Small language models

Oct 23, 2026

Self-replicating AI, your doctor’s chatbot & agents at dinner

A look at three developments shaping the near future of AI: Anthropic's research on small models that could copy themselves across cheap consumer devices, a JAMA study showing how doctors are adopting clinical chatbots for treatment decisions, and an experiment in which AI agents booked a founders' dinner and then networked with one another. The panel weighs security risks in the home, the trade-offs of speed versus verification in medicine, and how much autonomy agents should have when dealing with other agents.

Oct 10, 2026

Small Models, Big Results: Training a Finance Agent for Under $500 — Charles Dickens, Snorkel AI

Snorkel AI and UC Berkeley's Sky Computing Lab show that a 4B Qwen3 model, trained with reinforcement learning for under $500 using the rLLM framework, beats its 235B sibling on expert-validated financial question answering built from SEC 10-K filings. The talk covers the FinQA dataset construction and verification, common failure modes of frontier models, transfer to multi-table and general tool-use tasks, and ablations showing that simple data and binary rewards outperform more elaborate setups, since the real bottleneck is disciplined tool use rather than reasoning depth.

Oct 01, 2026

AI Makes Games Worse?

Piero Molino, CEO of Studio Atelico, argues that AI should be a foundational game mechanic enabling new experiences rather than a cost-cutting shortcut. He covers on-device multimodal engines built on small fine-tuned models, the economics of cloud inference, artist rights, open source in the game stack, and what skill means in an era of coding agents.

Sep 16, 2026

Your Agreements Are a Database You Can't Query — Hiral Shah, Docusign & Sean Sodha, NVIDIA

The talk by Hiral Shah (DocuSign) and Sean Sodha (NVIDIA) addresses the critical challenge of extracting valuable, negotiated data from unstructured agreements, highlighting how generic AI models fail at complex tables. They introduce DocuSign's Intelligent Agreement Manager powered by NVIDIA's purpose-built, small-parameter NeMo Parse VLM, designed specifically for efficient and accurate table extraction, demonstrating 20x faster processing, lower cost, and its impact on unlocking billions in trapped enterprise data.

Jun 29, 2026

Frontier results, on device - RL Nabors, Arize

RL Nabors discusses the significant costs associated with using frontier AI models, covering security, latency, and financial implications. She introduces a framework for right-sizing AI solutions by leveraging smaller, task-specific models and Small Language Models (SLMs). The framework details how to prove task feasibility, establish success criteria with golden datasets, conduct capability evaluations (using tools like Phoenix), and select the most appropriate "Small And Good Enough" (SAGE) model. Nabors further demonstrates how prompt engineering, particularly few-shot prompting, and post-processing can close performance gaps with larger models, while advocating for continuous regression evaluations to maintain performance integrity. The overarching message is to "prototype big, deploy small" to optimize AI deployments.

Jun 29, 2026

The Future Is Domain-Specific Agents - Justin Schroeder, StandardAgents

Justin Schroeder argues for a paradigm shift in AI agent development from monolithic, context-inflated agents (inheritance) to modular, domain-specific agents (DSAs) that operate through composition. He explains how DSAs offer superior token efficiency, cost savings with smaller models, enhanced security through capability limits, and better scalability, predicting their widespread adoption by 2027 as a solution to rising AI costs and the need for practical, customer-facing AI.