Microsoft’s spending in the first quarter reached $20 billion, reflecting an aggressive push into AI and data center expansion.
Rapid progress in AI development may be slowing as companies run out of available digital data needed to train language models at scale, Google DeepMind CEO Demis Hassabis said. he warned. The industry has long relied on feeding vast amounts of online text into AI systems to improve performance, but the benefits are now starting to decline. Some experts, including OpenAI’s Ilya Sutskever, believe the industry has reached “peak data,” meaning future improvements are needed. A completely new approach.
Researchers are now exploring alternative methods, such as synthetic data, from which AI models generate and learn from their own outputs. While this technique holds promise in fields such as mathematics and programming, it presents challenges in more complex fields such as philosophy and art, where correctness is difficult to define. OpenAI has already applied this technique to its latest system, OpenAI o1, but challenges remain, particularly in preventing the AI from making mistakes or producing misleading information.
Technology industry leaders remain divided over whether advances in AI will continue at the same pace. Nvidia CEO Jensen Huang remains optimistic, citing strong demand for AI chips and ongoing innovation. But some of the company’s biggest customers are preparing for a plateau in AI development. Despite the uncertainty, investment in AI infrastructure remains high and companies continue to push the boundaries of what AI can achieve.
