, like “What does ‘awake at night’ mean?” and further explanations. I think it wouldn’t hurt if you limited consequential questions to two or even three, if it’s a pro-exclusive feature. I like this feature, by the way. Great job:)
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From these comments, you can see how much people depend on your app.
I’ve chatted with you, and your staffers, about bugs and feature requests, for years now. In addition, I’ve purchased every sleep gadget that has been offered.
No other Sleep app holds a candle to Sleep as Android, and I have some more feedback. I’ll leave it here, rather than in-app submission, because it could warrant some discussion:
The Assistant was stymied, when I prompted about comparing the App’s sleep reporting to Wearables’ direct reporting.
For example, my Garmin Epix 2 Pro is linked and communicates with SaA (without needing the “alternative” addon). However, the Garmin’s sleep graphs report far different sleep cycles. My Deep Sleep, according to the Garmin’s reporting, only occurs within the first half of my sleep sessions. According to the device, the rest of my night is spent in REM, Light Sleep, or brief spikes of Awake. Last night’s Sleep Score is a 93, on the App, while the Garmin reports a 77.
Perhaps through distinguishing N1-REM instances, Sleep as Android reports regular cycles of Deep Sleep throughout the whole night. This highlights the differences in algorithms that determine the cycles as both the device and App are working through the same base data HR, HRV, Pulse ox, etc.
It’s difficult to discern whether users’ Wearables, which they depend on for all-day data (or just all-night) should be trusted, when comparing the App’s -vs- Wearables’ sleep reporting/graphs.
My feedback is to train the generative model further on the nuances of how the same input data can produce vastly different sleep graphs. Naturally, you’d need to balance this with protecting proprietary algorithms.
Like most users who pair Wearables with the App, the first thing I see in the morning is my sleep reporting on my phone, and then my Garmin watch.
Explaining the nuances of wildly different sleep reporting is an excellent opportunity for the new Assistant to shine. Disseminating these complicated calculations, especially in a concise (think ELI5) concept, showcases the potent lifestyle value of Sleep as Android and the power of its Assistant feature.
Thanks, Petr 
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@lenka-urbandroid My sleep duration goal in the settings is at 8 h 30 m.
@petr-urbandroid I can report it but I don’t really think this is a bug. This is just generative AI being generative AI. It has no place giving people health advice.
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@b_j I think this isn’t about generative AI, we use generative AI in a different way, first we feed the sleep score data, but we also explain what are expected ranges, what may be too low etc… and we basically use generative AI only to generate a human understandable summary of all the data we have provided. This is a very constraned approach and we hope to minimize any error caused by the generative AI this way… so what I wanted to check from your report is what prompt are we generating to see if we can improve on our end…
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@evennight many thanks, I think we do not give it enough context to correctly answer the awake question … we will elaborate on this…
Hello @REM … many thanks for your suggestion. At the moment we do not use our own model, but we utilize Google’s Gemini LLM model.
But I think the differences you see in the data may step from the fact that there isn’t any standard way how differentiate between light sleep / deep sleep - where different vendors place the division line.
This is summarized in detail on this article on our website:
Not sure if and how an AI model could solve this.
Thanks, Petr.
I use their Gemini v1.5 Pro 0827 model for work, although I’m not sure which Gemini model Sleep as Android implemented.
The trainability of this model is strong. If not already in-progress, training the LLM on the wealth of knowledge from your blog articles empowers the Assistant to articulate in different ways. Users can then prompt the Assistant to explain in a way they know how to best understand and retain.
@petr-urbandroid that’s unfortunately not how generative AI works. you can’t constrain it in the ways you are seeking to.
Can this data be sent over MQTT or some other way I’d like daily briefing sent to Home Assistant could be awesome to TTS this in the morning
There seems to be an issue with the AI’s interpretation of the sleep disturbance value (according to the attached screenshot, this SHOULD be called AHI Apnoea Hypopnea Index… Is the AI giving wrong info here?).
