Are there too many AI models being created? It feels like it, especially when we're getting about 10 new ones every single week. This rapid introduction of models makes it hard to compare them to one another, a task that wasn't easy to begin with. Why is this happening, though? Right now, we're in a unique phase of AI development, where both large and small AI models are being developed at a rapid pace by a wide range of creators, from individual developers to large, well-funded teams.
This week alone has seen a fascinating variety of models. For instance, Meta has launched LLaMa-3, touted as an "open" large language model, while a French team has introduced Mistral 8x22, pulling back on their open-source promises. Then, there's Stable Diffusion 3 Turbo, Adobe's AI Assistant for Acrobat, and several more, each bringing something unique to the table. The sheer number, including tools for AI development like torchtune and Glaze 2.0, makes it clear this isn't slowing down anytime soon.
But what does this mean for the future of AI? While it's hard to track every new model, their gradual improvements are what fuel progress in this field. Just like the automotive industry has evolved with countless models, the AI sector is diversifying. Each new model might not be a revolutionary step forward on its own, but together, these models are vital for the advancement of AI technology. We're committed to highlighting the most significant models, especially for those keen on machine learning advancements. When a truly groundbreaking model emerges, it's bound to stand out.