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DataTales.AI

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by Serop Baghdadlian

5.0(12 reviews)

19 episodes

Updated Daily

Accepts GuestsHas SponsorsLocation 🇩🇪

Podcast Authority

Beta

FairBased on show quality, social media presence, reviews, charts, and more

Quality68

Social0

YouTube76

Engagement51

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Podcast Overview

🎙️ Berlin Founders Hub Podcast 🌍 Welcome to the go-to podcast for Berlin’s most ambitious founders and creators and those building from anywhere! Hosted by the Berlin Founders Hub, we dive deep into interesting conversations with entrepreneurs, investors, and innovators inside and outside Berlin. 🚀 Real stories, honest challenges, and lessons from the front lines of startups. Whether you're launching your first venture or scaling your next big idea, this podcast is your backstage pass to the minds shaping the future. 📍Brought to you by Berlin’s dynamic founder community – where cowor

Language

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Publishing Since

7/26/2024

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🇺🇸 Charts #3

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Apple 142

Spotify 827

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Podcast Authority

Beta

FairBased on show quality, social media presence, reviews, charts, and more

Quality68

Social0

YouTube76

Engagement51

Learn more

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excellent

Episode Length

42 minutes

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Every 12 days

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Recent Episodes

March 14, 2025

#19 Paul Iusztin: The Truth About LLMOps and Building Real AI Systems

SummaryThis conversation explores the rapid evolution of AI, the complexities of AI roles, the importance of MLOps in deployment, and the challenges faced in implementing AI projects. The speakers share their personal journeys in AI engineering, discuss the balance between custom models and APIs, and emphasize the need for effective data retrieval methods in AI applications. In this conversation, the speakers delve into the complexities of AI, particularly in the context of MLOps and generative AI. They discuss the challenges of ambiguity in AI queries, the evolution of best practices in MLOps, and the importance of evaluation in AI models. The conversation also touches on the transition to content creation, the European AI landscape, and predictions for the future of AI, including advancements in robotics and genomics. Chapters00:00 Coming Up03:07 The Journey into AI Engineering05:55 The Complexity of AI Roles08:56 Custom Models vs. APIs in AI11:52 The Role of MLOps in AI Deployment15:00 Challenges in AI Project Implementation18:11 Building Production-Ready AI Systems20:49 Integrating Semantic Search in AI Applications28:19 Navigating Ambiguity in AI Queries30:37 The Evolution of MLOps in the Age of Gen AI32:39 The Challenges of Evaluation in AI Models35:41 Evaluating Non-Deterministic AI Systems38:58 Transitioning to Full-Time Content Creation41:35 The European AI Landscape and Data Security44:14 Staying Updated in a Rapidly Evolving Field48:15 Predictions for the Future of AI TakeawaysAI is evolving rapidly, making it challenging to keep up.Europe has a strong advantage in data security for AI.The journey into AI can be overwhelming due to its complexity.Custom models may be necessary for specific tasks to reduce costs.MLOps is crucial for deploying AI systems effectively.Many AI projects fail due to unrealistic expectations and lack of resources.Building production-ready AI systems requires careful planning and organization.Semantic search can enhance data retrieval in AI applications.Understanding user intent is key to effective AI solutions.Collaboration and communication are essential in AI project success. Navigating ambiguity in AI queries is challenging but essential.MLOps principles are being overlooked in the rush of Gen AI.Evaluation of AI models is crucial and often neglected.Non-deterministic AI systems require careful evaluation.Transitioning to content creation can lead to a disconnect from industry practices.The European AI landscape is rich with talent and innovation.Data security is a competitive advantage for European companies.Staying updated in AI requires a strategic approach to information consumption.Robotics and genomics are poised to be the next big advancements in AI.Trusting oneself to learn and adapt is crucial in the evolving AI landscape. Contactlinkedin.com/in/serop-baghdadlian<a href="http://linkedin.com/in/pauliusztin">linkedin.com/in/pauliusztin</a> #DataTales #DataScience #AIEngineering #MLOps #GenerativeAI

January 28, 2025

#18 Ceyhun Derinbogaz: Building a 1M User AI SaaS [Success Story]

