InfoWorld AI·
To many people, AI manifests one of sci-fi’s central plot points: built intelligence or machines that think and act independently of a human supervisor. But from my perspective, we haven’t quite achieved the true fulfilment of that vision. For this reason, many thought leaders describe world models as AI’s next big paradigm shift. These models learn from the full physical environment — synthetic or real — and can understand the spatial and physics complexities of worlds, unlike LLMs, which are restricted to language and images. AMI’s Yann LeCun is such a strong believer that he quit his role as chief AI scientist at Meta to found his own organization to advance world models. “I’ve not been making friends in various corners of Silicon Valley, including at Meta, saying that within three to five years, [world models] will be the dominant model for AI architectures, and nobody in their right mind would use LLMs of the type that we have today,” LeCun said. Apparently, LLMs have achieved gro
Read full articleAI-generated video has gone from novelty to creative tool almost overnight, and Runway has a front row seat to the shift. The New York-based company has raised close to $860 million at a $5.3 billion valuation, and its models are going toe-to-toe with the most well-funded labs in the world, including Google and OpenAI. The technology goes way beyond […]
AI systems have already gained impressive mastery over the digital world, but the physical world is still humanity’s domain. As it turns out, building an AI system that can compose a novel or code an app is far easier than developing one that can fold laundry or navigate a city street. To get there, many…
.grasp-results-table table { font-size: 0.875rem; line-height: 1.35; width: 100%; } .grasp-results-table th, .grasp-results-table td { padding: 0.35rem 0.5rem; } /* Consistent whitespace between major sections (this post is long and hr-heavy) */ article.post-content h2 { margin-top: 2.75rem; margin-bottom: 0.75rem; } article.post-content h2:first-of-type { margin-top: 2.25rem; } article.post-content h3 { margin-top: 1.65rem; margin-bottom: 0.5rem; } article.post-content hr { margin-top: 2.5rem; margin-bottom: 2.5rem; } GRASP is a new gradient-based planner for learned dynamics (a “world model”) that makes long-horizon planning practical by (1) lifting the trajectory into virtual states so optimization is parallel across time, (2) adding stochasticity directly to the state iterates for exploration, and (3) reshaping gradients so actions get clean signals while we avoid brittle “state-input” gradients through high-dimensional vision models. Large, learned world
Head straight for orbit with GeForce NOW — no space helmet required. PRAGMATA, Capcom’s long-awaited sci-fi action adventure, touches down on GeForce NOW the same day it launches worldwide. The futuristic journey through a cold lunar station in the near future can be streamed instantly from the cloud to almost any device, no console or […]
Agents are the future of legal AI, but how will they really work at scale, and what is a law firm world model? Plus, how ...
