KeywordsAI, video analytics, security, Vault AI, incident detection, privacy, technology, company culture, future of AI, Igor OlteanuSummaryIn this episode, Igor Olteanu, co-founder of Vault AI, discusses the transformative impact of AI-powered video analytics on physical security. He shares his journey from military service to tech innovation, the technology behind Vault AI's solutions, and the importance of real-time incident detection. Igor addresses privacy concerns, highlights the effectiveness of their technology, and shares notable success stories. He also reflects on the cultural insights gained from his time at Google and how they influence the company culture at Vault AI. Finally, Igor offers his thoughts on the future of AI in security and encourages listeners to embrace innovation.TakeawaysIgor transitioned from military to tech due to a passion for innovation.Vault AI focuses on real-time incident detection in educational spaces.The technology uses geolocation and 3D mappi

SummaryIn this episode, Philippe Trounev and Grant McCracken discuss the evolving landscape of cybersecurity, particularly focusing on the role of agentics and AI in enhancing security measures. They explore the implications of new attack vectors like prompt injection, the potential for agent-to-agent attacks, and the innovative approach of agentic pen testing. Grant shares insights on how AI can improve the efficiency and effectiveness of security testing while emphasizing the importance of foundational cybersecurity practices. The conversation highlights the balance between leveraging advanced technologies and maintaining robust security protocols.TakeawaysCybersecurity is evolving with the introduction of agentics.Fundamentals of cybersecurity remain crucial despite new technologies.68% of data breaches originate from human error.Prompt injection is a significant new attack vector.AI can identify existing vulnerabilities but not create new ones.Agentic pen testing offers continuous,

KeywordsAI, drug discovery, Pauling.AI, language models, FDA approvals, automation, inhibitors, in silico experiments, agentic prompts, healthcareSummaryIn this conversation, Javier Tordable from Pauling.AI discusses the innovative approach to drug discovery using AI and language models. He explains the mission behind the company, the challenges of FDA approvals, and the automation of literature reviews and simulations. The discussion also covers the importance of inhibitors in drug discovery, the differences between in silico and wet lab experiments, and the need for adaptability in AI models. Tordable emphasizes the significance of the mission in improving healthcare and the potential for partnerships in the drug discovery process.TakeawaysPauling.AI aims to shorten drug discovery time significantly.AI-generated drugs follow the same FDA approval process as traditional drugs.Language models excel at reviewing and summarizing prior research.Automation of initial simulations can save w

keywordsAI agents, enterprise implementation, pharmaceutical sector, SAP, ChatGPT, employee training, AI adoption, technology consulting, Infosys, automationsummaryIn this conversation, Philippe Trounev interviews Patrick Rayes, a senior principal at Infosys Consulting, about the implementation of AI agents in enterprise settings, particularly in the pharmaceutical sector. They discuss the challenges faced during AI adoption, the importance of human intervention, and the approval processes required in regulated industries. Patrick shares insights on employee training and the top-down approach necessary for successful AI integration, as well as managing expectations and misconceptions about AI capabilities.takeawaysAI implementation in enterprises requires a top-down approach.Human intervention is still necessary in AI processes.Approval processes in regulated industries are crucial for AI adoption.Employee training and education are key to successful AI integration.AI agents can simpli

In this episode of What About AI Agents, host Philippe Trounev sits down with Sofiya Eremenko, founder of the agency Aimly, to discuss the practical, and sometimes surprising, reality of implementing AI at scale. Sofiya shares her hard-earned insights from working in the vibrant but complex GCC (Gulf Cooperation Council) region. She dives into her own "failure experience" with a client-facing AI agent that was meant to automate sales follow-ups. The key lesson? Cultural nuances and different dialects, like those found across the Arab world, are too complex for current AI models to handle effectively. Sofiya learned that a polite "Insha'Allah" from a client doesn't mean a follow-up is necessary—it can be a subtle "no." Instead of a full-automation "autopilot," Sofiya’s team found success by building an internal AI "copilot." This agent acts as a powerful knowledge base, helping sales managers quickly get complex product detai