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Zip’s new AI agents want to stop your finance team from uploading contracts into personal ChatGPT accounts

Zip, the AI procurement platform valued at $2.2 billion, announced two products on Monday that mark a turning point in its evolution from procurement software to autonomous AI platform: a suite of five AI “Superagents” that can review contracts, code invoices, and negotiate with vendors inside Zip’s governance framework, and a procurement-native implementation of the …

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Anthropic’s browser agent got hijacked 31.5% of the time before safeguards engaged

Across the frontier labs, the highest prompt injection figures published this spring are Anthropic’s. Point a red-teamer at its newest model in a browser, and the attacker hijacked it 31.5% of the time before safeguards engaged. OpenAI, Google, and Meta never gave security leaders a comparable number to set beside it. That figure looks like …

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MiniMax-M3 debuts, eclipsing GPT-5.5 and Gemini 3.1 Pro on key benchmark performance for just 5-10% of the cost

Big news in enterprise AI broke over the weekend as Chinese AI startup MiniMax released its highly anticipated M3 large language model on Sunday evening Eastern time, pairing frontier-tier coding and agentic performance with a 1-million-token context window and native multimodality for a fraction of the cost of leading proprietary models, with pricing starting at …

MiniMax-M3 debuts, eclipsing GPT-5.5 and Gemini 3.1 Pro on key benchmark performance for just 5-10% of the cost Read More »

Claude Mythos exposed a hard truth: Your enterprise patching process is way too slow

In 2024, researchers from the University of Illinois found that GPT-4, when provided with a common vulnerabilities and exposures (CVE) description, could autonomously exploit 87% of a curated 15-vulnerability one-day dataset. Without the description, it could only exploit 7%. This provided a “margin of safety” for the industry because while AI could exploit known vulnerabilities, …

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The AI agent bottleneck isn’t model performance — it’s permissions

Enterprise AI agents are stalling — not because of model performance, but because of permissioning. Every agentic workflow eventually hits the same wall: what is this agent allowed to touch, on whose behalf, and how does the system know? Workday’s answer is to make its existing system of record the governance layer for agents. Gerrit …

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MIT’s MeMo lets teams swap in a better LLM without retraining — and performance jumps 26%

Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits. MeMo, a framework from researchers at multiple universities, encodes new knowledge into a dedicated smaller memory model that operates separately from the main LLM. The …

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Pinterest cut AI costs 90% by gutting a frontier model’s vision layer

At 620 million monthly users, calling a frontier model for every image recommendation isn’t a strategy — it’s a bill. Pinterest CTO Matt Madrigal solved it by gutting Qwen3-VL’s vision layer and rebuilding it with proprietary embeddings, cutting costs 90% and boosting accuracy 30%. Madrigal’s team has been heavily investing in customizing open-source models “foundationally …

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AI agents are entering their rebuild era as enterprises confront the reliability problem

As enterprise AI agents move into production, organizations are confronting a growing reliability problem. Many teams are discovering that LLM performance alone does not determine whether agents succeed in production. Long-running AI workflows must survive crashes, preserve state, recover from failures, manage inference costs, and coordinate across APIs, tools, and enterprise systems. After a first …

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Researchers automated LLM reasoning strategy design and cut token usage by 69.5%

Test-time scaling (TTS) has emerged as a proven method to improve the performance of large language models in real-world applications by giving them extra compute cycles at inference time. However, TTS strategies have historically been handcrafted, relying heavily on human intuition to dictate the rules of the model’s reasoning.  To address this bottleneck, researchers from …

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