We evaluated our overall performance last round? Our portfolio included personalized chatbots – interactive helper apps driven by multimodal giant language models, a concept we were unaware of at the time but is now commonly referred to as the most popular aspect of AI today; with OpenAI and Google DeepMind releasing their flagship video technology models, Veo, inside just a week of each other this December; and more general-purpose robots capable of performing a wider range of tasks. 

Fortunately, we correctly identified and addressed the issue of AI-generated election disinformation being all over the place. Despite numerous challenges that have caused us great concern over the past 12 months, however. 

So what’s coming in 2025? Disregarding the plain right allows you to assume that both parties will establish a trade agreement. Here are five alternative options chosen by our AI team:

1. Generative digital playgrounds 

If 2023 was the 13th year of a recurring cycle, then 2024 would be the 14th year of that cycle, and so on. In cases where you’ve guessed that generative digital worlds—a.k.a. virtual reality (VR) or augmented reality (AR)—will revolutionize the way we interact and create, you’re not alone. Video games), excessively addictive to some people are.

When Google DeepMind unveiled its innovative technology in February, we caught a fleeting glimpse of its potential, as it transformed a still image into a side-scrolling 2D platform game that allowed players to interact with each other seamlessly. In December, the agency unveiled a groundbreaking innovation: a mannequin capable of transforming a starter image into a fully immersive digital environment.

Multiple companies are developing similar technological innovations. In October, Decart and Etched, two AI startups, unveiled a clandestine Minecraft hack, whereby every entity within the game was endowed with. World Labs, founded in part by renowned AI pioneer Fei-Fei Li, is pioneering the development of gigantic world models, colloquially referred to as LWMs.

Video games are a prominent example of software. Early experiments exhibited a lighthearted quality, while generative 3D simulations could uncover innovative design concepts for novel video game developments, effortlessly transforming sketches into immersive, interactive environments in real-time. This might result in . 

However, they could also be leveraged to train robots. To enable seamless collaboration between machines in the ever-evolving world, World Labs must focus on cultivating their spatial intelligence, allowing them to interpret and operate harmoniously alongside humans on a daily basis? Although robotics researchers often lack a thorough understanding of the actual scenarios they should draw upon when developing this expertise. Spinning up multiple digital worlds, then diving in to learn through trial and error, could potentially fill the gap.