Artificial intelligence is reaching a new chapter in its development by entering an era of self-optimisation. As such, AI is becoming capable of discovering and improving algorithms autonomously. A recent example is AlphaEvolve, an evolutionary AI agent developed by Google DeepMind that can develop complete code and optimise complex tasks, ranging from data centre management to chip design.
This advance is not an isolated one. Technology giants such as Microsoft and OpenAI are investing heavily in advanced AI, too. Their collaboration has led to the expansion of the Azure OpenAI Service, which now combines large language models with cloud personalisation tools. Meanwhile, Meta is focusing on generative and multimodal AI.
The benefits are clear: operational efficiency, accelerated innovation and reduced costs. Technology like AlphaEvolve has already delivered tangible savings, accelerating model training time and improving resource utilisation.
In a sector where investment in AI is expected to exceed USD 300 billion this year, the development of self-optimising AI is a race for efficiency. The companies that lead this evolution could define the future of computing, while those that fall behind could struggle to catch up.
