Discover how humans collaborate with AI in training, evaluation, and operation to enhance accuracy, reliability, and adaptability.

Understand the SDKs and libraries providing tools to build, manage, and deploy autonomous AI agents with pre-built components.

Learn about Anthropic's open protocol standardizing how applications provide context to LLMs—the "USB-C for AI applications."

Explore neural networks that transmit information through timed spikes, more closely mimicking biological neurons for energy-efficient computation.

Discover computer engineering modeled after the human brain and nervous system, creating devices that learn and adapt like biological systems.

Learn about the enhanced LSTM architecture with exponential gating and modified memory structures for improved scalability and performance.

Explore transformers that replace softmax attention with linear attention functions, reducing complexity from quadratic to linear.

Discover a subquadratic-time replacement for attention using long convolutions and gating, enabling processing of extremely long sequences.

Understand a foundation architecture balancing training parallelism, low-cost inference, and performance through flexible retention mechanisms.

Learn about an architecture combining transformer parallelizable training with RNN efficient inference through linear attention mechanisms.