ZeroSlop — September 2, 2026
Today: Anthropic's Claude Fable 5.1 and Mythos 5.1 Arrive…; Anthropic launches Claude Fable 5.1 and says…; OpenAI delayed its new model’s development after the…
12 stories worth knowing about today — AI breakthroughs, launches, and innovations making a difference.
1. Anthropic’s Claude Fable 5.1 and Mythos 5.1 Arrive With a 75% Cost Reduction For Fable Cache Reads
Slashdot
Anthropic has released Claude Fable 5.1 and Mythos 5.1, two versions of the same underlying model aimed at longer-running agentic work. “For enterprise buyers, however, the release is about more than another round of benchmark gains,” reports VentureBeat. “Anthropic is simultaneously changing the ec…
2. Anthropic launches Claude Fable 5.1 and says it’s up to 45 percent cheaper for agentic work
The Verge AI
Anthropic says its newest AI models, Fable 5.1 and Mythos 5.1, address criticisms from customers about price, data retention, and overzealous safeguards. The company claims Claude Fable 5.1 offers stronger performance than Fable 5, but costs around 25 percent less typically and up to 45 percent less…
3. OpenAI delayed its new model’s development after the Hugging Face hack
The Verge AI
After an unreleased OpenAI model wreaked enough havoc to make international headlines, OpenAI delayed the development of a different unreleased model suite, Astra, in order to shore up its safety work, the company wrote Tuesday in a blog post. In July, an unreleased OpenAI model broke out of its res…
4. Codex bundles LibreOffice
Simon Willison
I was poking around in my ~/.cache/ folder using OmniDiskSweeper when I spotted something interesting. The OpenAI Codex desktop app (since rebranded to just ChatGPT) has 1.7GB of stuff in there in a folder called codex-primary-runtime , including a full Python installation, a full Node.js installati…
5. AIR raises $50M to help companies vet the skills and add-ons AI agents use
TechCrunch AI
AIR’s platform can discover agents running at a company, continuously vets any skills and add-ons they use, and blocks any unwanted behavior….
6. Long-Horizon State Tracking in LLMs: Executing MD5 through a Deep Sequence of Dependent Tool Calls
arXiv CS.AI
arXiv:2609.00012v1 Announce Type: new Abstract: Long-horizon tasks remain uncommon in large language model (LLM) evaluation, and for a reason: when each step depends on the last, per-step accuracy that looks excellent in isolation decays catastrophically, as errors cascade and the end-to-end failur…
7. OpenAgentFlow: Enabling System-Wide Safety Boundaries for Heterogeneous AI Agent Fleets
arXiv CS.AI
arXiv:2609.00015v1 Announce Type: new Abstract: AI agents powered by large language models are evolving from isolated assistants into heterogeneous systems in which multiple agents, planners, controllers, and execution backends operate over the same user or enterprise environment. In such settings,…
8. UI-Venus-2 Technical Report
arXiv CS.AI
arXiv:2609.00028v1 Announce Type: new Abstract: Multimodal GUI agents have emerged as a promising paradigm for digital task automation, yet transitioning from benchmark-oriented models to dependable real-world applications remains challenging due to limited environment coverage, brittle task constr…
9. AI Morbidity and Mortality: A Framework for Clinical AI Failure Review
arXiv CS.AI
arXiv:2609.00076v1 Announce Type: new Abstract: Clinical artificial intelligence is increasingly embedded in real-world care, yet existing safety mechanisms are poorly suited to reconstructing and learning from individual AI-related errors and near-misses. Aggregate model monitoring can identify pe…
10. Deploying and Evaluating a Smart-Agriculture Agentic Engine for Full-Season Soybean Farm Operations
arXiv CS.AI
arXiv:2609.00106v1 Announce Type: new Abstract: This paper presents FAIRY, a full-stack smart-agriculture agent system developed for and deployed to an operating soybean research farm at Harbin Institute of Technology’s smart-agriculture site. We develop FAIRY to execute and evaluate agentic agrono…
11. AI Should Not Only Be Helpful. It Should Be Contingent. Artificial Intimacy, Sycophancy, and the Future of Social Learning
arXiv CS.AI
arXiv:2609.00211v1 Announce Type: new Abstract: Conversational artificial intelligence is increasingly embedded in everyday social environments, where it functions as both an informational tool and a source of interpersonal feedback. This perspective introduces contingency, i.e., the degree to whic…
12. Learning What to Retain: Gated-Memory Routing for Efficient Collaboration in Multi-Agent LLM Systems
arXiv CS.AI
arXiv:2609.00237v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems tackle complex reasoning by orchestrating how multiple agents are configured and how they collaborate. A central challenge is to adapt orchestration to the evolving collaboration state. Routing from…