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REDWOOD CITY, Calif., Sept. 25, 2025 /PRNewswire/ -- MiroMind, the open-source initiative founded by entrepreneur and philanthropist Tianqiao Chen, has achieved the top ranking on the FutureX benchmark, the world's first real-time test of AI's ability to predict unfolding events. MiroMind's agent framework, Miroflow, rose from sixth place in August to first in September, surpassing leading international competitors.
FutureX, developed by a global consortium including Stanford, Princeton, and Fudan, measures how well AI agents anticipate real-world outcomes—from stock market shifts to election results to technology trends. Unlike static benchmarks, FutureX evaluates reasoning and adaptability in dynamic environments.
"The first paradigm of AI was about general knowledge and subject-less reasoning. The new paradigm requires subjects—agents with memory, identity, and goals," said Chen. "MiroMind is building large models around long-term memory, so AI can make better predictions and ultimately better decisions. We want an AI that reflects people, not replaces them."
While LLMs generate content from general knowledge, MiroMind integrates subject data—individualized, contextual, multimodal, long-term memory—to reason, predict, and converge on the best decisions for each subject.
Chen created the Tianqiao and Chrissy Chen Institute nearly ten years ago and has built out a strategic ecosystem which aims to advance the use of technology such as AI to advance our understanding of the human brain and aspects of human intelligence that can lead to better artificial intelligence. The Institute partners with universities and other organizations around the world. Together, these efforts form a human-centered, AI-powered intelligence platform built on the principles of memory, prediction, and reflection.
About MiroMind
MiroMind is an open-source AI initiative dedicated to building Predictive Large Model as the basis for safe, evolving, and community driven artificial intelligence. Its mission is to create agentic systems that can reason, predict, and collaborate with humans in complex environments. Follow us on X at @miromind_ai. Learn more at https://miromind.ai/. On Github at https://github.com/MiroMindAI or on Hugging Face at https://huggingface.co/miromind-ai.
REDWOOD CITY, Calif., Sept. 25, 2025 /PRNewswire/ -- MiroMind, the open-source initiative founded by entrepreneur and philanthropist Tianqiao Chen, has achieved the top ranking on the FutureX benchmark, the world's first real-time test of AI's ability to predict unfolding events. MiroMind's agent framework, Miroflow, rose from sixth place in August to first in September, surpassing leading international competitors.
FutureX, developed by a global consortium including Stanford, Princeton, and Fudan, measures how well AI agents anticipate real-world outcomes—from stock market shifts to election results to technology trends. Unlike static benchmarks, FutureX evaluates reasoning and adaptability in dynamic environments.
"The first paradigm of AI was about general knowledge and subject-less reasoning. The new paradigm requires subjects—agents with memory, identity, and goals," said Chen. "MiroMind is building large models around long-term memory, so AI can make better predictions and ultimately better decisions. We want an AI that reflects people, not replaces them."
While LLMs generate content from general knowledge, MiroMind integrates subject data—individualized, contextual, multimodal, long-term memory—to reason, predict, and converge on the best decisions for each subject.
Chen created the Tianqiao and Chrissy Chen Institute nearly ten years ago and has built out a strategic ecosystem which aims to advance the use of technology such as AI to advance our understanding of the human brain and aspects of human intelligence that can lead to better artificial intelligence. The Institute partners with universities and other organizations around the world. Together, these efforts form a human-centered, AI-powered intelligence platform built on the principles of memory, prediction, and reflection.
About MiroMind
MiroMind is an open-source AI initiative dedicated to building Predictive Large Model as the basis for safe, evolving, and community driven artificial intelligence. Its mission is to create agentic systems that can reason, predict, and collaborate with humans in complex environments. Follow us on X at @miromind_ai. Learn more at https://miromind.ai/. On Github at https://github.com/MiroMindAI or on Hugging Face at https://huggingface.co/miromind-ai.
** The press release content is from PR Newswire. Bastille Post is not involved in its creation. **
MiroMind's Open Deep Research Framework Tops FutureX Benchmark, Heralds a New Paradigm in AI
SAN MATEO, Calif., Dec. 13, 2025 /PRNewswire/ -- AI infrastructure company EverMind has recently released EverMemOS, an open-source Memory Operating System designed to address one of artificial intelligence's most profound challenges: equipping machines with scalable, long-term memory.
