AI assisted search-based research actually works now

Curated retrieval versus open web search in public AI information...

Public institutions increasingly use large language models (LLMs) to answer citizens' questions, often pairing a curated knowledge base with live web search, yet whether the sources behind these...

The AI Chemist: To be trustworthy, LLMs need to show their work

Good scientists reveal how they do their experiments and report their results; so should any machine-driven research

Meilisearch: Unified Search & AI Retrieval Platform

Build lightning-fast search and AI retrieval with Meilisearch. Open-source, developer-friendly search engine trusted by 20,000+ teams worldwide.

AI Mode is obviously the future of Google Search

The internet’s biggest search engine is going to be unrecognizable in just a few years.

elvis on Twitter / X

arXiv Papers → LLM ArtifactsThis is how I keep up with AI research now.It's like having access to the most personalized arXiv feed.Automations run everyday to curate papers based a set of rules and insights.Curated papers are indexed and power the artifacts.Agent… pic.twitter.com/5UCxF8ZsT0— elvis (@omarsar0) May 6, 2026

How I use AI

LLMs in everyday life and work

AI search answers are the fast food of your information diet – convenient and tasty, but no substitute for good nutrition

An information scientist explains that while Google’s AI Overviews and other AI search tools may look enticing, you shouldn’t rely on them to fill all your search needs.

AI search answers are the fast food of your information diet – convenient and tasty, but no substitute for good nutrition

An information scientist explains that while Google’s AI Overviews and other AI search tools may look enticing, you shouldn’t rely on them to fill all your search needs.

Chroma - open-source search infrastructure for AI

Open-source search infrastructure for AI

Stevens: a hackable AI assistant using a single SQLite table and a handful of cron jobs

There’s a lot of hype these days around patterns for building with AI. Agents, memory, RAG, assistants—so many buzzwords! But the reality is, you don’t need fancy techniques or libraries to build useful personal tools with LLMs.

Sebastian Raschka on Twitter / X

Pretty cool. I think 2025-2026 will be a stronger focus on these in open source tooling.I.e. having LLMs delegate knowledge-based queries to search, which in turn frees up model capacity to improve reasoning capabilities and tool use. https://t.co/wNTg283mb2— Sebastian Raschka (@rasbt) August 12, 2025

Artificial intelligences and human scientists exhibit...

We investigate the effectiveness of artificial intelligences (AI)-specifically large language models (LLMs)-relative to human scientists at high-level cognitive tasks in social science such as...

MainPage8

The InfoCentral project has historically been focused more heavily upon the symbolic (human-meaningful) side of AI. This included derivatives of Semantic Web and related knowledge representation research, which were dependent on human effort to curate and categorize structured data. The symbolic approach to AI has largely lost the race to the neuro/neuro-symbolic (opaque vectors, statistical) side of AI research, notably the success of the Large Language Model (LLM) paradigm. Due to its faculties with natural language, remarkably little human involvement is needed to infer structure and meaning from traditional (mostly unstructured) information. As such, some of the approaches previously explored in the InfoCentral project have lost relevance. That said, LLM-based tools can perhaps help us finish the symbolic side of the grand AI project, by doing the tedious work that humans were reluctant to do! It has long been theorized that a combination of approaches will ultimately provide the most robust and performant systems, able to work with messy transient unstructured information while also building networks of verifiable persistent structured information that both humans and machines can cross-verify. This may prove useful in both ensuring that future AI systems remain aligned to human goals and values and that inevitable abuses and failures can be easily recovered from. To that end, some research results of this project may be re-usable in a new context.

Agentic Search for Dummies — Benjamin Anderson

A simple, effective baseline for building AI search agents.

Zero-click searches: Google’s AI tools are the culmination of its hubris

Google's first year with AI search was a wild ride. It will get wilder.