641: Data Science Trends for 2023 — with Sadie St. Lawrence

AI Models

Sadie St. Lawrence highlights the rise of multimodal AI models, predicting their significant impact in 2023. She envisions a future where these models, like ChatGPT and DALL-E, evolve to create engaging video content, revolutionizing how we interact with AI 1. Jon Krohn shares his company's experience with GPT-3, illustrating how AI advancements are streamlining processes and enhancing productivity 2. He emphasizes the accessibility of multimodal models as a major trend that will shape the data science landscape in the coming year 3.

It's really cool times. And, you know, not only obviously, like chat GPT is taking over the Internet right now, but even the lens app took over the Internet.

--- Sadie St. Lawrence

These developments indicate a transformative period for AI, with potential applications spanning various industries.

   

Data Mesh

The concept of data mesh is gaining traction as a solution to manage and utilize vast amounts of data efficiently. Sadie St. Lawrence explains that data mesh enables decentralized data management, allowing different departments within an organization to access and utilize data independently while maintaining privacy standards 4. Jon Krohn5.

The whole technology is to enable those business functions to be able to share the data.

--- Sadie St. Lawrence

This approach aims to empower businesses by offloading data responsibilities from centralized teams, fostering innovation and efficiency.

   

Sustainability

Environmental sustainability in data science is becoming increasingly crucial as AI models grow in complexity. Jon Krohn and Sadie St. Lawrence discuss the need for sustainable practices, such as using less data and optimizing model efficiency to reduce energy consumption 6. They highlight initiatives like Tesla's Dojo supercomputer, which aims to enhance processing power while minimizing environmental impact 3.

As practitioners in this space, you'll be pushed to use less data, make better models.

--- Sadie St. Lawrence

These efforts reflect a growing awareness of the environmental implications of data science, urging the industry to adopt greener technologies and practices.