AI in 2026 (gusarich.com)

In a recent prediction for the future of AI by 2026, advancements in large language models (LLMs) are expected to accelerate rapidly due to increased computational resources. The introduction of a test-time scaling paradigm continues to reshape model capabilities, with anticipated improvements allowing models like GPT-5.2 Pro and its successors to work on complex tasks for extended periods, marking a significant leap in AI problem-solving efficacy. This could lead to AI systems capable of completing intricate projects autonomously, suggesting a shift toward more agentic AI that can exhibit traits of artificial general intelligence. The author forecasts that by the end of 2026, AI will significantly impact various fields, including mathematics, software engineering, and scientific research. Novel breakthroughs in automated code generation and long-term memory integration for agents could lead to unprecedented scientific discoveries. While acknowledging the speculative nature of these advancements, the emphasis on memory and continual learning suggests that AI could soon tackle sophisticated, long-term challenges effectively. This trajectory positions AI as a pivotal force in innovation, potentially enabling machines to contribute to complex problem-solving that could include addressing some of the hardest theoretical questions in science and mathematics.