DeepSeek

If GPT-4 was the apex of pretraining, DeepSeek might be the blueprint for what comes next. Released in two families—DeepSeek-V3 and DeepSeek-R1—this Chinese open-source model series isn’t just catching up to frontier LLMs. It’s reshaping the paradigm entirely. By sidestepping traditional supervised fine-tuning in favor of reinforcement learning (RL), and coupling it with memory-efficient innovations like Multi-head Latent Attention (MLA) and cost-efficient training techniques like FP8 mixed precision and fine-grained MoE, DeepSeek models demonstrate how strategic architectural bets can outpace brute-force scale. ...

The AI world has always been unusual, but starting in early 2025, it became increasingly so. LLM developers began releasing and updating models at unprecedented paces, while more giants and startups joined the AI rush—from foundational generative models (text, image, audio, video) to specific applications. It’s a new kind of gold rush, but fueled by GPUs and transformer architectures. On February 1st, DeepSeek released its open-source model DeepSeek R1, quickly recognized for rivaling—or even exceeding—the reasoning power of ChatGPT-o1. The impact was immediate. Just days later, a screenshot from Reddit showed Sam Altman, CEO of OpenAI, admitting: ...

A multi-modal foundation model by DeepSeek AI, integrating vision and language for high-performance tasks including OCR, captioning, and visual reasoning.