The Daily AI Briefing - 14/03/2025

Welcome to The Daily AI Briefing, here are today's headlines! Today we're tracking major moves in the AI landscape with OpenAI lobbying for federal protection, Cohere releasing an impressively efficient enterprise model, Google enhancing Gemini with personal data, and several notable model releases. Let's dive into the details of these developments reshaping the AI world, from regulatory battles to technical breakthroughs. First up, OpenAI is making waves in Washington with its ambitious regulatory proposal. The company has submitted a 15-page document to the White House's AI Action Plan, advocating for federal shield laws to protect AI companies from the patchwork of state regulations. OpenAI warns that the 781 state-level AI bills introduced this year could seriously hamper American innovation and competitiveness against China. Their proposal extends beyond regulatory protection, calling for infrastructure investment, copyright reform, and expanded access to government datasets for AI development. Notably, they highlighted China's "unfettered access to data," suggesting the AI race could be "effectively over" without fair use copyright protections in the U.S. In a controversial move, OpenAI also pushed for bans on models like DeepSeek, citing security risks and labeling the lab as "state-controlled." The timing of this regulatory push has raised eyebrows, coming amid criticism over closed-source models and ongoing copyright disputes, suggesting OpenAI's regulatory ambitions may now rival its technical ones. Moving to technical innovations, Cohere has unveiled Command A, an enterprise-focused AI model that delivers impressive performance with remarkable efficiency. What stands out is Command A's ability to match or exceed the capabilities of giants like GPT-4o and DeepSeek-V3 while running on just two GPUs. The model achieves 156 tokens per second, operating 1.75 times faster than GPT-4o and 2.4 times faster than DeepSeek-V3. Beyond raw speed, Command A offers a substantial 256k context window and supports 23 languages, making it versatile for global enterprises. The model will integrate with Cohere's North platform, enabling businesses to deploy AI agents that connect securely with internal databases. While much of the industry focuses on pushing benchmark scores higher, Cohere's efficiency-first approach may prove particularly appealing to enterprise customers. The ability to run competitive AI capabilities on minimal hardware not only reduces costs but also makes private deployments more practical for security-conscious organizations. Google is taking personalization to the next level with new features for its Gemini AI assistant. The company is now allowing Gemini to access users' Search history to deliver more contextually aware and tailored responses. This experimental feature leverages the Gemini 2.0 Flash Thinking model to identify when personal data could enhance interactions. Google plans to expand beyond search history, eventually incorporating data from other services like Google Photos and YouTube to further personalize the AI experience. The company is emphasizing user control with opt-in permissions and the ability to disconnect history access at any time, with the feature limited to users over 18. Free users are also gaining access to Gems (custom chatbots) and improved Deep Research capabilities that were previously exclusive to Advanced subscribers. This move represents Google strategically leveraging its vast ecosystem of user data, while carefully balancing personalization benefits against privacy concerns. In model releases news, several notable AI tools are making headlines today. Google's Gemma 3 introduces a multimodal, multilingual model family with 128k context window. Gemini 2.0 Flash experimental version now supports direct image creation and editing within text conversations. Alibaba has released R1-Omni, an open-source multimodal reasoning model with emotional recognition capabilities. Meanw