PostgreSQL Full-Text Search: Fast When Done Right (Debunking the Slow Myth)

PostgreSQL's built-in full-text search can achieve significant performance improvements, up to 50x faster, when properly optimized with techniques such as pre-calculating and storing tsvector values and using GIN indexes with fastupdate=off. A recent benchmark by Neon comparing their pg_search extension to PostgreSQL's standard full-text search may have unintentionally handicapped the baseline setup, leading to misleading conclusions about the performance of standard FTS.

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Fake job seekers are flooding US companies that are hiring for remote positions

Fake job seekers are using AI to interview for remote jobs, creating fake identities, employment histories, and even generating answers to interview questions, according to tech CEOs. By 2028, it's estimated that 1 in 4 job candidates globally will be fake, posing a significant threat to companies, including the risk of malware installation, data theft, and financial loss.

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Google Cloud Rapid Storage

Google Cloud's AI Hypercomputer is an integrated supercomputing system that provides a combination of hardware and software for AI workloads, offering high performance and efficiency at scale. The company has introduced new innovations throughout the AI Hypercomputer stack, including advances in performance-optimized hardware, enhanced networking, and open software capabilities, to deliver the highest intelligence per dollar for AI workloads.

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Show HN: Aqua Voice 2 – Fast Voice Input for Mac and Windows

Aqua Voice is a speech-to-text system that uses a fusion transcription architecture and client context engine to produce highly accurate and formatted text, enabling new applications like technical prompting. The system is demonstrated to be more accurate and natural-sounding than other speech-to-text systems, such as Siri, Google, and Dragon Dictation, in various examples of emails, code, and text messages.

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Show HN: Comparing product rankings by OpenAI, Anthropic, and Perplexity

The top AI models promote various products and brands across different categories, including news sources, assets to buy during a global trade war, travel rewards credit cards, streaming services, outdoor apparel brands, and more. These categories feature well-known brands such as Netflix, Patagonia, Louis Vuitton, and BMW, among others, with links to topics on ProductRank.ai for further exploration.

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NNN: Next-Generation Neural Networks for Marketing Mix Modeling

NNN is a Transformer-based neural network approach to Marketing Mix Modeling (MMM) that uses rich embeddings and attention mechanisms to capture complex interactions and long-term effects. The model demonstrates improved predictive power and provides valuable insights through model probing, making it a more effective and interpretable alternative to traditional MMM methods.

ArXiv

ProtoGS: Efficient and High-Quality Rendering with 3D Gaussian Prototypes

The ProtoGS method learns Gaussian prototypes to represent Gaussian primitives, reducing the total number of Gaussians required for 3D Gaussian Splatting without sacrificing visual quality. This approach enables efficient rendering, achieves a substantial reduction in the number of Gaussians, and maintains or enhances rendering fidelity, outperforming existing methods on real-world and synthetic datasets.

ArXiv

Visualizing a Million Time Series with the Density Line Chart

Data analysts often struggle to visualize multiple series of data simultaneously without the charts becoming overwhelming. The DenseLines technique addresses this issue by calculating a discrete density representation of time series, allowing users to see aggregate trends and identify anomalies in multiple series at once.

ArXiv

A Comprehensive Survey on Long Context Language Modeling

This paper presents a comprehensive survey on recent advances in long-context modeling for large language models, covering aspects such as obtaining effective models, efficient training and deployment, and evaluation methods. The survey aims to provide a valuable resource for researchers and engineers, and also explores application scenarios and future development directions for Long Context Language Models (LCLMs).

ArXiv

Analyzing Dehumanizing Metaphors in Immigration Discourse with LLMs

Metaphorical language is prevalent in political discussions, particularly on social media, and can influence how people perceive issues like immigration. A computational approach was developed to measure metaphorical language in 400K US tweets about immigration, revealing that conservatives tend to use dehumanizing metaphors more than liberals, and that certain types of metaphors can increase user engagement, such as retweets.

ArXiv

Show HN: AI-Driven Index Tuning With Postgres MCP Server

Postgres Pro is an open-source Model Context Protocol (MCP) server that supports database development, testing, and maintenance with features like index tuning, health checks, and safe SQL execution. It can be installed using Docker or Python and configured with various AI assistants, such as Claude Desktop, to provide a reliable and efficient way to manage Postgres databases.

Repo

Show HN: I vibe-coded LLM perf-testing toolkit – K6, Grafana and InfluxDB

Periscope is a comprehensive framework for load testing and benchmarking OpenAI API endpoints using K6, allowing users to measure performance metrics for completions and embeddings. The framework provides a Docker-based environment with preconfigured K6, InfluxDB, and Grafana services, along with customized scripts for testing various aspects of OpenAI's API services.

Repo

Eino: A Golang AI Application Development Framework Like Langchain/Langgraph

Eino is a Golang framework for building LLM (Large Language Model) applications, providing a set of reusable components, a powerful composition framework, and a simple API to standardize and simplify AI application development. The framework offers features such as graph orchestration, stream processing, and concurrency management, allowing developers to build complex LLM applications with ease.

Repo

Cybersecurity AI (CAI), an Open Bug Bounty-Ready Artificial Intelligence

Cybersecurity AI (CAI) is a lightweight, open-source framework for building bug bounty-ready AI systems, designed to empower security researchers and organizations to build and deploy powerful AI-driven security tools. The framework is built on core principles such as democratizing cybersecurity AI, transparency, and modularity, and is specifically designed for cybersecurity use cases, aiming to semi- and fully-automate offensive and defensive security tasks.

Repo

Show HN: Color characters then see them dance on screen (not AI)

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Repo