News Summary for February 12, 2026

Summary

Today’s AI news cycle is dominated by major strategic moves from frontier AI companies. Anthropic and OpenAI are now engaged in open political warfare, with Anthropic donating $20M to a super PAC opposing OpenAI’s regulatory positions ahead of the 2026 midterms. Meanwhile, Chinese AI lab z.ai (Zhipu) released GLM-5 as fully open-source under MIT license, a 744B parameter MoE model with novel “Slime RL” training that competes with closed frontier models. On the research front, a University of Chicago study shows GPT-5 achieves 100% legal formalism compliance versus 52% for federal judges, though experts debate whether rigid rule-following is actually desirable. Other significant developments include Amazon engineers openly preferring Claude Code over Amazon’s internal Kiro tool, Google detecting 100K+ prompt campaigns attempting to clone Gemini, and the Pentagon pushing AI companies to deploy on classified military networks.

Top 3 Articles

1. z.ai Launches Open-Source GLM-5 with Record-Low Hallucination Rate via ‘Slime RL’ Training

Source: VentureBeat / Reddit

Date: February 11-12, 2026

Detailed Summary:

Z.ai (formerly Zhipu AI) has released GLM-5, a 744B parameter Mixture-of-Experts model (40B active parameters) fully open-sourced under MIT license. The model was trained on 28.5 trillion tokens and uses an innovative open-source RL post-training framework called “Slime” that enables asynchronous reinforcement learning at scale.

Key Technical Details:

200K+ token context window with DeepSeek Sparse Attention integration
Achieves best-in-class performance among open-source models on reasoning, coding, and agentic tasks
Compatible with Claude Code, OpenClaw, and other agentic coding environments
Ranks #1 on Vending Bench 2 (long-term operational capability benchmark)
GGUF quantizations available via Unsloth for deployment

Benchmark Performance:

Benchmark	GLM-5	Claude Opus 4.5	GPT-5.2
SWE-bench Verified	77.8%	80.0%	76.2%
Terminal-Bench 2.0	56.2%	54.0%	54.2%
AIME 2026 I	92.7%	-	90.6%

The Slime framework (Apache-2.0) provides production-grade RL infrastructure connecting Megatron-LM with SGLang, supporting MoE models under various parallelism strategies. This release continues the trend of Chinese AI labs (following DeepSeek) producing competitive open-source alternatives to closed frontier models, with Yann LeCun notably commenting “the best open models are not coming from the West.”

2. GPT-5 Outperforms Federal Judges in Legal Reasoning Experiment

Source: SSRN / University of Chicago Law School / Hacker News

Date: February 2026

Detailed Summary:

A new paper titled “Silicon Formalism: Rules, Standards, and Judge AI” by Eric A. Posner and Shivam Saran at University of Chicago Law School demonstrates that GPT-5 achieved 100% adherence to legally correct outcomes in a choice-of-law experiment, compared to only 52% for federal judges.

Research Methodology: The study replicated a prior 2x2 factorial experiment originally conducted on 31 U.S. federal judges. Subjects were asked to determine whether Kansas or Nebraska law should apply to a tort claim, where the plaintiff would receive $750,000 under Nebraska law but only $250,000 under Kansas law (due to damage caps). The experiment manipulated victim sympathy levels through gruesome injury descriptions.

Key Findings:

GPT-5: 100% formalistic adherence across all conditions
Federal Judges: 52% followed the legally correct framework
Only 31% of judges applied the Kansas damage cap when legally required
Judges were influenced by sympathy for injured plaintiffs; GPT-5 was not
Gemini 3 Pro also achieved perfect formalistic adherence

Critical Nuance: The paper itself questions whether pure formalism is desirable, noting judges may intentionally exercise discretion to achieve equitable outcomes. The authors explicitly ask: “And does that mean that LLMs are becoming better than human judges or worse?”

Expert Reactions: Critics note this tests a narrow, mechanical legal question typically handled by law clerks, not the complex constitutional interpretation and value judgments that are the core of judicial work. One commenter observed: “Judges do what their name implies—make judgment calls. If LLMs give only one answer, no matter what nuances are at play, that sounds like they are failing to judge.”

3. Anthropic Donates $20M to PAC Opposing OpenAI on AI Regulation

Source: New York Times / CNBC / Techmeme

Date: February 12, 2026

Detailed Summary:

Anthropic has donated $20 million to Public First Action, a bipartisan 501(c)(4) political group, directly countering OpenAI-backed super PAC “Leading the Future” which has raised $125 million. This marks an unprecedented political divide between the two leading AI frontier labs.

The Battle Lines:

Anthropic/Public First Action: Advocates AI model transparency safeguards, federal governance framework with meaningful protections, opposing federal preemption of state laws, and targeted regulation on AI-enabled bioweapons and cyberattacks
OpenAI/Leading the Future: Favors national/federal AI regulation over state-by-state patchwork, less restrictive safety requirements, federal preemption of state laws, and faster development with fewer barriers

Political Context:

Public First Action plans to support 30-50 candidates (both R and D) in state and federal races
Immediate ad buys for Sen. Marsha Blackburn (R-TN) and Sen. Pete Ricketts (R-NE)
Leading the Future donors include Andreessen Horowitz (~~$62M), Greg Brockman’s family (~~$62M), Joe Lonsdale, and Ron Conway
White House AI czar David Sacks has publicly attacked Anthropic, calling them “principally responsible for the state regulatory frenzy”

Industry Implications: This institutionalizes the philosophical split between “move fast” (OpenAI) and “safety first” (Anthropic). The 2026 midterms are now effectively a referendum on AI’s future—regulated with safety guardrails or unleashed for maximum innovation speed. Poll data shows 80% of Americans want AI safety rules even if development slows, and 69% think government is “not doing enough to regulate AI.”

Summary#

Top 3 Articles#

1. z.ai Launches Open-Source GLM-5 with Record-Low Hallucination Rate via ‘Slime RL’ Training#

2. GPT-5 Outperforms Federal Judges in Legal Reasoning Experiment#

3. Anthropic Donates $20M to PAC Opposing OpenAI on AI Regulation#

Other Articles#

Summary

Top 3 Articles

1. z.ai Launches Open-Source GLM-5 with Record-Low Hallucination Rate via ‘Slime RL’ Training

2. GPT-5 Outperforms Federal Judges in Legal Reasoning Experiment

3. Anthropic Donates $20M to PAC Opposing OpenAI on AI Regulation

Other Articles