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The post promotes Forge '26, a conference by Fireworks AI focused on specialized intelligence and AI engineering skills, with featured speakers from NVIDIA and Microsoft.
The article argues that as open weight models become equally capable to proprietary ones, OpenAI and Anthropic's valuations will plummet, while companies like Fireworks AI will capture value by operating open models as a neutral infrastructure layer.
A Fireworks AI representative signs an open letter supporting open weights, arguing that open models enable intelligence to compound within companies.
Fireworks AI announces Serverless 2.0, introducing three serving tiers (Standard, Priority, Fast) to handle traffic congestion without pre-provisioning GPUs, enabling per-request routing for reliability and cost efficiency.
Natolambert shares a positive first impression of GLM, noting it is easy to set up on Fireworks AI and works well with Claude Code.
DAIR Academy Plugins is an open-source marketplace of plugins for Claude Code, including an llm-council skill that orchestrates multiple open-weight LLMs via Fireworks AI.
Fireworks AI announces reaching $800M annualized run rate with 4x revenue growth in Q1, excluding Cursor, marking a significant business milestone.
Marco Oram shares his exploration of automating LLM fine-tuning using Fireworks AI Agent, fine-tuning a small Qwen model to integrate with his PaperWiki project, demonstrating a step toward self-improving AI.
Fireworks AI announces its training platform in preview, allowing developers to train, fine-tune, and deploy custom AI models with full ownership of data and weights.