So What About AI Agents

• EP 38 - The Role of AI in Drug Discovery - Javier Tordable from Pauling.AI

  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 weeks of work.Most drugs developed are inhibitors, which block specific biological processes.In silico experiments are a focus for Pauling.AI, differentiating from wet lab experiments.The risk of hallucinations in AI requires careful management in drug discovery.Adapting to rapid changes in AI models is crucial for success.Human-initiated interactions guide the AI agents' processes.The mission of drug discovery is to improve lives, not just profit.Sound bites"Most drugs are inhibitors.""We focus on in silico experiments.""Human-initiated interaction is key."Chapters00:00 Introduction to Agentic Drug Discovery02:15 The Role of AI in Drug Discovery04:55 Current State of AI-Driven Drug Development07:25 Challenges in Drug Discovery and AI Integration10:04 Optimizing AI Agents for Drug Discovery12:53 Human-AI Collaboration in Drug Discovery15:39 Future of AI in Drug Discovery18:13 Insights and Best Practices for Building AI Agents21:10 The Economics of Drug Discovery23:41 Conclusion and Future Directions

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• AI News - Sep 7 - Sep 14

  KeywordsAI news, investment, governance, AI companions, market dynamics, technology trends, AI deployment, valuations, regulatory landscape, business intelligenceSummaryIn this episode of So What About AI, Philippe Trounev discusses the latest developments in AI news, focusing on significant investments, the challenges of AI deployment, the rise of AI companions, and the shifting focus of venture capitalists from artificial general intelligence (AGI) to return on investment (ROI). The conversation highlights the complexities of AI governance, the societal implications of AI companionship, and the regulatory landscape affecting AI technologies.TakeawaysCognition AI raised $400 million at a $10.2 billion valuation.95% of enterprise AI pilots fail, indicating a significant challenge in deployment.97% of AI deployments globally lack proper governance.AI companions are becoming a concern for governments due to their increasing prevalence.Venture capitalists are shifting their focus from AGI to ROI, emphasizing profitability.Companies are increasingly buying AI solutions rather than building them in-house.The AI market is experiencing a peak hype phase, with significant investments flowing in.OpenAI's job platform aims to teach humans to work alongside AI.Mistral's $1.3 billion investment reflects the growing intersection of hardware and AI.The regulatory landscape is becoming more complex, particularly in the EU.Sound bites"OpenAI launches a job platform.""95% of enterprise AI pilots fail.""AI agents are at peak hype."Chapters00:00 AI News Overview04:50 Governance and Regulation in AI09:32 Data Breaches and Security Concerns

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• EP 37 | Navigating AI Implementation in Enterprises - Patrick Rayes

  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 simplify complex workflows and processes.Managing expectations about AI capabilities is essential for stakeholders.The pharmaceutical sector has specific requirements for AI implementation.A centralized interface enhances user experience with AI tools.Consulting firms play a vital role in guiding AI adoption.Companies must adopt AI with the same urgency as the internet.titlesNavigating AI Implementation in EnterprisesThe Role of Human Intervention in AISound Bites"AI is getting big right now.""Human intervention is still required.""AI agents simplify complex processes."Chapters00:00Introduction to AI Agents in Enterprises02:19AI Implementation in Pharmaceuticals and Banking04:43Challenges and Lessons Learned in AI Adoption07:01Human Intervention in AI Processes09:37Real-World Examples of AI Implementation11:02Approval Processes for AI in Regulated Industries12:45Comparing AI Tools: SAP Jewel, ChatGPT, and Gemini15:21Employee Adoption and Training for AI Systems18:03Impact of AI on Workflows and Efficiency20:41Managing Expectations Around AI Capabilities23:24Consulting Strategies for AI Transformation26:10Safeguarding Proprietary Knowledge in AI28:56Key Takeaways for Successful AI Implementation

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• EP 36 | The Future of User Experience in an AI-Driven World | Ginny Delaiter

  In this episode, Ginny Delaiter, founder and CEO of BDS Digital Agency, discusses the intersection of user experience (UX) and artificial intelligence (AI) in marketing. She emphasizes the importance of integrating AI into UX design while maintaining a human-centered approach. The conversation explores how AI can enhance user experience, the need for accessibility in AI-driven designs, and the evolving landscape of UI/UX as AI becomes more prevalent. Ginny shares insights on best practices for adapting websites for AI agents and the importance of educating users about new technologies.takeawaysUser experience should be the center of the product.AI gives us open doors to do faster work and better work.We need a human interloop in the process of UX design.Blocking the agent means losing traffic and visibility.Agents are smarter than traditional search engines like Google.UX strategies need to be done by humans, not just AI.Don't say no and refuse everything new; adapt to change.A good website should be understood by both people and AI.UX is all about education and guiding users through the experience.We need to think about different personas in UX design.

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• EP 35 | With Sofiya Eremenko | Is a "Copilot" AI Better Than an "Autopilot" One?

  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 details without needing to consult with different teams. This system reduced the time to respond to a client from an entire day down to a single hour, proving that the most effective AI solutions often support human work rather than replace it. Tune in to hear more of Sofiya’s insights, including her advice on selling AI solutions by focusing on the "wow effect" of simple use cases and the critical importance of extensive testing to safeguard against unexpected outcomes. Want to be a guest on What About AI Agents? Send Philippe Trounev a message on PodMatch, here: https://podmatch.com/hostdetailpreview/17345406908669558d25580e0#AI #AIAgents #SoftwareDevelopment #Innovation #HR #Technology #Podcast #Enterprise #Podmatch

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