venturebeat
MIT’s new ‘recursive’ framework lets LLMs process 10 million tokens without context rot

Recursive language models (RLMs) are an inference technique developed by researchers at MIT CSAIL that treat long prompts as an external environment to the model. Instead of forcing the entire prompt into the model's context window, the framework allows the LLM to programmatically examine, decompose, and recursively call itself over snippets of the text.Rather than expanding context windows or summarizing old information, the MIT team reframes long-context reasoning as a systems problem. By letting models treat prompts as something they can inspect with code, recursive language models allow LLMs to reason over millions of tokens without retraining. This offers enterprises a practical path to long-horizon tasks like codebase analysis, legal review, and multi-step reasoning that routine [...]

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venturebeat
DeepSeek drops open-source model that compresses text 10x through images, defying conventions

DeepSeek, the Chinese artificial intelligence research company that has repeatedly challenged assumptions about AI development costs, has released a new model that fundamentally reimagines how large l [...]

Match Score: 153.68

venturebeat
GAM takes aim at “context rot”: A dual-agent memory architecture that outperforms long-context LLMs

For all their superhuman power, today’s AI models suffer from a surprisingly human flaw: They forget. Give an AI assistant a sprawling conversation, a multi-step reasoning task or a project spanning [...]

Match Score: 151.84

venturebeat
How DeepSeek’s radical architecture is shattering Silicon Valley's token moat

DeepSeek’s announcement over the weekend that it has made its 75% price cut permanent on its flagship V4 Pro model is a disruptive assault on the capital-heavy business models of Silicon Valley’s [...]

Match Score: 137.46

venturebeat
How RecursiveMAS speeds up multi-agent inference by 2.4x and reduces token usage by 75%

One of the key challenges of current multi-agent AI systems is that they communicate by generating and sharing text sequences, which introduces latency, drives up token costs, and makes it difficult t [...]

Match Score: 120.64

venturebeat
ACE prevents context collapse with ‘evolving playbooks’ for self-improving AI agents

A new framework from Stanford University and SambaNova addresses a critical challenge in building robust AI agents: context engineering. Called Agentic Context Engineering (ACE), the framework automat [...]

Match Score: 120.62

venturebeat
Open source Xiaomi MiMo-V2.5 and V2.5-Pro are among the most efficient (and affordable) at agentic 'claw' tasks

Xiaomi, the Chinese firm best known for its smartphones and electric vehicles, has lately been shipping some incredibly affordable and high-powered open source AI large language models.The trend conti [...]

Match Score: 114.29

venturebeat
Samsung AI researcher's new, open reasoning model TRM outperforms models 10,000X larger — on specific problems

The trend of AI researchers developing new, small open source generative models that outperform far larger, proprietary peers continued this week with yet another staggering advancement.Alexia Jolicoe [...]

Match Score: 109.16

venturebeat
Vercel breach exposes the OAuth gap most security teams cannot detect, scope or contain

One employee at Vercel adopted an AI tool. One employee at that AI vendor got hit with an infostealer. That combination created a walk-in path to Vercel’s production environments through an OAuth gr [...]

Match Score: 99.75

venturebeat
Miami startup Subquadratic claims 1,000x AI efficiency gain with SubQ model; researchers demand independent proof.

A little-known Miami-based startup called Subquadratic emerged from stealth on Tuesday with a sweeping claim: that it has built the first large language model to fully escape the mathematical constrai [...]

Match Score: 97.94