For the first time, firms can build compounding engines of institutional knowledge. Those that succeed will become massively more valuable than those that don't.
@ashwingop@sequoia@kleinerperkins@generalcatalyst@EngramLab@harvey Putting memory, preferences etc outside the weights just makes way more sense. Apart from accessing frontier intelligence w every new model, it’s easy to understand, tweak, and audit. A firm fine tune is unauditable and near impossible to finely tweak behavior.
Performance and $$ depend hugely on harness design. In vertical AI, the gains from a great specialized harness >>> gains from more expensive model
inb4 kimi has quirks - @runta can you try with a diff model also