Welcome to the Time for AI Podcast, where we engage with leading AI conference speakers to distill their insights into concise episodes. In this episode, I welcomee Philip Keren, Director of Developer Relations at Elastic, to discuss the evolution of search and information retrieval in the age of AI. Philip delves into Elastic's pioneering tools like Elasticsearch and Kibana, explaining how they address search challenges in logs, observability data, and security through effective information retrieval techniques. While the AI buzz brings new attention and investment to search technologies, Philip emphasizes the importance of leveraging traditional keyword search and newer vector search methods to enhance retrieval processes. Join us as we explore the dynamic role AI plays in search, the potential challenges in adopting AI indiscriminately, and practical ways businesses can integrate Elastic's solutions into their workflows. Discover how Elastic continues to innovate and future-proof search solutions in a rapidly evolving tech landscape. You can find Philipp at xeraa.net or on Linkedin. Watch the whole workshop on YouTube.  

In this episode, we talk to Fatima Sumroo (Linkedin), a data engineering and analytics consultant at Argusa, about the impact of generative AI, particularly LLMs, on data-related jobs. Fatima shares insights from a systematic study conducted at Argusa, revealing surprising findings about which tasks are most likely to be augmented or replaced by GenAI. The discussion touches upon the importance of integration, the hype cycle surrounding new technologies, and practical examples of using AI tools like Grammarly and Copilot. Check out Fatimas presentation: Other interesting things mentioned: Tobias Zwingmann - 7 Deadly Sins of AI - Presentation 

This episode features Giulia Solinas (linkedin) (the Al a la Carte Newsletter), an AI and Data Science consultant at CROZ, a Croatian company providing business and technology consulting services. Julia discusses her work at CROZ, focusing on programming solutions that enable LLMs to work with business requests. She also talks about her transition from academia to business, highlighting the bridge between the two and how her academic experience has helped in her current consulting role. The main topic of the episode is Julia's presentation "Unlocking the Power of AI Assistants" at the AI Weekend 2024 Media Festival (part of the Rovinj Conference Weekend Media Festival 2024 ). Julia summarizes the presentation, emphasizing the challenges and considerations of implementing AI assistants in production for organizations. Key discussion points include: Topicality of AI Assistants: The widespread belief that AI will impact businesses and the potential for AI assistants like Copilot to significantly increase productivity. Types of AI Assistants: The difference between general AI for everyone (like Copilot) and customized AI assistants tailored for specific company needs. Challenges of Implementation: Identifying users and their needs. Integrating the AI assistant with existing infrastructure (legacy and non-legacy systems). Ensuring scalability to other departments and use cases. Addressing governance and compliance, particularly GDPR and the EU AI Act. These considerations include data anonymization, masking, location, and usage. An Example Use Case: An AI assistant developed for a large bank's HR department to handle employee requests and save HR personnel time. Looking Ahead to 2025: The prediction that 2025 will be the year of agentic AI. Julia anticipates the increasing complexity of AI systems, with multiple models interacting and integrating with each other. AI Literacy in Organizations: Julia stresses the need for AI literacy across all levels of an organization, from employees to C-level decision-makers, suggesting training and leveraging online resources. This includes fostering trust in AI, facilitating familiarity with AI tools and resources, reducing fear of job displacement, and empowering informed decision-making about AI use cases. Ethical Considerations: The importance of understanding ethical issues related to AI, something that is often overlooked but crucial to consider from both technical and user perspectives. Julia's Current Pet Project: A GitHub repository focused on personal training on InstructLab, a methodology co-developed by Red Hat and IBM for fine-tuning smaller LLMs. This project stems from Julia's enthusiasm for open-source models and their potential for cost-effective and efficient AI solutions in production. Key Takeaways: Implementing AI assistants is a complex process requiring careful planning and consideration of various factors. AI literacy is essential for organizations to maximize the benefits of AI and address potential challenges. Ethical considerations are crucial in AI development and deployment. Open-source models and fine-tuning offer promising avenues for cost-effective and efficient AI solutions.

Jason Schemmel, a marketing expert from Get Social Done, joins us to discuss how AI is revolutionizing the marketing landscape. He shares his insights from a recent AI conference presentation, focusing on practical AI tools and tactics businesses can implement to improve operations, increase sales, and decrease costs. Jason emphasizes the power of AI for research, ideation, and time-saving, highlighting Perplexity AI as a particularly valuable tool. He also discusses the importance of verifying AI-generated content and maintaining authenticity. You can find the slides here. Key Takeaways: AI is rapidly becoming essential for businesses, much like the internet was years ago. AI can be a massive time-saver for tasks like ideation, competitor research, and content creation. Perplexity AI excels as a research tool, sourcing and citing information from across the web. It's crucial to verify AI-generated content and maintain your brand's authentic voice. The future of large language models may involve a single, dominant platform like Google or Apple for AI. Mentioned AI Tools: Perplexity AI: A powerful research tool that sources and cites information from the web. (https://www.perplexity.ai/) Claude: An AI chatbot known for conversational abilities and detailed responses. (https://www.anthropic.com/index/claude) ChatGPT: A versatile large language model used for various tasks, including content generation. (https://chat.openai.com/) Gemini: Google's large language model. (https://blog.google/products/gemini/) Copilot: An AI pair programmer that assists with coding tasks. (https://github.com/features/copilot) Other Mentioned Resources: Get Social Done: Jason Schemmel's marketing agency. (https://getsocialdone.com/) Grow with AI Summit: The conference where Jason presented (https://growwithaisummit.com/free-clone-page) Claude Projects (now called Claude 2.1): A feature in Claude that allows users to upload documents and use them as a knowledge base. Perplexity Spaces: Similar to Claude Projects, this allows users to upload documents for Perplexity to use as a context. (https://www.perplexity.ai/spaces) Connect with Jason Schemmel: Facebook LinkedIn