The AI is telling me that as I have a Sleep Disturbance Value of 1, which is lower than the national average in my country, then it indicates possible issues.
I think that the logic here is reversed. The lower the Sleep Disturbance Value, the better. I use a CPAP machine, so I do expect the AHI to be lower than 5 (my target is lower than 2).
I mentioned my circadian rhythm disorder to the assistant and it gave incorrect treatment information.
Is there any way to limit its ability to provide poor medical advice?
Sure, it says to speak to your doctor, but that doesn’t justify poor information/advice. I was not given the option to correct it/inform it like you can with Chat GPT.
This feature won’t be useful for me, but I hope it helps others… But I mostly hope it doesn’t mislead anyone.
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I tried this and used the “How did I sleep last night” question. That made me want to k iw what it would say about Sunday’s sleep. There is not an option to check any past nights sleep. Would also be nice to maybe see a comparison of 2 different sleep cycles.
Also, a tad off topic, but it did mention my snoring numbers, how does the app seperate snoring from continuous allergic rhinitis that can sometimes sound like snoring? And yes, that is a thing.
Hi @ShoalBear,
EDIT: sorry, I was mistaken and deceived by the Assistant’s answer…
Regarding allergic rhinitis - this sound will probably confuse the algorithms into thinking it might be snoring. To design a new sound class for rhinitis, we would need hundreds of thousands of samples of confirmed rhinitis sounds - so the algorithms can learn to recognize them.
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@b_j in fact you can, we use a grounding approach, we first restrict the answer to only relate to the data we have provided, then we explain what are correct ranges and what is good / bad or neutral so we specify very carefully the whole playground and we only ask the AI to summarize it in human language and translate it to user’s langauge…
This approach greatly reduces any risk of hallucination of the AI, but of course theme may be issues which can be addressed by further restricting the scope. We can work iteratively here and fine-tune, but for that I would need to see what promt did we send to the model so that I can first reproduce it and then modify the promt so that the problem is fixed…
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Thanks for the reply @lenka-urbandroid I appreciate it.
I am glad to hear that the app doesn’t differentiate snoring from rhinitis. Now I can relax a bit about that issue.
Maybe there could be an addition of that info on your page about snoring stats, etc?
When AI compares my sleep with others, it mentons stats about my snoring, heart rate variability and breathing - 3 things i am not tracking at all?
(I might have tried those options a few times in the past, but that was at least a year ago)
Also, if you ask to compare your sleep when others, which period does it look at? Last night, last week, last month?
It’s most likely because you use Sonar as the tracking method, it can measure your breath and heart beat alongside the things accelerometer can do
I had a similar experience. The app tells me I don’t snore, and I don’t. But comparison with others, the app said my snoring is beyond the healthy limits.
I asked a follow-up, could this be my husband’s snoring. AI replied this is a misunderstanding, my sleep data does not contain evidence of snoring.
When tracking snoring, I have noticed the app never tracks my husband’s snoring although it is loud. (That’s impressive!) So, maybe there is some kind of a bug as the AI says I snore more than average although the data says I don’t snore.
@petr-urbandroid @lenka-urbandroid reporting this because I like to help you, I have been using the app since it was brand new. I like the AI feature and its replies are beyond my expectations.
Could you name the AI “The Sleeping Droid”? Pun intended
The AI tells me my regularity is improving (I go to bed earlier) but my duration in the short term has gone down. For 2 nights I woke up several hours before the alarm. The AI / app does not pay attention on such instances (very short sleep, waking up hours before alarm) but seems to assume the wake up time is single factor. Whether wake up time is planned or accidental and how it is associated with wake up pattern and alarm is crucial, I hink.
Hi @Saara,
the regularity and duration can go the opposite way, it all depends on your data set.
Regularity is derived from the SRI index (the probability of you being in the same state (asleep or awake) at any two time points 24 hours apart).
In which direction did the SRI change in your recent history?
(what about the Sleep AI - Android Intelligence 
?)