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Send us a text Welcome to the cozy corner of the tech world where ones and zeros mingle with casual chit-chat. Datatopics Unplugged is your go-to spot for relaxed discussions around tech, news, data, and society. Dive into conversations that should flow as smoothly as your morning coffee (but don't), where industry insights meet laid-back banter. Whether you're a data aficionado or just someone curious about the digital age, pull up a chair, relax, and let's dive into episode #36 titled "Altman's Chips, Mojo Gets Fast and TUIs", featuring Nemanja Radojkovic, an MLOps Lead and Educator, as our special guest. In this episode, we explore a variety of cutting-edge topics: Text-based User Interfaces (TUIs) Rediscovered: Delving into the resurgence of TUIs with Ratatui and gping. Are we witnessing a TUI renaissance? Ratatui | gpingThe Surprising Length of ChatGPT's System Prompt: Unpacking the implications of a 1700 token system prompt. Is there more than meets the eye? Reddit discussionMojo Outpaces Rust in DNA Sequence Parsing: A closer look at how Mojo outperforms Rust by 50% in benchmarks. Is Mojo the new king? Modular's blog postSam Altman's Vision for the Future of Chips and AI: Examining Altman's ambitious plan to reshape the business of chips and AI with trillions of dollars. WSJ article | Reuters on Microsoft's AI chipsThe Real Challenge in Generating Code: Discussing the misconception that generating code is the hard part, with insights into the complexities of software engineering beyond code generation. Nick Scialli's blog Follow Nemanja on LinkedIn and check out his courses.  Intro music courtesy of fesliyanstudios.com

Today many of us are familiar with foundational models such as LLM/ChatGPT. However, there are many more enterprise foundational models that can be rapidly deployed, trained and applied to enterprise use cases. This approach dramatically increases the performance of AI/ML models in production, but also gives AI teams rapid roadmaps for efficiency and delivering value to the business. Databricks provides the ideal toolset to enable this approach.

In this session, we will provide a logically overview of foundational models available today, demonstrate a real-world use case, and provide a business framework for data scientists and business leaders to collaborate to rapidly deploy these use cases.

Talk by: Nick King

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksin

Summary A lot of the work that goes into data engineering is trying to make sense of the "data exhaust" from other applications and services. There is an undeniable amount of value and utility in that information, but it also introduces significant cost and time requirements. In this episode Nick King discusses how you can be intentional about data creation in your applications and services to reduce the friction and errors involved in building data products and ML applications. He also describes the considerations involved in bringing behavioral data into your systems, and the ways that he and the rest of the Snowplow team are working to make that an easy addition to your platforms.

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