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30 articles about search in AI news
Grep Beats Vector Search in Agent Benchmarks, New Paper Finds
Grep beats vector search on LongMemEval across all harness-model pairs, showing agent design matters more than retrieval method for evidence-location tasks.
Gemini Embeddings Beat ResNet50, SigLIP on Visual Search Benchmark
Gemini embeddings beat ResNet50 and SigLIP on visual product search with 92.3% recall@10, an 8.2-point gain.
Large Memory Models: New Architecture Beyond RAG and Vector Search
Researchers with 160+ Nature and ICLR publications have built Large Memory Models (LMMs), a new architecture designed to emulate human memory processes, offering an alternative to RAG and vector search paradigms.
OpenAI Agents Now Ask Questions Good Enough for Research Papers
Sébastien Bubeck revealed on the OpenAI Podcast that internal AI agents now ask research questions so insightful they're inspiring papers and correcting published mistakes, with a 1-2 year timeline for full researcher-level capabilities.
Onyx: Open-Source AI Enterprise Search Challenges Glean's $7.2B Valuation
Open-source platform Onyx provides self-hosted AI enterprise search connecting to 40+ tools, offering a free alternative to Glean's $50/user/month SaaS. Backed by YC and $10M seed funding, it's used by Netflix and Ramp.
ECLASS-Augmented Semantic Product Search
Researchers systematically evaluated LLM-assisted dense retrieval for semantic product search on industrial electronic components. Augmenting embeddings with ECLASS hierarchical metadata created a crucial semantic bridge, achieving 94.3% Hit_Rate@5 versus 31.4% for BM25.
Google Launches Deep Research Max Agent on Gemini 3.1 Pro
Google DeepMind rolled out Deep Research Max and standard Deep Research agents on Gemini 3.1 Pro, enabling autonomous web and proprietary data research via the Gemini API. The Max variant uses extended test-time compute for thorough asynchronous reports.
AI Agents Now Training Other AI Models, Sparking Autoresearch Trend
AI agents are now being used to train other AI models, creating advanced agentic systems. This development stems from Andrej Karpathy's autoresearch repository and represents early-stage automation of AI research.
A Reference Architecture for Agentic Hybrid Retrieval in Dataset Search
A new research paper presents a reference architecture for 'agentic hybrid retrieval' that orchestrates BM25, dense embeddings, and LLM agents to handle underspecified queries against sparse metadata. It introduces offline metadata augmentation and analyzes two architectural styles for quality attributes like governance and performance.
New Research Models 'Exploration Saturation' in Recommender Systems
A research paper analyzes 'exploration saturation'—the point where more diverse recommendations hurt user utility. Findings show this saturation point is user-dependent, challenging the standard practice of applying uniform fairness or novelty pressure across all users.
NVIDIA Research Shows AI Can Optimize Decades-Old EDA Tools Like ABC
New NVIDIA research indicates AI can be used to optimize Electronic Design Automation (EDA) tools, such as the classic ABC system, which have been manually tuned by engineers for decades. This could automate a core, labor-intensive bottleneck in semiconductor design.
Anthropic Launches STEM Fellows Program to Pair Experts with AI Research
Anthropic announced the Anthropic STEM Fellows Program, a new initiative to bring science and engineering experts into its research teams for collaborative, months-long projects aimed at accelerating progress with AI.
Codex 'Chronicle' Research Preview Adds Memory for Daily Developer Context
A research preview of 'Chronicle' for Codex has been released. It enables the AI coding assistant to accumulate memories from a developer's daily workflow to improve context.
PRL-Bench: LLMs Score Below 50% on End-to-End Physics Research Tasks
Researchers introduced PRL-Bench, a benchmark built from 100 recent Physical Review Letters papers, testing LLMs on end-to-end physics research. Top models scored below 50%, exposing a significant capability gap for autonomous scientific discovery.
Researchers Achieve Ultra-Long-Horizon Agentic Science with Cohesive AI Agents
A research team has developed AI agents capable of executing and maintaining coherent, long-horizon scientific research workflows. This addresses a core challenge in creating autonomous systems for complex discovery.
Clerk: Auto-Summarize Every Claude Code Session into Searchable Markdown
Install Clerk to automatically generate Markdown summaries of every Claude Code session, making your debugging, research, and architecture decisions searchable across projects.