The Memory Bottleneck
For years, large language models (LLMs) have been constrained by fixed context windows, a limitation that causes "forgetfulness" in long-term tasks. This results in broken context, factual inconsistencies, and an inability to deliver deep personalization or maintain knowledge coherence. The issue extends beyond technical hurdles; it represents an evolutionary bottleneck for AI. An entity without memory cannot exhibit behavioral consistency or initiative, let alone achieve self-evolution. Personalization, consistency, and proactivity, which are considered the hallmarks of intelligence, all depend on a robust memory system.
There is a consensus that memory is becoming the core competitive edge and defining boundary of future AI. Yet existing solutions, such as Retrieval-Augmented Generation (RAG) and fragmented memory systems, remain limited in scope, failing to support both 1-on-1 companion use cases and complex multi-agent enterprise collaboration. Few meet the standard of precision, speed, usability, and adaptability required for widespread adoption. Equipping large models with a high-performance, pluggable memory module remains a core unmet demand across AI applications.
Discoverative Intelligence
"Discoverative Intelligence" is a concept proposed in late 2025 by entrepreneur and philanthropist Chen Tianqiao. Unlike generative AI, which mimics human output by processing existing data, Discoverative Intelligence describes an advanced AI form that actively asks questions, forms testable hypotheses, and discovers new scientific principles. It prioritizes understanding causality and underlying principles over statistical patterns, a shift Chen argues is essential to achieving Artificial General Intelligence (AGI).
Chen contrasted two dominant AI development paths: the "Scaling Path," which relies on expanding parameters, data, and compute power to extrapolate within a search space, and the "Structural Path," which focuses on the "cognitive anatomy" of intelligence and how systems operate over time.
Discoverative Intelligence falls into the latter category, built on a brain-inspired model called Structured Temporal Intelligence (STI) that requires five core capabilities in a closed loop: neural dynamics (sustained, self-organizing activity to keep systems "alive"), long-term memory (storing and selectively forgetting experiences to build knowledge), causal reasoning (inferring "why" events occur), world modeling (an internal simulation of reality for prediction), and metacognition & intrinsic motivation (curiosity-driven exploration, not just external rewards).
Among these capabilities, long-term memory serves as the vital link between time and intelligence, highlighting its indispensable role in the path toward achieving true AGI.
EverMind's Answer
EverMemOS is EverMind's answer to this need: an open-source Memory Operating System designed as foundational technology for Discoverative Intelligence. Inspired by the hierarchical organization of the human memory system, EverMemOS features a four-layer architecture analogous to key brain regions: an Agentic Layer (task planning, mirroring the prefrontal cortex), a Memory Layer (long-term storage, like cortical networks), an Index Layer (associative retrieval, drawing from the hippocampus), and an API/MCP Interface Layer (external integration, serving as AI's "sensory interface").
The system delivers breakthroughs in both scenario coverage and technical performance. It is the first memory system capable of supporting both 1-on-1 conversation use cases and complex multi-agent enterprise collaboration. On technical benchmarks, EverMemOS achieved 92.3% accuracy on LoCoMo (a long-context memory evaluation) and 82% on LongMemEval-S (a suite for assessing long-term memory retention), significantly surpassing prior state-of-the-art results and setting a new industry standard.
The open-source version of EverMemOS is now available on GitHub, with a cloud service version to be launched late this year. The dual-track model, combining open collaboration with managed cloud services, aims to drive industry-wide evolution in long-term memory technology, inviting developers, enterprises, and researchers to contribute to and benefit from the system.
About EverMind
EverMind is redefining the future of AI by solving one of its most fundamental limitations: long-term memory. Its flagship platform, EverMemOS, introduces a breakthrough architecture for scalable and customizable memory systems, enabling AI to operate with extended context, maintain behavioral consistency, and improve through continuous interaction.
To learn more about EverMind and EverMemOS, please visit:
Website: https://evermind.ai/
GitHub: https://github.com/EverMind-AI/EverMemOS
X: https://x.com/EverMindAI
Reddit: https://www.reddit.com/r/EverMindAI/
** The press release content is from PR Newswire. Bastille Post is not involved in its creation. **
AI Infrastructure Company EverMind Released EverMemOS, Responding to Profound Challenges in AI
