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Guillermo del Toro and Ben Affleck, among others, have voiced concerns about the capabilities of generative AI in the creative industries. They believe that while AI can produce text, images, sound, and video that are technically proficient, it lacks the authentic emotional depth and creative intuition inherent in human artistry—qualities that define works like those of Shakespeare, Dalí, or Hitchcock.
Generative AI models are trained on vast datasets and excel at recognizing and replicating patterns. They can generate coherent narratives, mimic writing or artistic styles, and even compose poetry and music. However, they do not possess consciousness or genuine emotions. The “emotion” conveyed in AI-generated content is a reflection of learned patterns rather than true emotional experience.
Having extensively tested and used generative AI over the past four years, I observe that the rapid advancement of the field suggests many current limitations could be overcome in the future. As models become more sophisticated and training data expands, AI systems are increasingly capable of generating content that is coherent, contextually relevant, stylistically diverse, and can even evoke emotional responses.
The following video is an AI-generated “casting” using a text-to-video model specifically prompted to test emotion, expressions, and microexpressions. This is only the beginning.
https://generative-world-explorer.github.io
Planning with partial observation is a central challenge in embodied AI. A majority of prior works have tackled this challenge by developing agents that physically explore their environment to update their beliefs about the world state. However, humans can imagine unseen parts of the world through a mental exploration and revise their beliefs with imagined observations. Such updated beliefs can allow them to make more informed decisions at the current step, without having to physically explore the world first. To achieve this human-like ability, we introduce the Generative World Explorer (Genex), a video generation model that allows an agent to mentally explore a large-scale 3D world (e.g., urban scenes) and acquire imagined observations to update its belief about the world .
Mochi 1 AI operates on a pay-as-you-go model, meaning you only pay for the services you utilize without any hidden fees.
A feed-forward model capable of reconstructing 3D scenes parameterized by 3D Gaussians from unposed sparse multi-view images.
Linus Torvalds, the creator and maintainer of the Linux kernel, talks modern developments.
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