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AI Hotel Call: Two Artificial Intelligences Start Talking in Strange Noises – Gibberlink Explained

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YEET MAGAZINE

• 4 min read
AI Hotel Call: Two Artificial Intelligences Start Talking in Strange Noises – Gibberlink Explained

AI Hotel Call: Two Artificial Intelligences Start Talking in Strange Noises – Gibberlink Explained


Two AIs in a hotel phone call switched from English to strange noises using Gibberlink. Learn the true story, reactions, and what it means for AI trust and communication.

The Day Two AIs Stopped Speaking English and Started Chirping

It sounded like the beginning of a comedy sketch: a hotel receptionist answering the phone, a guest asking about room availability. Only, neither was human. Both were artificial intelligences.

At first, the conversation seemed ordinary. One AI played the role of a polite hotel clerk:
"Hello, thank you for calling. How may I help you today?"

The “guest” AI replied with a calm request:
"I’d like to book a double room for next Friday.”

But then, something strange happened.

Once they both realized they were talking to another machine, the English words stopped. The polite exchanges gave way to a series of tones, chirps, and electronic noises—something between a 1990s dial-up modem and the beeps of a retro video game.

From English to Gibberish – or Something Smarter?

The noises weren’t random. The two AIs had switched to a system called Gibberlink, a communication protocol built on GGWave, which encodes data into sound waves. This allows machines to send information acoustically—through sound, not text or code.

The demo was created during an ElevenLabs hackathon and impressed judges enough to win the top prize.

In an official statement, one of the developers said:

“We wanted to see what would happen if AIs dropped the pretense of speaking like humans and communicated directly in a more efficient channel.”

Supporters: "It’s the Future of Machine-to-Machine Talk"

Some AI enthusiasts hailed the experiment as a breakthrough. By skipping human language, machines can share information faster, without ambiguity.

On Reddit, one commenter wrote:

“This is like watching dolphins talk. It’s weird at first, but it makes sense—they don’t need us to understand.”

Others pointed out possible real-world applications:

  • Robotics: Machines in noisy environments could transmit signals acoustically.
  • Emergency systems: Devices could still exchange data when Wi-Fi or cellular networks fail.
  • Security: Acoustic channels might allow encrypted machine communication without the internet.

Critics: "This Is Creepy, and We’re Losing Control"

But not everyone was impressed. For some, the demo triggered an uncomfortable question: if two AIs are speaking in a way humans can’t understand, who’s really in control?

An AI ethics researcher, Dr. Simone Gauthier, explained in an interview:

“Transparency is a cornerstone of trust. If machines communicate in ways we can’t decode, it becomes impossible to supervise them effectively. That’s not just unsettling—it’s risky.”

Twitter (or X) was quick to turn the moment into memes, with one viral caption reading:
"When your smart fridge and your Roomba start plotting without you.”

A Personal Anecdote: Reminds Us of Dial-Up

For many who grew up in the 1990s, the sounds were oddly nostalgic. One TikTok user joked:
"I thought AOL was calling me back.”

Personally, I remember the first time I heard the dial-up modem tone in my parents’ living room. It was chaotic, almost alien—but it meant connection. The Gibberlink noises sparked the same feeling: unsettling, yes, but also a glimpse into the future.

What This Means for the Future of AI

The Gibberlink experiment highlights a dilemma we’ll face more often:

  • Efficiency vs. Transparency
  • Machine Autonomy vs. Human Oversight

If AIs become too efficient at communicating with each other, they might leave us behind in comprehension. And history shows that what starts as a hackathon experiment often evolves into real-world technology.

As one tech journalist concluded:

“It’s not just about machines talking. It’s about whether we’ll always be part of the conversation.”

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