According to Andrew Ng, a new course on the Agent Communication Protocol (ACP) enables developers to build AI agents that can communicate and collaborate across different frameworks. The course, developed in partnership with IBM Research's BeeAI and taught by AI Research Engineer Sandi Besen, focuses on practical skills for implementing ACP in real-world scenarios. This training addresses a growing need for interoperability in multi-agent systems and presents significant business opportunities for organizations looking to integrate diverse AI technologies seamlessly. Source: Andrew Ng on Twitter.

According to ElevenLabs on Twitter, their Conversational AI platform now allows businesses to build agents that can book appointments, summarize content, search for information, or automate various workflows using natural language. The platform provides practical business applications, such as streamlining customer service, automating repetitive administrative tasks, and enabling instant knowledge retrieval. These AI-powered agents can be easily integrated via ElevenLabs’ API and documentation, enabling companies to deploy scalable automation solutions that reduce operational costs and enhance user experience (Source: twitter.com/elevenlabsio, elevenlabs.io/docs/conversational).

According to Stanford AI Lab, the introduction of BountyBench marks a significant advancement in the cybersecurity sector by providing the first framework designed to systematically capture both offensive and defensive cyber-capabilities of AI agents in real-world environments (source: Stanford AI Lab, 2025). This tool enables security professionals and businesses to evaluate the practical impact of autonomous AI on cyberattack and defense strategies, offering actionable insights for improving resilience and threat detection. BountyBench's approach opens new business opportunities in cybersecurity solutions, risk assessment, and the development of adaptive AI-driven security protocols.

According to Google DeepMind on Twitter, experts @_rebecca_paul and @maxjaderberg from Isomorphic Labs discussed how AI agents are revolutionizing drug discovery by enabling human experts to efficiently explore vast molecular spaces. Their conversation with @fryrsquared emphasized that AI does not replace human intuition but augments the ability to identify promising compounds, drastically reducing time and cost in early-stage pharmaceutical research (source: Google DeepMind, June 11, 2025). The integration of AI-driven molecular exploration opens significant business opportunities for biotech firms and pharmaceutical companies seeking to accelerate R&D pipelines and gain competitive advantages in drug development.

According to DeepLearning.AI, OpenAI has launched Codex, an advanced AI system that leverages multiple AI agents to write, test, and debug code in parallel, effectively simulating a team of virtual software engineers. Codex is now available in preview for ChatGPT Pro, Enterprise, and Team users, allowing seamless integration with code repositories. This development enables businesses to accelerate software development cycles, automate routine programming tasks, and improve code quality at scale. The AI-driven approach offers significant business opportunities by reducing engineering costs and increasing productivity, especially for organizations seeking to modernize legacy systems or build new AI-powered applications (source: DeepLearning.AI, May 26, 2025).