Knowledge distillation transfers useful behavior from a large teacher model into a smaller student model. The student learns from the teacher’s probability distributions, generated examples, internal representations, or a combination of those signals and original labels. A distilled model may run faster, cost less, and fit on hardware that cannot host the teacher, making the technique valuable for mobile and edge deployment. Compression can reduce accuracy or remove rare capabilities, and the student may inherit the teacher’s bias, errors, or unsafe behavior. Teams compare performance across important subgroups and tasks, verify latency and memory gains, and confirm that legal or licensing terms permit the training process.
Google Cloud and Figma have launched an expanded partnership to embed Google’s generative AI models – including Gemini 2.5 Flash and Imagen 4 – directly into Figma’s design tools, reducing latency and accelerating creative workflows.
Opera today introduced Neon, an AI-powered browser that can run tasks and navigate pages autonomously — aiming to shift web browsing from passive to “agentic.”
AI search startup Perplexity has reportedly raised $200 million at a $20 billion valuation, just two months after a $100 million round – signaling its rapid rise as a major rival to Google.