#model-robustness

#model-robustness

AI Mode can use your previous conversations, along with places you've searched for or tapped on in Search and Maps to deliver more relevant options, personalized to you. So if AI Mode infers that you have a preference for Italian food, plant-based meals, and places that have outdoor seating, you may get results suggesting options like these.

Before you can even get the opportunity to impress a human interviewer, you will first need to impress the algorithm! More recently, AI has also been used to assist current employees in doing their jobs and then to help their employers evaluate how well employees are performing in those jobs.

What happens under the hood? How is the search engine able to take that simple query, look for images in the billions, trillions of images that are available online? How is it able to find this one or similar photos from all that? Usually, there is an embedding model that is doing this work behind the hood.

OpenAI's GPT-5.2 Pro does better at solving sophisticated math problems than older versions of the company's top large language model, according to a new study by Epoch AI, a non-profit research institute.

Before enterprises can deploy AI agents that actually work, they need something most organizations don't have: a single, authoritative source of truth.

sensitive or potentially harmful content.

Since AlexNet5, deep learning has replaced heuristic hand-crafted features by unifying feature learning with deep neural networks. Later, Transformers6 and GPT-3 (ref. 1) further advanced sequence learning at scale, unifying structured tasks such as natural language processing. However, multimodal learning, spanning modalities such as images, video and text, has remained fragmented, relying on separate diffusion-based generation or compositional vision-language pipelines with many hand-crafted designs.