“We put a ton of time into not just model architecture, but also the data pipelines around it, how we eval the product, and having a really good RL loop around post-training and mid-training the model”
The a16z Show · The Missing Infrastructure for AI Agents: Documents | Reducto’s Adit Abraham
Play from 6:22
6:22
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What was described
trained their own foundation model called R1, claiming higher accuracy, faster speed and lower cost than off-the-shelf models
Said nearby on the same subject
“The cost of that is lowered to nearly zero, and you can build your own… you can add your own features… very attractive to say, maybe building my own is something that is better than buying off the shelf”
“We can actually model different scenarios... what happens if expenses rise faster than expected or when the market's down or if you need a new roof, buy a car or possibly healthcare costs increase”