Super HN

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211. Poor man's bitemporal data system in SQLite and Clojure
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
212. Scala language server with rich IDE features
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
213. 'Howya lads': how we greet our friends and acquaintances
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
214. Engineers transform dental floss into needle-free vaccine
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
215. France to recognise Palestinian state in September
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
216. Extending the von Neumann Model with Dedicated Reasoning Unit for Native AGI
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
217. Do You Know How `or` and `and` Work in Python?
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
218. Legends of the games industry: Jim Sachs – Amiga – (2024)
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
219. Hitting the Brakes on Claude Code
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
220. Hundreds of Weather Records Could Be Broken Next Week
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
221. Fireside Chat with Cerebras CEO Andrew Feldman and Eric Schmidt [video]
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
222. AI setup wizard for installing packages into the codebase
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
223. Thoughts on Flash (2010)
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
224. America's AI Action Plan Is Pretty Good
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
225. Philosopher–Builder Summer Reads
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
226. How AI, robotics and late artist Norval Morrisseau are helping fight art fraud
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
227. Delta Struggles with Elite Overproduction
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
228. Anybody in Tech in the Dominican Republic?
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
229. AI could think in ways we don't understand – evading efforts to keep it aligned
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
230. Climate-driven polar motion: 2003–2015 (2016)
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
231. Basic Computer Terms (1976) [video]
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
232. Shakti (K9) Tutorial
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
233. The Problem with Time and Timezones [video]
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
234. SF may soon ban natural gas in homes and businesses undergoing major renovations
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
235. Elderly cat suffers 'terror' from Blue Angels, feline's owner says in lawsuit
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
236. San Francisco Cybernetics Symposium
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
237. Light of Other Days [pdf]
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
238. Fighter Jets for Sale
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
239. .gitignore Is Inherently Sisyphean
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…
 
240. Ask HN: How you network in NYC as a founder from out of town
    TL;DR - We’re excited to introduce voyage-context-3, a contextualized chunk embedding model that produces vectors for chunks that capture the full document context without any manual metadata and context augmentation, leading to higher retrieval accuracies than with or without augmentation. It’s also simpler, faster and cheaper, and is a drop-in replacement for standard embeddings without…