Google has announced a series of new AI advancements focused on privacy, security and real world functionality, unveiling an updated Private AI Compute framework and introducing SIMA 2, its next generation agentic system designed to reason, learn and interact inside virtual environments. These announcements reflect the company’s push to combine its Gemini capabilities with safer and more structured deployment models at a time when global interest in consumer and enterprise AI continues to grow.
The updated Private AI Compute framework is aimed at delivering Gemini features with on device level privacy controls. According to Google, the system ensures that sensitive user information does not leave the device without explicit permission. The company stated that its goal is to offer advanced AI assistance without requiring full cloud level data access. The approach is expected to support compliance requirements for regulated sectors and provide a more secure environment for enterprise applications.
Google said the Private AI Compute model is designed to process tasks that involve confidential user inputs in a secure enclave. These enclaves isolate sensitive data from general cloud systems and allow Gemini to perform reasoning tasks with restricted access protocols. The company indicated that this structure will give developers more control while improving transparency around how user information is handled.
At the same time, Google DeepMind introduced SIMA 2, an upgraded version of its generalist agent that can interact in 3D virtual environments. SIMA 2 has been trained using Gemini models and is designed to operate with natural language instructions, interpret user intent and navigate complex virtual tasks. DeepMind researchers described SIMA 2 as a system that can learn through interaction, allowing it to adapt to new virtual scenarios and perform actions across multiple digital platforms.
Google reported that SIMA 2 can work across different virtual worlds, including simulation environments created for research and gaming engines. During testing, the agent demonstrated the ability to reason through objectives, take step by step actions and refine its behaviour based on feedback. SIMA 2 also incorporates tools that allow it to generalise learnings across environments, a capability that Google claims moves closer to real world action reasoning.
Industry analysts note that these developments reflect the growing focus on agentic AI systems, which are expected to form a major part of next generation digital assistants. These agents are being designed to not only respond to prompts but take actions, complete tasks and operate independently within authorised boundaries. With SIMA 2, Google appears to be accelerating its investment in this area while also ensuring that such systems remain aligned with user safety requirements.
The introduction of Private AI Compute is seen as a response to rising concerns about data privacy as cloud based AI models expand. Government bodies in multiple markets are drafting AI regulations that emphasise transparency, auditability and stronger protection of sensitive information. Google’s framework places emphasis on user control by offering a blend of on device processing and cloud based AI services. This hybrid structure could help enterprises adopt AI tools while meeting corporate governance standards.
Google also highlighted that Private AI Compute can support organisations that handle classified information, internal documentation or large scale proprietary datasets. By processing key data within a secured environment, companies can engage with Gemini capabilities while reducing exposure to external networks. The system is expected to be integrated into Google Cloud services, giving enterprise clients more flexibility in AI deployment.
SIMA 2, which operates in virtual environments rather than real world robotics settings, is expected to be used first for training and research purposes. The agent’s ability to understand complex instructions in natural language could support use cases such as virtual training, gaming, interactive education and simulation based design. Google DeepMind researchers noted that virtual training is an effective first step before agents are introduced into real world tasks where higher precision and safety are required.
The company also stated that SIMA 2 has been trained using diverse virtual tasks that build its capacity for flexible reasoning. This includes object manipulation, navigation, multi step problem solving and learning by observing human demonstrations. The system can adapt to environments that were not part of its initial training, which researchers said is a notable improvement over earlier agentic systems that struggled with scenario transfer.
Industry experts believe that the convergence of privacy oriented AI frameworks and agent based systems indicates the next phase of AI evolution. Companies are developing more autonomous models while also meeting regulatory expectations around safe use. Google’s announcement signals its intention to strengthen its leadership across both enterprise AI and general purpose AI agents.
The developments come at a time when the global AI market is moving toward sophisticated automation assistants capable of managing workflows, completing digital tasks and offering predictive insights. By combining Gemini reasoning capabilities with secure compute options, Google is attempting to address both the functional and compliance demands of enterprises.
As Google expands its AI research and ecosystem efforts, the Private AI Compute framework and SIMA 2 agent represent steps in integrating intelligence, security and real world practicality. The company is expected to continue refining these systems as demand for privacy preserving and highly capable AI technologies rises across sectors.