Category: AI Leaders Connect Roundtables


  • Navigating Challenges and Best Practices in AI Research and Talent Recruitment

    During a roundtable discussion with AI leaders Alex and Farshad, we gained valuable insights into the challenges and best practices of conducting research at startups, recruiting AI talent, and designing effective interviews. In this blog post, we will highlight the key points discussed by these two experts, shedding light on the nuances and complexities of…

  • Mastering Data Science and ML Interviews: Key Insights from AI Leaders

    In today’s competitive job market, hiring the right candidates for data science and machine learning roles is crucial for the success of any organization. To identify the best fit for these positions, companies need to design effective interview questions that evaluate not only technical skills but also problem-solving abilities, learning aptitude, and cultural fit. The…

  • Accelerating the Data Science Life Cycle

    In this roundtable discussion, Yong and George shared valuable insights on the data science life cycle. This conversation shed light on various stages of the life cycle, challenges faced, and strategies adopted to generate value in their specific use cases. The discussion also touched on resource allocation, the role of platforms, and the potential for…

  • Scaling AI Research: Challenges and Strategies

    Artificial intelligence (AI) research and development are at the forefront of technological advancements, revolutionizing industries and pushing the boundaries of what’s possible.  In a recent conversation, two AI professionals, Alex and Kat, discussed their experiences and challenges in scaling AI-applied research within their organizations. Here, we delve into their insights and approaches. Scaling AI Research…

  • Navigating AI Challenges

    In this AI leaders’ roundtable discussion, participants delved into various facets of AI applied research, encompassing topics such as scaling AI within organizations, deploying deep learning models, data-centric AI, the pros and cons of open source, and model plus data version control.  The insights shared during this dialogue offer valuable perspectives on these key aspects…

  • Navigating the AI Landscape

    This blog post presents a summary of the insightful conversation, highlighting key perspectives shared by the speakers. The discussion touched upon the impact of AI advancements, challenges in AI development, the role of product managers in AI teams, and the balance between networking and day-to-day work. According to Bibhu, there has been a significant increase…

  • Data Science Lifecycle: Streamlining Processes and Generating Value

    In this roundtable discussion, AI leaders shared their experiences and insights on the various stages of the data science lifecycle. From data acquisition to model evaluation, the conversation shed light on key challenges, best practices, and the value-generating aspects of the process. In this blog post, we will summarize the highlights of the discussion and…