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Ollama

Zero Cold Starts: Serverless AI Agents on Akamai Functions — Thorsten Hans

Zero Cold Starts: Serverless AI Agents on Akamai Functions — Thorsten Hans

Thorsten Hans shows how to build MCP servers and AI agents with Spin, the open-source WebAssembly framework, and run them on Akamai Functions, a globally distributed serverless platform with no cold starts. The talk explains why WebAssembly suits edge-native AI workloads, live-codes MCP servers with wasmcp in TypeScript and Rust, deploys them worldwide with one command, and closes with a Vercel AI SDK agent backed by a Linode GPU model and memory snapshots that keep apps warm.

Open Models Change The Economics of AI

Open Models Change The Economics of AI

Ollama Co-founder Jeffrey Morgan discusses the enterprise shift to open models, driven by cost, customization, and coding agents, leading to a 150X token growth. He highlights the dominance of Chinese models in cloud consumption, the hardware renaissance enabling local LLMs, and the rise of ultra-efficient "flash" models. Morgan also shares Ollama's journey, from its YC pivot to its monetization strategy, and reflects on lessons for building AI companies.

Compression at the Edge — Chris Alexiuk, NVIDIA

Compression at the Edge — Chris Alexiuk, NVIDIA

This panel discussion explores the critical role of model compression, particularly quantization, in democratizing AI. It delves into how massive models like GLM 5.2 can be shrunk by over 80% without equivalent performance loss, thanks to techniques like mixed-precision quantization and understanding uneven layer importance. The discussion covers NVIDIA's NVFP4 format, challenges posed by new model architectures, the preference for KL divergence over accuracy benchmarks, and the vision of future AI running efficiently on all local devices.

You Asked About AI: Agents, Hacking & LLMs

You Asked About AI: Agents, Hacking & LLMs

An exploration of the evolving AI landscape, covering the paradigm shift in cybersecurity due to AI agents, the practicalities of running local LLMs with tools like Ollama and vLLM, and the emerging stack for agent-to-agent communication.

Build a Local LLM App in Python with Just 2 Lines of Code

Build a Local LLM App in Python with Just 2 Lines of Code

Distinguished Engineer Chris Hay demonstrates how to run and program Large Language Models (LLMs) locally in just two lines of Python code. The tutorial covers setting up a local environment with Ollama and UV, using a custom library for simplified interaction, and explores advanced topics like asynchronous streaming, persona customization with system prompts, and managing multi-turn conversations.