Aligning the world model with the environment for the agent's specific task is

Neural Information Processing Systems http://nips.cc/

Recently, model-based reinforcement learning algorithms have demonstrated remarkable efficacy in visual input environments.

Inference in the introduced linear Gaussian SSM is straightforward and can be performed using Kalman prediction and observation updates.

As the world's largest companies pour hundreds of billions of dollars into large language models, San Francisco-based Logical Intelligence is trying something different in pursuit of AI that can mimic the human brain. If you ask Yann LeCun, Silicon Valley has a groupthink problem. Since leaving Meta in November, the researcher and AI luminary has taken aim at the orthodox view that large language models (LLMs) will get us to artificial general intelligence (AGI), the threshold where computers match or exceed human smarts. Everyone, he declared in a recent interview, has been "LLM-pilled." On January 21, San Francisco-based startup Logical Intelligence appointed LeCun to its board .