-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
These models are pretty much always extrapolating [0]
Whether the extrapolation is crude/low-rank or astute/high-rank is a question of memorization vs generalization. That gets into the question of whether or not the model is over-fitted or under-fitted. There are certain heuristics borrowed from high dimensional statistical physics that can be used to guess how good the test performance of a model will be on a typical task without even knowing what the test data is [1].
Originality for me means finding better answers to sub-tasks, and then combining those answers together in a better way. This is the nirvana of cross-entropy minimization - the emergence of capability results from gaining the ability to amass a wider range of skills, improving upon them, and percolating those improvements towards multiply the leverage of other skills.
How long such a thing can keep improving with current tech, who knows, but you should really think critically about whether that sounds just like interpolation through the corpus.
[0] Learning in High Dimension Always Amounts to Extrapolation - https://arxiv.org/abs/2110.09485
[1] https://github.com/CalculatedContent/WeightWatcher
Related posts
-
NPi – An Open Source project for enhancing AI Agents in taking action
-
Recapping the AI, Machine Learning and Data Science Meetup — May 2, 2024
-
THOR: Tracklet-Less Heliocentric Orbit Recovery
-
Show HN: Panza: A personal email assistant, trained and running on-device
-
Show HN: SpRAG – Open-source RAG implementation for challenging real-world tasks