A prominent AI founder and researcher has asserted that Artificial General Intelligence (AGI) — machines with cognitive abilities on par with or exceeding those of humans — may already be a reality, sparking fresh debate about the pace and implications of AI development. That’s according to Eliza Labs’ founder Shaw Walters, who spoke with Decrypt last week during ETHDenver. Walters said current leading models already meet his definition of artificial general intelligence, better known as AGI.
“I think that we’re at the inflection point where we have AGI,” he said. “I completely believe that this is general intelligence. It’s nothing like us. It learns in a completely different way, but it is intelligent nonetheless, and it is very general.” Originally launched in 2024 as ai16z, Walters founded Eliza Labs, which created the open-source ElizaOS, one of the first frameworks for creating autonomous AI agents for blockchains.
The claim comes amid rapid advancements in AI capabilities, especially in systems that can reason, plan, learn and generalize across diverse tasks without being explicitly programmed for each one — hallmarks many experts use to define AGI.
What the Founder Claimed
In recent commentary, the AI founder — speaking on condition of attribution in some outlets and publicly in others — noted that recent large-scale AI models and agentic systems demonstrate emergent reasoning, autonomous planning and cross-domain fluency that approaches or meets criteria traditionally associated with AGI.
This perspective suggests that AGI might already exist in forms that outperform human benchmarks on standardized tests or complex problem sets without being explicitly trained on those tasks.
Context: What Is AGI?
Artificial General Intelligence refers to systems that:
Understand and reason across a wide range of domains
Learn autonomously from limited data
Apply knowledge flexibly like a human brain
Transfer learning from one task to novel tasks without retraining
Current state-of-the-art AI — including major language models and agent frameworks — exhibits strong capabilities in narrow domains, but most experts have historically argued that true AGI remains a research goal rather than a realized product.
Why This Claim Is Controversial
While the AI founder’s comments highlight impressive progress, many researchers caution that existing systems still lack key elements of human-like intelligence — such as deep conceptual understanding, autonomous reasoning in open environments, and robust common-sense cognition.
Academic and industry observers point out that:
Performance on benchmarks doesn’t always equate to general understanding
Models often rely on pattern recognition rather than causal reasoning
Many AI systems require extensive training data and human-designed prompts — unlike biological intelligence
Implications if AGI Is Here Now
If AGI — or something functionally similar — is already operational, the implications are profound:
Economic impact: Automation could accelerate productivity gains while disrupting labor markets.
Ethical considerations: Decision-making authority, bias and accountability become even more critical.
Safety and governance: Ensuring alignment with human values and preventing harmful outcomes would be urgent global priorities.
Some policymakers and researchers argue that even if current systems are not AGI by strict definitions, preparing regulatory, ethical and societal frameworks now remains essential given the pace of advancement.
Broader Debate in the AI Community
The AI field is divided:
Optimists say recent models demonstrate fundamental breakthroughs that have ushered in a new epoch of machine intelligence.
Skeptics argue that current AI is still fundamentally narrow and that true AGI — capable of self-directed cognition — remains years or decades away.
This debate continues to shape investment, research priorities and public policy discussions around AI governance, safety standards and international cooperation
