#78 - Gen AI, E-commerce, Data&Analytics and LLMs with Peter Gostev
🎙️ Who is Peter Gostev?
Peter Gostev is the Head of AI at Moonpig, specializing in generative AI and its transformative applications in e-commerce. With a strong background in structured problem-solving and data analytics, Peter emphasizes the importance of collaboration and rapid prototyping to drive innovation in AI projects.
💡 In this episode...
... we explore Peter's journey in the AI landscape, discussing the balance between delivering immediate value and fostering innovative experimentation. He shares insights on the distinctions between classical and generative AI, highlighting their respective use cases in structured and unstructured data. Peter elaborates on how generative AI can enhance data quality and operational efficiency, particularly in customer service through automation and insights extraction.
The conversation also addresses the challenges of integrating AI into software development, advocating for specialized teams to effectively manage new technologies. Peter encourages continuous learning and experimentation in AI, urging listeners to engage with emerging tools and models to drive innovation in their own practices.
⏳ Chapters
00:00:00 - Introduction
00:01:15 - Excitement about AI Initiatives
00:05:12 - Experience in Structured Problem Solving
00:08:10 - Building a Data Analytics Team
00:11:05 - Innovation in AI Projects
00:14:45 - Use Cases for Classical vs. Generative AI
00:16:12 - Enriching Data with Generative AI
00:14:46 - Software Development with AI Capabilities
00:18:05 - Specialization in AI Technologies
00:20:03 - Use Cases for Unstructured Data
00:28:14 - Agentic Systems in Software
00:29:21 - Challenges of Automation in Customer Service
00:33:13 - Use Cases for AI in Customer Service
00:34:58 - UI Innovation
00:35:22 - Voice Interaction in E-commerce
00:37:28 - Consumer Behavior and AI
00:39:14 - Historical Context of Technological Adoption
00:42:34 - Learning and Adapting to New AI Models
00:43:25 - OpenAI and Other AI Models
00:47:53 - AI Model Benchmarks and Evaluation
00:48:31 - Superficiality vs. Depth in AI Responses
00:51:05 - Inbuilt Memory and User Interaction
01:00:13 - Fine Tuning AI Models
00:52:02 - Jailbreaking AI Models
00:56:25 - AI Safety and Ethical Concerns
01:00:13 - Infrastructure and Scaling Challenges
01:04:12 - Evaluation Frameworks for AI Models
Peter Gostev: / peter-gostev
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