TII’s Falcon-H1R 7B Outperforms 47B Models on Math Reasoning While Running on a 16GB Laptop
A 7-billion parameter model just scored 88.1% on AIME-24 math reasoning, crushing NVIDIA’s 47B Nemotron at 49.7%. The assumption that…
Meta Announces $600 Billion AI Infrastructure Spend Through 2028, Creating ‘Meta Compute’ Division to Build Tens of Gigawatts of Data Center Capacity
Meta just committed more capital to AI infrastructure than the entire GDP of Finland, Belgium, or Thailand combined—and they hired a former…
Apple Confirms $1 Billion Annual Google Gemini Deal: 1.2 Trillion Parameter Model Powers Siri After In-House AI Delays
Apple’s $1 billion annual payment to Google for AI infrastructure confirms what the industry whispered for two years: the world’s…
NVIDIA Alpamayo: 10B-Parameter VLA Model Reduces Autonomous Driving Validation Variance by 83% Across 310,895 Real-World Clips
NVIDIA just open-sourced a 10-billion-parameter autonomous driving brain trained on 1,700+ hours of real-world footage from 25 countries—and…
GreyNoise Captures 91,403 Attacks Targeting Every Major LLM
Attackers launched 91,403 sessions against AI infrastructure in 90 days—and they hit every major model from GPT-4o to Claude to Llama. The…
The Home Depot Deploys Thousands of Agentic AI Agents Across Stores in Days—Not Months—As Google Cloud’s Gemini Enterprise Turns Retail Workflow Automation Into a Race Against Obsolescence
The Home Depot just compressed an 18-month enterprise AI rollout into days. On January 11, 2026, the company deployed autonomous AI agents to…
Sensor-to-Story: How Language Models Are Finally Learning to Read Your Body’s Raw Data—And Why Clinical Narratives Are the Missing Link Healthcare AI Forgot
Your therapist is about to get a translator they never knew they needed—and it speaks fluent heartbeat.
The 8-Second War Plan: Why Air Force DASH-2’s AI-Generated Courses of Action Just Made Human Military Oversight Mathematically Impossible
The Pentagon just proved that human commanders can’t keep up with AI warfare—and they’re deploying it anyway.
Inverse Scaling in Test-Time Compute: When More ML Reasoning Tokens Systematically Destroy Performance
The industry just spent billions convincing you that longer AI thinking equals better results. New research proves that’s…
The Compute-Optimal Blind Spot: Why Most ML Teams Are Still Wasting 40% of Training Budget on the Wrong Scaling Trade-Off
Your ML team probably burned through 40% of its training budget last quarter—and nobody noticed because the waste happened before a single GPU…