use of ChatGPT for HIFI

I have used a Google product called NotebookLM.  The advantage is that it will only look at the sources you provide.  You can add youtube videos PDFs links.  I think that this increases the quality of the answers. 

I use a Google doc and paste in information that I find that is relevant.  On a free account you can only add 30 sources, but the sources can be a large as you want.  By adding content to only one Google Doc it reduces the # of sources.. 

https://notebooklm.google.com/

Then I asked:

`What do blind listening tests suggest about this topic. Restrict your comments to tests with high-end audio listeners as subjects':

 

Blind listening tests—particularly **double-blind** tests involving **experienced high-end audio listeners**—consistently show:

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### 🎧 **1. Power Cables**

* **Finding**: No statistically significant audible differences under controlled conditions.
* **Example**: In tests conducted by audio engineering societies (AES), even audiophiles could not reliably distinguish between standard and high-end power cords.
* **Conclusion**: Perceived differences are typically due to expectation bias.

---

### 🎼 **2. Interconnect Cables**

* **Finding**:

  * Differences are *occasionally* heard when cables are poorly made or excessively long.
  * In most high-quality systems with properly made cables, **blind tests fail to confirm audible distinctions**, even among trained listeners.
* **Conclusion**: Brand or price does not correlate reliably with perceived quality when sighted bias is removed.

---

### 🔊 **3. Speaker Cables**

* **Finding**:

  * Audible differences are more likely to be detected in blind tests **when comparing cables of significantly different gauge or impedance**, particularly with low-impedance or highly revealing speakers.
  * Between two high-quality cables of similar spec, **even audiophiles rarely detect consistent differences blind**.
* **Conclusion**: The most important variables are physical: resistance, length, and termination—not brand or exotic materials.

---

### 📜 Representative Studies & Findings

* **Audio Engineering Society (AES) papers** (e.g., by David Clark, Sean Olive, Floyd Toole) often report that:

  > Listeners—even experienced audiophiles—fail to distinguish expensive cables from inexpensive or standard ones in controlled, blind setups.
* **Boston Audio Society test**: A well-known blind test where listeners couldn’t reliably tell a Monster cable from a coat hanger wire in speaker cable comparisons.

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### 🧠 Cognitive Bias Note

In blind tests, many effects attributed to cables disappear, suggesting that **sighted listening is heavily influenced by expectations, branding, and cost**. This is especially true in high-end audio communities, where psychological investment in gear is high.

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### ✅ Summary for High-End Listeners

| Cable Type     | Consistent Audible Difference in Blind Tests? | Key Variable (If Any)              |
| -------------- | --------------------------------------------- | ---------------------------------- |
| Power Cables   | ❌ No                                          | None, if spec-compliant            |
| Interconnects  | ❌ Rare, unless defective or poorly shielded   | Shielding, length                  |
| Speaker Cables | ⚠️ Occasionally, if mismatched impedance      | Gauge, length, termination quality |

---

**Bottom Line**:
Even experienced listeners generally **cannot distinguish cables blind** unless a measurable electrical fault is present. Sighted evaluations often introduce psychological artifacts mistaken for sonic differences.
 

@cjmarkle - I agree 100%. These are tools designed to foster addictive behaviors. And addictive behaviors leads to tiered pricing. And tiered pricing leads to big income streams for these companies. I've worked in emerging technology on the west coast all my career. Although they like to paint their mission as virtuous, it's all about the money. 

@maholl50 - My bet it suggested keeping the Audio Research I-50 and Devore's paired together. Based on your mentioned equipment, that is pairing I'd keep myself based on what I know about them. What did it suggest? 

I've been using Google Gemini, standard issue on my Pixel 8. It can be very helpful but requires good prompts and follow up questions. I start by assigning an "expert" role related to my question. I'll tell it to be a "professor of electrical engineering", an "expert speaker designer", or similar. I also instruct it to seek out authoritative sources or specific sites. Then I follow up with requests and questions to resolve inconsistencies or hallucinations. This also prompts the AI to request more info from me to narrow down the information. 

I don't use it for subjective evaluations of gear. That's my role. But I'll ask it to find reviews that mention a particular quality for suggestions. 

As a casual user of AI. I have found its recommendations generally very good on sonic characteristics of equipment and general questions. But very bad at specific recommendations. It will often recommend the wrong piece of equipment... like I want a streamer and it recommends preamps or a mixture of different components. 

Now if you are loading full sets of your own data and carefully crafting queries... then that is a different thing.