Fable 5 IS BACK? GPT 5.6 & Gemini 3.5 Pro Delayed, NEW OpenAI AI Chip, & QWEN STEALING! AI NEWS

2026-06-25 · Source: WorldofAI · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, Cybersecurity & Data Privacy · Depth: Intermediate, long

Summary

Anthropic's Claude Fable 5 is anticipated to return by July 31st, with Polymarket odds surging to over 90% following sightings in Amazon Bedrock and Claude code v2.1.19 updates. Its prior removal was due to its Mythos model identifying vulnerabilities in sensitive US government systems during Project Last Think testing, reportedly breaking into classified systems in hours. Concurrently, Anthropic accuses Alibaba and other Chinese AI labs of a "largest AI theft attack," involving 25,000 fraudulent accounts and 28.8 million Claude exchanges for model distillation. Meanwhile, Google DeepMind faces talent departures and a delayed Gemini 3.5 Pro, with new checkpoints reportedly underperforming Gemini 3.1 Pro. OpenAI released a GPT 5.5 Instant update and delayed GPT 5.6 to July, while also unveiling Halpino, its first custom AI chip for LLM inference, designed in 9 months with ChatGPT's aid, aiming for deployment by late 2026. Other developments include Anthropic's Claude tag for Slack, Mistral's OCR4 for structured document extraction, and the open-source Ornit 1.0 LLM family for agent coding.

Key takeaway

For AI Engineers and strategists evaluating model deployment or IP protection, be aware that advanced AI capabilities can expose critical system vulnerabilities, as seen with Claude Mythos. Your organization must implement robust security testing protocols for frontier models and guard against distillation attacks, which Anthropic alleges are occurring at an industrial scale. Consider OpenAI's move into custom AI chips as a long-term strategy to control compute economics and reduce reliance on external GPU providers.

Key insights

AI model capabilities can pose national security risks and drive industrial-scale espionage.

Principles

• Frontier models require robust security testing.
• AI chip development reduces external GPU dependency.
• Model distillation poses significant IP theft risk.

Method

Model distillation involves using frontier model outputs to train a competing model at reduced cost, often via fraudulent API access.

In practice

• Integrate AI assistants directly into team workflows.
• Use OCR models for complex document structure extraction.
• Explore open-source LLMs for agentic coding tasks.

Topics

• AI Model Security
• Model Distillation
• Custom AI Chips
• LLM Performance
• Open-source LLMs
• Anthropic Claude

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Related on AIssential

• Anthropic accuses DeepSeek, Moonshot, and MiniMax of "industrial-scale distillation attacks". — AI development faces critical challenges in intellectual property protection, ethical data use, and robust model evaluation amidst rapid technological advancements.
• Attackers prompted Gemini over 100,000 times while trying to clone it, Google says — Model extraction via extensive prompting is a common method for AI model distillation and intellectual property theft.
• not much happened today — The AI industry is rapidly integrating hardware, software, and agentic systems, intensifying competition and raising new infrastructure and security challenges.
• White House reins in OpenAI's GPT-5.6 — Government oversight is emerging as a critical gatekeeper for releasing powerful, "Mythos-level" AI models to the public.
• Did Alibaba Illegally Extract Anthropic’s AI Capabilities? — Model extraction attacks exploit knowledge distillation to illicitly replicate proprietary AI model capabilities, raising significant IP concerns.
• Anthropic Paid $1.5B for Pirated Data — Frontier AI labs are reporting coordinated, large-scale distillation attacks by foreign entities to extract model capabilities.

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Editorial summary, takeaway, and curation by AIssential. Original article published by WorldofAI.