Summary In this conversation, Serop Baghdadlian and Ceyhun (Jay) discuss the challenges and rewards of entrepreneurship, particularly in the AI sector. They explore the journey of TextCortex, its innovative solutions for knowledge management, and the importance of compliance in AI development. The discussion also touches on the future of workflow automation and the integration of AI features into existing systems. They also discuss the evolution of AI and automation, focusing on its applications in various industries, including legal and tax sectors. They explore the challenges of trust and accuracy in AI solutions, the impact of AI on software development, and the competitive landscape of AI startups. Jay shares his entrepreneurial journey, highlighting the importance of understanding industry-specific problems to create valuable solutions. The discussion also touches on the future of user interfaces and the potential for a universal API that could streamline interactions with technology. Chapters 00:00 Coming Up 00:44 Introduction to TextCortex and AI's Potential 03:01 The Evolution of TextCortex and Its Growth 06:00 Setting Up TextCortex for Enterprises 08:57 Integrations and Automation with TextCortex 12:08 Compliance and Challenges in AI Development 14:49 Future of AI and Workflow Automation 17:49 The Role of AI in Software Development 20:45 Navigating Competition in the AI Space 23:47 Predictions for the Future of AI Interfaces Takeaways TextCortex AI is a knowledge answer engine that simplifies data access. The evolution of TextCortex has been driven by organic growth and user feedback. Setting up TextCortex for enterprises involves understanding their systems and data sources. Integrations with platforms like make.com enhance automation capabilities. Compliance and security are significant challenges in AI development, especially in Europe. The future of AI includes more automation and workflow solutions for businesses. AI tools are becoming essential for software development, reducing the need for traditional coding. Competition in the AI space is intense, with many companies offering similar solutions. The interface of software applications is expected to evolve towards minimalism and voice interaction. AI needs to be equipped with the necessary tools to operate effectively in various environments. Contacts <a href="http://linkedin.com/in/ceyhunderinbogaz">linkedin.com/in/ceyhunderinbogaz</a> <a href="http://linkedin.com/in/serop-baghdadlian">linkedin.com/in/serop-baghdadlian</a> #DataTales #DataScience #WorkflowAutomation #AIEntrepreneurship #TechStartups

January 18, 2025

#17 Maria Vechtomova: How to Correctly Navigate the AI Space

Summary In this conversation, Serop Baghdadlian and Maria discuss the evolution of MLOps and AI technologies, and the importance of fundamentals in AI engineering. They explore the complexities of LLM Ops compared to traditional MLOps, the shift in evaluation standards for AI models, and the necessity of a data scientist's mindset when approaching AI projects. In this conversation, Serop Baghdadlian and Maria discuss the complexities and unpredictability of machine learning models, the evolution of MLOps, and the importance of focusing on fundamentals. They explore the challenges of reproducibility in machine learning environments, the journey of creating effective courses, and the significance of teaching and sharing knowledge in the tech community. Maria shares her experience in writing a book on MLOps with Databricks and emphasizes the need for simplicity in solutions. Chapters 00:00 Coming Up 05:10 Navigating Complexity in AI Systems 09:50 Evaluating AI Models: The Shift in Standards 15:03 The Role of Human Oversight in AI 19:49 Building Reliable AI Systems 24:54 Teaching and Sharing Knowledge in AI 29:58 The Future of AI and Continuous Learning Takeaways Fundamentals in AI and MLOps are crucial and don't change rapidly. Complex systems can lead to unreliability and financial loss. MLOps focuses on principles rather than just tools. Human oversight is essential in evaluating AI outputs. Simplicity should be prioritized in building AI systems. Teaching and sharing knowledge is vital for community growth. Continuous learning is necessary due to the fast-paced nature of AI. Evaluation standards for AI models have shifted towards gut feelings. Collaboration and mentorship are important in the AI field. Curiosity drives learning and understanding in AI. Contacts <a href="http://linkedin.com/in/maria-vechtomova" rel="ugc noopener noreferrer" target="_blank">linkedin.com/in/maria-vechtomova</a> linkedin.com/in/serop-baghdadlian #DataTales #DataScience #MLOps #AIEngineering #TechPodcast

19 total episodes available

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Frequently asked questions

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What is DataTales.AI?: 🎙️ Berlin Founders Hub Podcast 🌍 Welcome to the go-to podcast for Berlin’s most ambitious founders and creators and those building from anywhere!

Hosted by the Berlin Founders Hub, we dive deep into interesting conversations with entrepreneurs, investors, and innovators inside and outside Berlin.

🚀 Real stories, honest challenges, and lessons from the front lines of startups.

Whether you're launching your first venture or scaling your next big idea, this podcast is your backstage pass to the minds shaping the future.

📍Brought to you by Berlin’s dynamic founder community – where cowor
How often does this podcast release new episodes?: This podcast updates daily.
Where can I listen to this podcast?: This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
Does this podcast accept guests?: No, this podcast does not typically feature guests.

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