A lot of people think open source AI has no chance against closed proprietary AI because there is no incentive to open sourcing powerful AI models you spent tons of money training. What these people don't understand is, all it takes is ONE actor to start a snowball. https://t.co/dpzFrLYnua
Interested in deploying and running custom AI models? Web2.0 has AWS SageMaker, Google Vertex, and HuggingFace. Web3.0 has @OpenGradient. https://t.co/lBvReKRKMS
Open source AI 🦾 https://t.co/ueNu2IpmWs
Recent discussions among industry leaders highlight the growing momentum of open-source AI models as they increasingly compete with closed-source alternatives. A notable launch from Meta, the Llama 3.1 model, can now be deployed on DigitalOcean with a single click through the newly introduced HUGS platform. This development underscores the trend towards simplifying AI deployment for users. Reports indicate that while closed models like OpenAI's GPT-4 initially led in adoption, open-source models have rapidly closed the quality gap and are gaining traction in enterprise applications. Jonathan Ross, CEO of Groq, emphasized this shift, stating, 'Open always wins,' reflecting the sentiment that open-source solutions may dominate the future landscape of AI technology. However, some experts caution that the comparison between open-access AI and traditional open-source software may not be as straightforward as it seems, with open-access models being less open than their label suggests.