Why has a significant portion of the public latched onto the narrative that AI is stalling? Despite daily breakthroughs, you’ll often hear that “the output is slop” or that the “AI boom is just another tech bubble.”
As noted in a recent discussion on r/singularity regarding Louis Rosenberg’s concept of “AI Denialism,” this skepticism often feels like the first stage of grief. The argument isn’t about the tech not working; it’s about shifting goalposts. Every time AI clears a hurdle we thought was impossible (art, poetry, coding, bar exams), the definition of “true intelligence” moves just out of reach.
But if we look at the objective measures, the “hype cycle is dead” narrative falls apart. Here is the concrete evidence that AI is actually accelerating, not stalling.
1. The Coding Revolution is Already Here
Just twelve months ago, AI coding assistants were glorified autocomplete tools. Today, they are capable of refactoring entire codebases. Tools like Cursor and GitHub Copilot aren’t just saving a few seconds here and there; they are fundamentally changing how software is built.
We are seeing models solve complex coding tasks that require planning and context awareness—tasks that would have stumped the best models of 2023. This isn’t theoretical; it’s a massive, tangible productivity gain being felt by developers globally right now.
2. Reasoning Capabilities (System 2 Thinking)
The most common critique of Large Language Models (LLMs) is that they are just “stochastic parrots”—predicting the next word without understanding. The release of reasoning models, like OpenAI’s o1, has shattered this argument.
These models effectively use “System 2” thinking—pausing to “think” and reason through a chain of thought before answering. This has led to crushing performance on math and physics benchmarks that previously confounded AI. We aren’t just getting faster answers; we are getting deeply considered ones.
3. Multimodal Mastery: From Glitchy to Cinematic
Visual progress is the easiest to track, and the leap here is undeniable. Remember the viral AI video of Will Smith eating spaghetti from early 2023? It was a nightmarish, glitchy mess.
Fast forward to late 2024 and 2025. Models like Sora and Veo are generating high-definition, consistent video that is often indistinguishable from reality. The “uncanny valley” is being bridged at a speed that is genuinely difficult to comprehend.
4. Scientific Discovery Beyond Chatbots
While the internet argues about ChatGPT’s tone, AI is quietly solving some of humanity’s hardest problems. Google DeepMind’s AlphaFold has predicted the structure of nearly all known proteins—a feat that accelerates drug discovery by years.
From material science to weather prediction models that outperform traditional supercomputers, the utility of AI is exploding in fields that actually matter for human survival and progress.
Conclusion: The Exponential Curve
AI Denialism is often a coping mechanism. It is comforting to believe that the technology has hit a wall because the alternative—that we are rapidly approaching systems with cognitive supremacy—is terrifying.
But the data doesn’t care about our comfort. By every objective measure—reasoning, coding, creativity, and scientific utility—the line is going up, and it’s going up fast.