MLOps.community

In this podcast, Rohit Agarwal, CEO of Portkey.ai, discusses designing for forward compatibility in Gen AI. He explores advancements in generative AI and the importance of a tooling layer. The podcast also covers the evolving landscape of software engineering tools, the ops layer for Janet Away applications, challenges in using open-source models, the technology stack in app production, the importance of an AI gateway, and the challenges of open-sourcing a product.

Anand Das, co-founder and CTO of Bito, discusses the impact of LLMs in tech stack and product development, including their Chrome extension 'explain code'. They explore topics such as optimizing at lower levels, ensuring privacy in non-open source projects with AI language models, and best practices for debugging with coding assistants and learning models.

Faizaan Charania, Product Manager, AI at LinkedIn, discusses his AI product development approach, integrating generative AI, and evaluating AI-driven experiences. He shares wisdom on feedback integration, user trust, and collaboration challenges between product managers and AI teams. The podcast explores push vs pool mechanisms in product development, pros and cons of using open source models in enterprise-level use cases, prompt engineering and iteration, building trust in new interaction patterns, and the shift towards understanding machine learning and natural language models.

Mike Del Balso, CEO of Tecton, and Josh Wills, Angel Investor, discuss the importance of feature stores and platforms for ML applications. They explore challenges in operationalizing data pipelines, integrating offline and online data stores, and templatizing workflows for fraud detection and recommendation systems. The concept of gamification in feature creation is also explored.

Luigi Patruno, VP of Data Science at 2U, Inc, shares insights on managing data products and the challenges that come with it. He discusses effective communication, transitioning from an individual contributor to a data science leader, the importance of discipline and focus in goal-setting, data science leadership and incentives, the value of specific and meaningful positive reinforcement, setting boundaries as a manager, and the importance of solutions and identifying blind spots.

Richa Sachdev, Executive Director- Data Operations and Automation, shares insights on optimizing the end-user experience, understanding business goals and metrics, converting legacy applications, working with data platforms, challenges of integrating different databases, and the role of automation in streamlining processes and improving customer interactions in the reward space.

Ketan Umare, CEO at Union.ai, discusses ML orchestration vs MLOps, prioritizing features for open-source and enterprise projects, challenges of ML orchestration, building a flexible architecture, Unionverse flight and plugin models, challenges of large language models and evaluation.

GetYourGuide's Jean Machado, Meghana Satish, Olivia Houghton, and Theodore Meynard discuss various topics including optimizing marketing for machine learning, building services and pipelines, handling pain points in experimentation, implementing resilience and optimization in the travel industry, preventing regrets and continuing improvements, exploring use cases and building foundations, and evaluating experiments in growth.

Kyle Harrison, General Partner at Contrary, discusses the limitations in language for grasping reality and the dangers of centralizing power in AI, emphasizing the need for improved language model performance. The podcast explores comparisons between TensorFlow and PyTorch, open-source initiatives in AI, and Meta's involvement. They also touch on AI capabilities, the challenges of AI agents, and the impact of blockchain technology.

Sachin Abeywardana, Deep Learning Engineer at Canva AI, shares insights on incorporating AI and ML capabilities, challenges of building CLIP and other language models, balancing work and family life, limitations of transformers in NLP, and trade-offs in deploying features.