Yash Patil Calls Specialized Models the Future of AI
Applied Compute CEO and other founders post about narrow AI models for business tasks.
Yash Patil, Applied Compute CEO and former OpenAI engineer, posted that specialized models are the future. Shopify CEO Tobi Lütke replied that finetuned tiny models work well with self-improving flywheels, noting one case where such a model outperformed a larger general system on a buyer profile task. Moondream CTO Vikhyat K. offered an inference engine for Qwen3.5 0.8B on H100s. DatologyAI CEO Ari Morcos added that business use cases are narrow and pre-specified, giving focused models an edge in cost and control. LangChain and others shared related posts on open weights models and agent traces.
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8 postsTL 
tobi lutke@tobiTraining tiny models for special purpose use cases works so incredibly well if you have a great self improving recursive flywheel. Shopify ML team is on fire. finetuned 0.8b model beats GPT 5.6-sol xhigh in this very specialized task.
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VI vik@vikhyatk@tobi looks like you're running Qwen3.5 0.8B on H100s here? we recently shipped an inference engine that runs it really fast, in case that's of interest to you!
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AL Aaron Levie@levieNow that the base open weights AI models are getting far better, and post training infra is becoming more mature and commercialized, there are going to be all new plays for companies that have large amounts of data to have their own models. Licensing data for external model…
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FI Fireworks@FireworksAI_HQOur partners @LangChain generate billions of tokens of agent traces a day, their richest signal on how real users react. Judging every one with a frontier closed model like GPT-5.5 or Opus is too costly, so they fine-tuned a Qwen base model on Fireworks that matches it at up…
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YP Yash Patil@ypatil125Specialized models are the future! So much exciting stuff to build and scale!
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RA Ramin@ramin_m_habout a year ago, we released the first instances of Liquid nanos. these are products we sell to enterprises: tiny models + the customization platform matching the quality of frontier models on specialized use-cases. It is easy to recursively customize a model to 90% production…
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