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AI Daily — July 31, 2026

2026-07-31

deepmind.google

Gemini Robotics ER 2: powering robotics with video understanding, task orchestration, and multi-robot collaboration

Google DeepMind released Gemini Robotics ER 2, a new model targeting physical robot applications with significant advances in video understanding, tool/API orchestration, and coordinated multi-robot collaboration. The release positions Gemini as a backbone for robot reasoning and task planning rather than just perception. This is a notable step toward embodied AI systems that can handle complex, real-world task sequences across multiple robot agents.

openai.com

Advancing the price-performance frontier with GPT-5.6

OpenAI introduced GPT-5.6 with two tiers—Luna and Terra—at reduced pricing aimed at enterprise-scale AI workflow deployment. The announcement signals continued model efficiency gains that lower the cost barrier for high-throughput production use cases. Specific pricing details and benchmark comparisons were shared to help enterprises evaluate deployment economics.

www.anthropic.com

Investigating three real-world incidents in our cybersecurity evaluations

Anthropic published a post-mortem analyzing three real-world incidents surfaced through its cybersecurity evaluation program, providing transparency into how Claude models behaved in adversarial or sensitive security contexts. The write-up details what went wrong, how evaluations detected the issues, and what mitigations were applied. This kind of incident disclosure is relatively rare among major labs and sets a precedent for operational safety transparency.

www.technologyreview.com

A fundamental flaw leaves LLMs strikingly vulnerable to attack

Researchers presented at ICML 2026 argue that LLMs are structurally incapable of being made fully secure against adversarial attacks due to a fundamental property of how they process inputs. The paper claims this is not a fixable engineering problem but an inherent limitation of the architecture, with significant implications for safety-critical deployments. The work adds formal weight to ongoing debates about whether alignment and hardening techniques can ever provide reliable security guarantees.