Nicolay Gerold

One of the common themes you see is that LLMs are great when you are operating in the gray zone at the "edge" of your knowledge or confidence. For example, translating a program to C to speed it up. I can code C but I'm really rusty. I can't remember precise function names, what to #include, arguments etc. But LLMs are awesome at that. So it... See more

The Gemini API context caching feature is designed to reduce the cost of requests that contain repeat content with high input token counts.

When to use context caching

Context caching is particularly well suited to scenarios where a substantial initial context is referenced repeatedly by shorter requests. Consider using context caching for use cases... See more

Bottom-up processing: information is directing your activity deliberately or reflexively depending on your attention. Brain tries to direct as much activity as possible in a reflexive way.

• Some datasets become standards for data exchange . S&P’s CUSIP for publicly traded securities, D&B’s DUNS for private companies, Datavant’s universal patient key for medical records, LiveRamp’s RampID for advertiser audiences are all examples here, albeit for varying degrees of “table-stakes-ness / industry adoption”.


• Some datasets become evaluation

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Red blood cells turn over roughly every 120 days. They offer many interesting more long term biomarkers for health (e.g. Omega-3 index).

1. Introduction of DeepSeek Coder

DeepSeek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese. We provide various sizes of the code model, ranging from 1B to 33B versions. Each model is pre-trained on project-level code... See more

Neuroplasticity only occurs after focused attention during rest or sleep. Diffused thinking is also consolidating the memory and skill pathways (no duration, path and outcome).

My top issues with the foundations of the "modern data stack":

• Snowflake - you may only pay for what you use, but you pay through the nose for it. The cost is so high that in many cases it can exceed the cost of binders full of dbas.


• Fivetran - convenient, but they tried to triple my licensing cost last year, they have almost constant 15 minute

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When it comes to identifying where generative AI can make an impact, we dig into challenges that commonly:

• Involve analysis, interpretation, or review of unstructured content (e.g. text) at scale


• Require massive scaling that may be otherwise prohibitive due to limited resources


• Would be challenging for rules-based or traditional ML approaches