Google paid $10M at auction for Spirit Airlines data to train AI

1 min
Google paid $10M at auction for Spirit Airlines data to train AI

Written by

More to read

  • IBM Research Evaluates Agentic Memory Sizing Across 8 Models: Dosage Calibrations, Ceiling Effects, and Token Efficiency

    In a technical report published on August 18, 2026, researchers at IBM Research detailed empirical evaluations on sizing and calibrating agentic memory across eight large language models. The study, conducted using the open-source ALTK-Evolve framework across the AppWorld benchmark, demonstrates that agentic memory performance is governed by capability-dependent dosage rather than uniform prompt accumulation. Agentic memory architectures typically extract procedural guidelines from prior execut

    1 min
  • Google Opens Gemini in Chrome to All U.S. Android Users and Extends Auto Browse to Mobile

    Google expanded Gemini in Chrome to all Android users across the United States on August 18, 2026. The update introduces the browser's built-in AI assistant to mobile handsets and extends "auto browse," Google's agentic web automation feature, to smartphones for Google AI Pro and AI Ultra subscribers. The Android rollout follows the initial launch of Gemini in Chrome for desktop environments in September 2025. On mobile devices, the assistant provides on-page article summaries, contextual answe

    1 min
  • Multi-Token Prediction: How Future Token Supervision Densifies Representations and Speeds Up LLM Serving

    Standard autoregressive language models are trained under a strict next-token prediction objective. At every sequence position, the model consumes a prefix of tokens and predicts the single immediate successor token using a cross-entropy loss. While this paradigm has scaled language modeling across orders of magnitude, it suffers from an architectural limitation: myopic optimization. By evaluating loss exclusively on the immediate next step, standard training fails to reward representations that

    1 min