Key Facts
- ✓ Vladimir Krylov serves as a scientific consultant for Artezio and is considered a top expert on AI in software development.
- ✓ Reasoning models, despite their advanced design, exhibit a hallucination rate that is double that of standard Large Language Models.
- ✓ OpenAI has reportedly initiated a 'code red' status, indicating internal concerns over losing their lead to competitors like Google.
- ✓ The future of programming is shifting toward 'vibe-coding,' a style that relies on directing AI rather than writing manual code.
- ✓ The comparison to opera singer Pavarotti highlights the potential shift from technical skill to intuitive direction in the coding profession.
The Inevitable Glitch
As artificial intelligence integrates deeper into professional workflows, a persistent issue remains: hallucinations. According to Vladimir Krylov, a professor of mathematics and scientific consultant at Artezio, these fabrications are not mere bugs to be patched, but fundamental features of how these models operate.
In a comprehensive year-end interview, Krylov, one of the most prominent Russian-speaking experts on AI in development, addressed the growing concerns regarding Large Language Models (LLPs). He argues that the industry must stop viewing hallucinations as errors and start understanding them as an unavoidable mathematical trade-off.
The discussion sheds light on the complex dynamics between major players like OpenAI and Google, while simultaneously predicting a radical shift in the nature of software engineering itself.
The Paradox of Reasoning
One of the most startling insights from Krylov’s analysis concerns the so-called reasoning models. These advanced systems, designed to think through problems step-by-step, are actually more prone to generating false information than their predecessors.
Krylov notes that these specific models hallucinate in twice the frequency of standard LLMs. This counterintuitive behavior is not a flaw in the design, but a mathematical inevitability inherent to the architecture of these reasoning systems.
As these models attempt to construct complex logical chains, the probability of introducing factual errors increases, creating a paradox where the AI designed to be more accurate actually fabricates more often.
"Pavarotti did not know how to read sheet music, and this says something about the future of vibe-coding."
— Vladimir Krylov, Professor of Mathematics
The Corporate Race
The competitive landscape of generative AI is shifting rapidly, with significant consequences for industry giants. Krylov highlights that OpenAI has reportedly declared an internal «code red», signaling a state of high alert regarding their competitive standing.
Despite their early dominance, the analysis suggests that OpenAI is currently lagging behind Google. This shift in momentum indicates that the race for AI supremacy is far from over, with Google potentially gaining a critical edge in the coming year.
The pressure to innovate is mounting, driving companies to push boundaries even as they grapple with the inherent limitations of current technology.
The Rise of Vibe-Coding
The conversation then pivots to the future of the human workforce, specifically programmers. Krylov poses a provocative question: will developers who write code manually soon become an endangered species?
The answer seems to lie in a new paradigm dubbed «vibe-coding». This approach prioritizes the ability to direct and curate AI output over the ability to write syntax from scratch.
Pavarotti did not know how to read sheet music, and this says something about the future of vibe-coding.
Using the legendary opera singer as an analogy, Krylov suggests that technical proficiency (reading notes) may become less valuable than the intuitive ability to direct the performance (the vibe). The future may belong to those who can guide the AI, not just those who can write the code themselves.
Deep Dives
For those looking to explore these topics further, Vladimir Krylov is a regular lecturer on the practical application of LLMs in development. He hosts a dedicated channel, Ai4dev, where he breaks down complex concepts for professionals.
His insights offer a roadmap for navigating the rapidly changing terrain of software development, emphasizing the need for adaptability and a deeper understanding of AI mechanics.
As the industry evolves, the distinction between human and machine capabilities continues to blur, necessitating a new definition of what it means to be a creator in the digital age.