Prince Canuma's M3 Ultra 512GB & RTX Pro 6000 Setup for MLX Research
Independent developer Prince Canuma has assembled a powerful, community-sponsored home compute cluster for MLX research and model porting, featuring an M3 Ultra with 512GB RAM and an RTX Pro 6000.
Google DeepMind Researcher: LLMs Can Never Achieve Consciousness
A Google DeepMind researcher has publicly argued that large language models, by their algorithmic nature, can never become conscious, regardless of scale or time. This stance challenges a core speculative narrative in AI discourse.
HUOZIIME: A Research Framework for On-Device LLM-Powered Input Methods
A new research paper introduces HUOZIIME, a personalized on-device input method powered by a lightweight LLM. It uses a hierarchical memory mechanism to capture user-specific input history, enabling privacy-preserving, real-time text generation tailored to individual writing styles.
Product Quantization: The Hidden Engine Behind Scalable Vector Search
The article explains Product Quantization (PQ), a method for compressing high-dimensional vectors to enable fast and memory-efficient similarity search. This is a foundational technology for scalable AI applications like semantic search and recommendation engines.
MiniMax Launches MaxHermes, Cloud-Hosted Agent with NousResearch
MiniMax has launched MaxHermes, a cloud-hosted version of the Hermes agent framework, in partnership with NousResearch. This provides a managed service for users of MiniMax's M2.7 model, aiming to simplify agent deployment.
New Research Proposes Collaborative Contrastive Network for Generalizable
Researchers propose the Collaborative Contrastive Network (CCN) to solve Trigger-Induced Recommendation challenges in ephemeral e-commerce scenarios like Black Friday. Instead of modeling ambiguous intent, CCN learns context-specific preferences from user-trigger pairs via novel contrastive signals. In online A/B tests on Taobao, CCN increased CTR by 12.3% and order volume by 12.7% in unseen scenarios.
New Research Proposes Lightweight Method to Fix Stale Semantic IDs in
Researchers propose a method to update 'stale' Semantic IDs in generative retrieval systems without full retraining. Their alignment technique improves key metrics and reduces compute costs by ~8-9x, addressing a core challenge in dynamic recommendation environments.
FRAGATA: A Hybrid RAG System for Semantic Search Over 20 Years of HPC
A new paper details FRAGATA, a system enabling semantic search over two decades of technical support tickets at a supercomputing center. It uses hybrid retrieval-augmented generation (RAG) to find relevant past incidents despite typos, language, or wording differences, showing a qualitative improvement over the legacy search.
New Research Proposes Authority-aware Generative Retrieval (AuthGR) for
A new arXiv paper introduces an Authority-aware Generative Retriever (AuthGR) framework. It uses multimodal signals to score document trustworthiness and trains a model to prioritize authoritative sources. Large-scale online A/B tests on a commercial search platform report significant improvements in user engagement and reliability.
Shopify Engineering Teases 'Autoresearch' Beyond Model Training in 2026 Preview
Shopify Engineering has previewed a 2026 perspective suggesting 'autoresearch'—automated research processes—will have applications extending beyond just training AI models. This signals a broader operational automation strategy for the e-commerce giant.
AI Research Suggests Whale 'Vowels' in Sperm Whale Communication
AI researchers analyzing sperm whale vocalizations have identified combinatorial structures that function like vowels, marking a step toward decoding cetacean communication.
Tsinghua Researchers Diagnose On-Policy Distillation Failures, Propose Fixes
Researchers from Tsinghua University have pinpointed two necessary conditions for successful on-policy distillation: compatible thinking patterns and novel teacher capabilities. They propose two recovery methods to salvage failing distillation runs.
New Research Proposes Profiler and DAVINCI for Scalable
Researchers propose Profiler, a non-learnable module to efficiently capture human citation patterns, and DAVINCI, a reranking model that integrates these patterns with semantic data. They also introduce a strict inductive evaluation setting to better simulate real-world recommendation scenarios, achieving state-of-the-art results.
Anthropic's AI Researchers Outperform Humans, Discover Novel Science
Anthropic reports its AI systems for alignment research are surpassing human scientists in performance and generating novel scientific concepts, broadening the exploration space for AI safety.