Open weights against the API
When is a fine-tuned open model a better fit than a hosted API?
What is the open source ML framework Hermoine
ClaimHermoine is intentionally open enough that users can reshape it to fit their preferred way of working.5:07
MLflow Open Source Framework Hermione Demo
ClaimThe MLflow interface can be used to compare runs, inspect metrics and register a model for use through an API.13:20
Bring Your On-Prem ML Use Cases to Production on Google Cloud using Kubeflow
ClaimChanchal Chatterjee's team created the open-source ML Pipeline Generator to help bring existing models into production on Google Cloud.3:02
The Current MLOps Landscape
Pushed backTimothy Chen and Nathan Benaich disagree with the idea that open source is always required for an MLOps business, while agreeing that it is increasingly advantageous for developer-focused products.43:05
How to Avoid Suffering in MLOps/Data Engineering Role
ClaimAdyen replaced a homegrown scheduling system with open source tools because the old system was supported by only one person and had accumulated limitations.17:41
MLOps Investments
ClaimSarah Catanzaro is a partner at Amplify Partners, an early-stage venture capital firm that primarily invests in technical tools and platforms.2:13
Tour of Upcoming Features on the Hugging Face Model Hub
ClaimJulien Chaumond says the Transformers open-source software has more than 5,000 companies using it in production.5:24
Wikimedia MLOps
Pushed backChris Albon argues that open source is not automatically accessible and that accessibility requires making projects understandable and reproducible.1:00:50
Investing in MLOps
ClaimDavis Treybig says open-source companies should plan how they might eventually monetize even if they do not build paid tiers for several years.33:44
Building the World's First Data Engineering Conference
ClaimOpen-source and commercial businesses have different routes to market and revenue, and founders should understand the difference between them.25:11
Modern Data Science with Vaex
ClaimVaex is an open-source out-of-core DataFrame library that lets users process very large datasets locally without clusters or complex configuration.4:06
Making MLflow
ClaimMLflow was built as an open-source platform for the end-to-end machine-learning lifecycle, using open APIs and supporting many tools.1:18
Solving the Last Mile Problem of Foundation Models with Data-Centric AI
Pushed backAlex argues that the most durable advantage will come from private data, domain-specific knowledge, and last-mile development rather than from closed general-purpose API models.7:54
Want High Performing LLMs? Hint: It Is All About Your Data
Pushed backVikram Chatterji rejects the idea that teams should exclusively prompt or exclusively fine-tune, arguing that the right balance depends on the use case.32:53
Pitfalls and Best Practices: 5 Lessons from LLMs in Production
Pushed backRaza argues against starting with complex chains or agents before testing stronger models, prompt engineering, and fine-tuning, while acknowledging that agents and chains work in some situations.13:38
Build and Customize LLMs in Less than 10 Lines of YAML
Pushed backTravis argued that fine-tuning a smaller model can match or outperform a much larger model for a sufficiently bounded task at lower latency and cost.17:17
Vision Pipelines in Production: Serving & Optimisations
Pushed backBasic generation with more configuration was considered insufficient for the required consistency and control, so fine-tuning was chosen instead.3:31
Fine Tuning Llamas
Pushed backKai Davenport rejects the idea that fine-tuning is always better than retrieval-augmented generation and argues that the two approaches can be combined.4:57
Ghostwriter - AI Writing That Learns From You
Pushed backThe speaker disputes the assumption that autocomplete can be made reliable through system-prompt instructions alone and says fine-tuning was needed.10:08
Alignment is Real
Pushed backDemetrios Brinkmann questioned whether DSPy was too much of a research project to trust in production, while Shiva Bhattacharjee defended using a modified, self-hosted version of it.4:57
I Let An AI Play Pokémon! - Claude plays Pokémon Creator
Pushed backFine-tuning is not usually the best first step; prompting should generally be pushed further before fine-tuning is considered.13:31
We're All Finetuning Incorrectly
Pushed backThe idea that prompting or prompt fine-tuning is inherently undesirable was softened; prompting is useful before a system reaches its ceiling.14:30
Building Out GPU Clouds
Pushed backDemetrios Brinkmann noted that fine-tuning is often criticized as difficult and potentially harmful when done incorrectly, while Mohan Atreya argued that it can become a zero-code workflow.45:57
Office Hours on DuckDB, AWS Glue, and Iceberg
Pushed backEric said the distinction between Delta Lake and Iceberg was not one he could fully explain from memory, while Hossam framed them as competing open-table-format approaches.15:27
Open vs Closed Source Agent Infra?
Pushed backBen disputed the assumption that open-source tools let teams fix any problem, saying highly abstract tools can quickly become difficult to understand and can create a painful dead end.11:03