In this discussion, Erik Bernhardsson, CEO and co-founder of Modal Labs, dives into the intricacies of cloud computing, emphasizing the competitive landscape with giants like Snowflake and AWS. He shares insights on the GPU shortage and its implications for AI startups. Erik boldly critiques the future role of data engineers, questioning its necessity while spotlighting the rise of analytics engineers. The conversation also touches on the impact of generative AI and the democratization of software development, showcasing a landscape ripe with innovation.
Erik Bernhardsson emphasizes the growing importance of GPUs in AI, highlighting their high costs and the need for efficient resource management across cloud platforms.
The discussion suggests that as technology advances, the role of data engineers may evolve towards more strategic functions, potentially reducing the demand for traditional data engineering jobs.
Deep dives
The Evolution of Modal
The speaker discusses the growth and development of Modal, which started as a general-purpose platform for cloud computing, specifically focused on data, AI, and machine learning use cases. Over the years, it has found significant traction as a solution for running large-scale applications involving audio, video, images, and various models in biotech. The ease of use is emphasized through its Python SDK, which simplifies code deployment without needing extensive knowledge of scaling or provisioning. This accessibility positions Modal as a competitive alternative to other cloud services, serving a specific niche for data-driven teams.
Addressing GPU Utilization Challenges
The discussion highlights the crucial role of GPUs in AI and data processing, particularly their high costs and the necessity of running them at maximum capacity to achieve economic efficiency. As demand for GPUs outstrips supply, the need for integrating different cloud vendors and regions arises to ensure adequate resource availability. The innovation within Modal includes techniques to optimize resource allocation dynamically based on real-time pricing and availability data, allowing users to maximize their computing capabilities without excess expenditure. This adaptability makes Modal an appealing solution for companies facing increasing pressure to manage costs while leveraging potent compute resources.
The Future of Data Engineering
The need for data engineering roles is examined, with the speaker expressing a belief that traditional data engineering might become less relevant as technology evolves. While still essential, these roles may see a shift with the rise of more automated systems that simplify data management and access. By drawing parallels with other changing job titles in tech, the speaker suggests that while data engineering is necessary now, advancements will likely lead to fewer human resources needed for this field, as tools become more capable of handling complex tasks independently. This evolution hints at a future where data professionals will transition towards more strategic roles focused on business needs rather than technical manipulation.
AI's Impact on Software Engineering
The conversation covers the transformative impact of AI on the software engineering landscape, predicting that AI tools are likely to improve productivity among engineers. While concerns exist about over-reliance on AI, the belief remains that these advancements will foster more innovative solutions, allowing software engineers to write better and more efficient code. There's also an optimistic view that as AI tools become more accessible, they will enable a wider range of individuals to engage in software development, ultimately growing the field. The future of software engineering may involve a more integrated approach where engineers harness AI to focus on higher-level problem-solving and application development.
Erik Bernhardsson, the CEO and co-founder of Modal Labs, joins Tristan to talk about Gen AI, the lack of GPUs, the future of cloud computing, and egress fees. They also discuss whether the job title of data engineer is something we should want more or less of in the future. Erik’s not afraid of a spicy take, so this is a fun one.
For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
The Analytics Engineering Podcast is sponsored by dbt Labs.
Get the Snipd podcast app
Unlock the knowledge in podcasts with the podcast player of the future.
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode
Save any moment
Hear something you like? Tap your headphones to save it with AI-generated key takeaways
Share & Export
Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode