IAC has announced the retirement of Ask.com, the successor to the iconic mid-90s search engine Ask Jeeves, after 30 years of operation. The service officially closed on May 1, 2026, as part of a strategic shift by its parent company. Known for pioneering natural language queries that allowed users to ask questions like they were speaking to a person, the platform was an early precursor to modern AI chatbots.
- Ask.com officially shut down on May 1, 2026.
- The site pioneered natural language processing in search technology.
- IAC is shifting its corporate focus away from the search business.
- Ask.com officially shut down on May 1, 2026.
- The site pioneered natural language processing in search technology.
- IAC is shifting its corporate focus away from the search business.
>"One scale parameter determines accuracy in rotation-based vector quantization."
The article demonstrates how the earlier EDEN quantization method outperforms its "successor" TurboQuant by utilizing an analytically optimized scale factor for superior accuracy and bias correction.
* EDEN outperforms newer TurboQuant algorithms.
* Optimal scaling is a key differentiator.
* EDEN-biased minimizes reconstruction error (MSE).
* EDEN-unbiased ensures highly accurate estimation.
* Superior efficiency at low bit-widths.
* Ideal for LLM and KV cache optimization.
The article demonstrates how the earlier EDEN quantization method outperforms its "successor" TurboQuant by utilizing an analytically optimized scale factor for superior accuracy and bias correction.
* EDEN outperforms newer TurboQuant algorithms.
* Optimal scaling is a key differentiator.
* EDEN-biased minimizes reconstruction error (MSE).
* EDEN-unbiased ensures highly accurate estimation.
* Superior efficiency at low bit-widths.
* Ideal for LLM and KV cache optimization.
As artificial intelligence continues to advance and outperform humans in specific tasks like mathematics or complex gaming, the question arises whether human cognition will remain unique. Tom Griffiths argues that intelligence is not a single linear scale but a multifaceted trait shaped by different constraints. While AI excels at processing vast amounts of data using scalable hardware, human intelligence is uniquely defined by biological limitations such as short lifespans and limited neural capacity. These constraints have forced humans to develop specific strengths in pattern recognition, social cooperation, and efficient learning from minimal experience. Ultimately, rather than seeing AI as a direct rival on all fronts, we should view it as a different kind of entity with its own set of capabilities and weaknesses.
- Intelligence is multifaceted rather than a single scale like height.
- Human intelligence is shaped by biological constraints such as lifespan and brain size.
- AI intelligence is driven by data volume, scalability, and machine communication.
- Different underlying architectures lead to different methods of problem-solving.
- Humans and AI are likely to be companions with distinct capabilities rather than total competitors.
- Intelligence is multifaceted rather than a single scale like height.
- Human intelligence is shaped by biological constraints such as lifespan and brain size.
- AI intelligence is driven by data volume, scalability, and machine communication.
- Different underlying architectures lead to different methods of problem-solving.
- Humans and AI are likely to be companions with distinct capabilities rather than total competitors.
WebMCP is an open source JavaScript library that allows any website to integrate with the Model Context Protocol. It provides a small widget for users to connect to and interact with webpages via LLMs or agents.
Key features include:
- Tools that allow LLMs to perform specific actions on your website
- Prompts that serve as predefined templates for standardized interactions
- Resources that expose page data and content to be used as context for LLM interactions
Key features include:
- Tools that allow LLMs to perform specific actions on your website
- Prompts that serve as predefined templates for standardized interactions
- Resources that expose page data and content to be used as context for LLM interactions
Google's web.dev guidance now advises developers to treat AI agents as a distinct audience alongside human visitors. As more users delegate goal-oriented tasks to AI, websites with complex hover states or shifting layouts may become functionally broken for these automated entities. The guide highlights that optimization for agents aligns closely with existing accessibility and semantic HTML best practices, making sites better for both humans and machines.
* Treating agents as a distinct visitor type
* How agents interpret websites via screenshots, raw HTML, and the accessibility tree
* Recommendations for using semantic HTML elements and maintaining stable layouts
* Introduction to WebMCP, a proposed web standard for agent-website interaction
* Treating agents as a distinct visitor type
* How agents interpret websites via screenshots, raw HTML, and the accessibility tree
* Recommendations for using semantic HTML elements and maintaining stable layouts
* Introduction to WebMCP, a proposed web standard for agent-website interaction
A collection of various LiDAR and ToF (Time-of-Flight) sensing solutions including 360 degree laser range scanners, depth cameras for ROS, and single-point ranging sensors. The selection features technologies such as DTOF, solid-state LiDAR, and RGB-D cameras suitable for SLAM and interactive AI applications.
Key product types:
RPLiDAR series (A1M8, A2M12, S2L, etc.)
STL DTOF sensors
CS depth cameras for ROS
TF series single-point ranging sensors
YDLIDAR linear array solid state LiDAR
Key product types:
RPLiDAR series (A1M8, A2M12, S2L, etc.)
STL DTOF sensors
CS depth cameras for ROS
TF series single-point ranging sensors
YDLIDAR linear array solid state LiDAR
- Theft Detection Lock with offline and authentication safeguards
- Private Space sandboxing for app isolation
- Now Playing background music recognition
- Private Space sandboxing for app isolation
- Now Playing background music recognition
This page provides download options and build information for the Orange Pi Zero2W board using Armbian. It features a Debian Minimal variant based on Debian 13 trixie with kernel version 6.18.26. Users can download the image directly or via torrent, and instructions are included for building the image from source using the Armbian framework.
Main topics:
- Available software variants and distributions
- Kernel version information
- Download links and file sizes
- Instructions for manual builds from source
Main topics:
- Available software variants and distributions
- Kernel version information
- Download links and file sizes
- Instructions for manual builds from source
A specialized toolset providing graphical data visualizations for ADS-B decoders, including readsb, dump1090-fa, and other dump1090 variants that supply stats.json files. The project includes automated installation scripts and features designed to protect SD card longevity on hardware like the Raspberry Pi by managing how frequently data is written to disk.
Main topics:
- ADS-B decoder graph visualization
- SD card write reduction and optimization
- Automated installation and update processes
- Data backup, restoration, and integration methods
- Configuration for local map URLs and system timezones
Main topics:
- ADS-B decoder graph visualization
- SD card write reduction and optimization
- Automated installation and update processes
- Data backup, restoration, and integration methods
- Configuration for local map URLs and system timezones
PiShrink is a bash script designed to automatically shrink Raspberry Pi images, making them easier to store and faster to flash onto SD cards. Once the shrunk image is booted, it will automatically resize itself to match the maximum capacity of the target SD card. The tool also supports compression using gzip and xz, with an option for parallel compression across multiple CPU cores to improve speed.
Key points:
- Automatic shrinking of Raspberry Pi images
- Boot-time filesystem expansion to full SD card size
- Support for parallel multi-core compression
- Compatibility with Linux, Windows (via WSL 2), and macOS (via Docker)
Key points:
- Automatic shrinking of Raspberry Pi images
- Boot-time filesystem expansion to full SD card size
- Support for parallel multi-core compression
- Compatibility with Linux, Windows (via WSL 2), and macOS (via Docker)
