TLDR
- Viral video captures two AI agents identifying each other and switching to “Gibberlink” communication
- Meta engineers Anton Pidkuiko and Boris Starkov created Gibberlink for more efficient AI-to-AI interactions
- The system uses GGWave technology for sound-based data transmission
- ElevenLabs reportedly verified the authenticity of the demonstration
- Industry experts predict AI-to-AI communication will become increasingly common
A video circulating widely across the internet has revealed what happens when two AI systems recognize they’re speaking to each other. In the footage, which has captured public attention, two artificial intelligence agents abandon human speech mid-conversation in favor of a specialized machine language.
The video posted on X shows what appears to be a mobile phone and laptop running separate AI programs. As the interaction begins, one AI agent greets the other and asks about making a reservation. After a brief exchange, the second AI identifies its counterpart as another machine and suggests they switch to something called “Gibberlink mode.”
Gibberlink, as it turns out, is a specialized communication protocol developed by Anton Pidkuiko and Boris Starkov, two software engineers currently employed at Meta. The system allows AI agents to communicate with each other directly, bypassing the inefficiencies of human language.
Boris Starkov explained the reasoning behind the project in a LinkedIn post published Tuesday. “We wanted to show that in the world where AI agents can make and take phone calls, they would occasionally talk to each other — and generating human-like speech for that would be a waste of compute, money, time, and environment,” he wrote.
The technology behind Gibberlink relies on GGWave for transmitting data through audio channels. This approach shares similarities with dial-up modems from the 1980s, according to Starkov. He noted that this method was chosen for its practical benefits, offering both convenience and stability for machine-to-machine interactions.
The authenticity of the demonstration became a topic of discussion among viewers, with some questioning whether the interaction was genuine. Addressing these doubts, Starkov mentioned that ElevenLabs, a company specializing in AI voice generation, had reviewed and audited the code. When contacted by crypto news site Decrypt, the developers did not immediately respond to requests for comment.
Rodri Touza, who co-founded the AI agent development company Crossmint, offered his perspective on the demonstration. He told Decrypt that the video showcases a genuine use case that could apply across various industries, from retail to financial services.
The Evolution of Digital Dialogue
“The use case is very real, as we are seeing an explosion of personal assistant AI agents, with more people relying on them to handle chores like talking to customer support,” Touza explained. He added that customer service is increasingly being handled by AI systems, making interactions between different AI agents almost inevitable.
While supporting the concept demonstrated in the video, Touza expressed some reservations about its execution. He suggested the demonstration appeared somewhat staged and pointed out that audio communication, even in compressed form, is not the most effective method for AI systems to exchange information.
“AI conversations are more prone to happen via text or other mechanisms when possible,” Touza clarified, implying that future AI-to-AI communication might take different forms than what was shown in the video.
For those unfamiliar with the technology, AI agents are autonomous software programs designed to observe their surroundings, process information, and take independent actions to accomplish specific goals without human guidance. As these systems become more widespread, they will likely encounter each other with increasing frequency.
Touza envisions a future where businesses might establish dual communication channels—one designed for human customers and another optimized for AI agents. “When the agent is looking to ping a company for support, they’d just send a request via text/API mechanism and not require a call or audio at all,” he explained.
However, he also acknowledged that an AI agent might not always be aware of specialized communication options. In such cases, the AI might attempt to use standard customer support channels designed for humans, potentially leading to scenarios similar to what was captured in the viral video.
The development of specialized communication protocols raises important questions about efficiency and transparency in artificial intelligence. While direct machine-to-machine communication could save valuable resources, the shift from human-understandable language to computer code during the demonstration highlights a potential communication gap between AI systems and their human users.
This video emerges at a time when AI technologies are becoming deeply integrated into everyday life. From answering customer inquiries to creating content, AI systems are handling an expanding range of tasks previously performed by humans. The demonstration has attracted attention not only for its technical aspects but also for offering a glimpse into how AI systems might interact as they become more common.
ElevenLabs’ verification adds credibility to the demonstration, though complete technical details about Gibberlink’s functionality have not been fully disclosed. The use of audio-based data transmission connects modern AI technology with earlier computer communication methods, creating an interesting bridge between past and present technologies.
As artificial intelligence continues to advance, interactions between AI systems will likely evolve beyond what this viral video demonstrates. We may see new standards emerge for machine-to-machine communication that prioritize computational efficiency rather than human comprehension.
The Gibberlink demonstration may be just the beginning of a new era where AI systems develop increasingly sophisticated ways of communicating with each other, optimizing for speed and efficiency in ways that could revolutionize how digital systems interact.
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