We’re excited to announce the fifth major update to Charlie Mnemonic, your open-source AI assistant with Long-Term Memory. This release brings groundbreaking features, including Chain-of-Thought reasoning and an integrated Recall system that allows you to effortlessly search and reference past.
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We are announcing major updates for Charlie Mnemonic, your AI assistant with Long-Term Memory that’s getting smarter and more capable every day. We’ve been working hard to integrate new features and improve existing ones, and we are excited to share.
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A Standardization Release: The main purpose of the GoodAI LTM Benchmark has always been to serve as an objective measure for our progress in the development of agents capable of continual and life-long learning.
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At GoodAI, we are committed to developing agents that are capable of continual and life-long learning. As part of our efforts, we have previously open-sourced the GoodAI LTM Benchmark, a suite of tests aimed to evaluate the Long-Term Memory (LTM).
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As part of our research efforts in continual learning, we are open-sourcing Charlie Mnemonic, the first personal assistant (LLM agent) equipped with Long-Term Memory (LTM).
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As part of our research efforts in the area of continual learning, we are open-sourcing a benchmark for testing agents’ ability to perform tasks involving the advanced use of the memory over very long conversations.
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This article unfolds a five-stage evolution of gaming, each building upon the previous innovations and technological breakthroughs, significantly reshaping the gaming experience and its societal impact. From intelligent NPCs to immersive neural interfaces, we will explore how each stage contributes.
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At GoodAI, we are deeply committed to the advancement of safe AGI. Large language models (LLMs) undoubtedly offer significant power, but on their own, they have limitations — notably, the inability to learn new skills post-deployment. It's here that our.
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At GoodAI, we are dedicated to pushing the boundaries of artificial intelligence. Our current focus is on the development of Large Language Model (LLM)-based agents with personalities that go beyond simple conversations, and instead exhibit LLM-driven behaviors, interacting with humans.
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Investigating the underlying mechanisms of memetics and collective intelligence through FlatWorld's 2D environment.
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