Original Summary

Hello. It&#x27;s 2026, we&#x27;re training simulated fruit fly brains to play Beat Saber, do we still have to be stuck with internet (re)search as fn: natural language -&gt; black box we can&#x27;t do anything about -&gt; ranked_list&#x2F;summary?<p>There is a long history of people trying to do very fancy things that end up being done in relational databases and a little SQL. There is a gravity to them, a bitter lesson, just like scaling of generalized ml training methods. I mean many, many information products can be built off essentially giant real-time OLAP databases and frontier LLMs writing brilliant SQL+Datalog+vector+Jev etc. queries.<p>Google Search, Tavily, Exa essentially have the problem of <i>mapping</i> your agents&#x27; context you are willing to provide, to a tiny subset of their index. You pay a fixed cost to an extremely hard problem that has a distribution of hardness, which means YOU eat the downsides when they are running out of budgeted compute to help you out.<p>Their algorithms are opaque to the caller, there&#x27;s really not much user control, and there&#x27;s not a serious opportunity to communally improve search recipes, like the lexical+Jev recipes you trust to select bleeding edge AI builders.<p>Furthermore, search companies aren&#x27;t even pursuing text-to-SQL anymore (several have talked to me)... they made up their minds during the traumatic 2024 text-to-sql days. They were just too early.<p>Meet Scry, where I have a 500 TB NVMe internet index (I&#x27;m doing my best indexing and normalizing all the intelligence explosion alpha) that you can run ~arbitrary readonly SQL and some of Datalog over, and I handle the problem of resource-contention with congestion-based micro-auction pricing. When there&#x27;s capacity, the service is free for non-commercial use.<p>I hope you enjoy. I&#x27;m intent on scaling this paradigm on differentiated hardware over much more data, so any compelling use cases or queries I could show off, would be much appreciated!

  • 情报分类：商业与市场研究
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  • 信息来源：Hacker News 新项目
  • 发布时间：2026/9/18 07:15:57