u/Weary-Necessary-3756

Hi everyone. I’m a 29-year-old male. I had a 28-hour Holter monitor. My cardiologist reviewed it and told me it was normal/clean.

Summary:

• Total QRS: 125,749
• Ventricular beats: 0
• Supraventricular beats: 0
• Noise: 1%
• Min HR: 60 bpm at 03:38
• Avg HR: 75 bpm
• Max HR: 141 bpm
• Tachycardia: 12% total
• Bradycardia: 3% total
• Max R-R interval: 6.96 seconds at 05:42 during sleep
• Interpretation: no SVES/VES observed

I’m worried about the “Max R-R 6.96 seconds” line. If this were a real sinus pause or AV block, wouldn’t it usually be mentioned separately in the interpretation? Could this be an automatic measurement error/artifact or a missed QRS?

I had no fainting, no syncope, no major symptoms. Cardiologist said the report was normal. I’m mainly asking whether a long Max R-R value on an automated Holter summary can appear due to artifact even when the cardiologist considers the study clean.

Hi everyone. I’m a 29-year-old male. I had a 28-hour Holter monitor. My cardiologist reviewed it and told me it was normal/clean.

Summary:

• Total QRS: 125,749
• Ventricular beats: 0
• Supraventricular beats: 0
• Noise: 1%
• Min HR: 60 bpm at 03:38
• Avg HR: 75 bpm
• Max HR: 141 bpm
• Tachycardia: 12% total
• Bradycardia: 3% total
• Max R-R interval: 6.96 seconds at 05:42 during sleep
• Interpretation: no SVES/VES observed

I’m worried about the “Max R-R 6.96 seconds” line. If this were a real sinus pause or AV block, wouldn’t it usually be mentioned separately in the interpretation? Could this be an automatic measurement error/artifact or a missed QRS?

I had no fainting, no syncope, no major symptoms. Cardiologist said the report was normal. I’m mainly asking whether a long Max R-R value on an automated Holter summary can appear due to artifact even when the cardiologist considers the study clean.

One thing I want to make clear is that my concern is not really about every AI company.

Most other companies are not putting these kinds of restrictions in the same way right now(for now). What worries me is seeing a company as huge as Google doing this.Google has insane resources, money, infrastructure and talent. So when even Google starts cutting token limits and making access more restrictive, it feels like a bad sign for where the whole industry might go.this kind of aggressive limiting from a company that powerful feels greedy to me. It makes me worry that once people become more dependent on AI the best versions will slowly become harder to access unless you can pay much more.

One thing I want to make clear is that my concern is not really about every AI company.

Most other companies are not putting these kinds of restrictions in the same way right now(for now). What worries me is seeing a company as huge as Google doing this. Google has insane resources, money, infrastructure and talent. So when even Google starts cutting token limits and making access more restrictive, it feels like a bad sign for where the whole industry might go.this kind of aggressive limiting from a company that powerful feels greedy to me. It makes me worry that once people become more dependent on AI the best versions will slowly become harder to access unless you can pay much more.

I honestly feel disappointed by Google’s current position in AI.

This is Google we are talking about: one of the most important tech companies in the world, with some of the best engineers, and a company that played a huge role in the early development of machine learning and modern AI. So it is genuinely frustrating to see newer companies like OpenAI and Anthropic seemingly move faster and deliver more impressive models.

After Google I/O, I was expecting something that would finally feel like a real leap forward. Instead, what we got felt underwhelming. A faster Flash model is nice, but speed alone is not enough. If a model is not smart enough, users end up repeating the same task multiple times, which still costs time, tokens, and frustration.

Right now there is huge demand for coding, reasoning, agentic workflows, and genuinely capable AI assistants. Does Google not see this? Why is the big push still around faster, cheaper, limited models instead of a true “wow” moment?

The new usage limits and the pricing of Gemini plans also feel disappointing. For a company with Google’s resources, it feels like the product should be much more competitive, not more restricted and confusing.

I keep waiting for Google to make a major comeback in AI. Every event feels like “maybe this is the one,” but the big breakthrough never seems to arrive.

Do you think Google is actually losing the AI race? Is this a leadership/product strategy problem? Or am I being too harsh and missing the bigger picture?

I honestly feel disappointed by Google’s current position in AI.

This is Google we are talking about: one of the most important tech companies in the world, with some of the best engineers, and a company that played a huge role in the early development of machine learning and modern AI. So it is genuinely frustrating to see newer companies like OpenAI and Anthropic seemingly move faster and deliver more impressive models.

After Google I/O, I was expecting something that would finally feel like a real leap forward. Instead, what we got felt underwhelming. A faster Flash model is nice, but speed alone is not enough. If a model is not smart enough, users end up repeating the same task multiple times, which still costs time, tokens, and frustration.

Right now there is huge demand for coding, reasoning, agentic workflows, and genuinely capable AI assistants. Does Google not see this? Why is the big push still around faster, cheaper, limited models instead of a true “wow” moment?

The new usage limits and the pricing of Gemini plans also feel disappointing. For a company with Google’s resources, it feels like the product should be much more competitive, not more restricted and confusing.

I keep waiting for Google to make a major comeback in AI. Every event feels like “maybe this is the one,” but the big breakthrough never seems to arrive.

Do you think Google is actually losing the AI race? Is this a leadership/product strategy problem? Or am I being too harsh and missing the bigger picture?