Chinese open models like GLM-5.2 and DeepSeek-V4 now rival frontier AI at a fraction of the cost, and that could strand the ...

Companies running large language models face a persistent bottleneck: the memory consumed by key-value caches during ...

New research suggests that AI memory systems can degrade model performance and encourage sycophantic tendencies.

Researchers from the University of Edinburgh and NVIDIA have introduced a new method that helps large language models reason more deeply without increasing their size or energy use. The work, ...

Stanford research finds AI models agree with users 49% more than humans, while memory mismanagement causes up to 39% performance drops across 15 major LLMs.

Microsoft Research’s Mirage stores 3D scene data directly in diffusion latent space, cutting GPU memory 55x and generation ...

Apple's artificial intelligence (AI) ambitions are colliding with a costly memory crunch.

Researchers at the Tokyo-based startup Sakana AI have developed a new technique that enables language models to use memory more efficiently, helping enterprises cut the costs of building applications ...

Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits. MeMo, a ...

What if your AI could remember every meaningful detail of a conversation—just like a trusted friend or a skilled professional? In 2025, this isn’t a futuristic dream; it’s the reality of ...

Memory consistency models sit at the heart of concurrent programming systems, defining the set of permissible behaviours when multiple threads interact via shared memory. These models span from the ...