OpenAI has released Symphony, an open-source framework designed to manage autonomous AI coding agents through structured ‘implementation runs.’ The project provides a system for automating software development tasks by connecting issue trackers to LLM-based agents. System Architecture: Elixir and the BEAM Symphony is built using Elixir and the Erlang/BEAM…

In this tutorial, we build an advanced Tree-of-Thoughts (ToT) multi-branch reasoning agent from scratch. Instead of relying on linear chain-of-thought reasoning, we design a system that generates multiple reasoning branches, scores each branch using a heuristic evaluation function, prunes weak candidates, and continues expanding only the strongest paths. We combine an instruction-tuned transformer model…

How can a trillion-parameter Large Language Model achieve state-of-the-art enterprise performance while simultaneously cutting its total parameter count by 33.3% and boosting pre-training efficiency by 49%? Yuan Lab AI releases Yuan3.0 Ultra, an open-source Mixture-of-Experts (MoE) large language model featuring 1T total parameters and 68.8B activated parameters. The model architecture is designed to optimize…

class EverMemAgentOS: def __init__( self, workdir: str = “/content/evermem_agent_os”, db_name: str = “evermem.sqlite”, embedding_model: str = “sentence-transformers/all-MiniLM-L6-v2”, gen_model: str = “google/flan-t5-small”, stm_max_turns: int = 10, ltm_topk: int = 6, consolidate_every: int = 8, consolidate_trigger_tokens: int = 1400, compress_target_chars: int = 420, seed: int = 7, ): self.workdir = workdir _ensure_dir(self.workdir) self.db_path = os.path.join(self.workdir, db_name)…

As AI development shifts from simple chat interfaces to complex, multi-step autonomous agents, the industry has encountered a significant bottleneck: non-determinism. Unlike traditional software where code follows a predictable path, agents built on LLMs introduce a high degree of variance. LangWatch is an open-source platform designed to address this by providing a standardized layer…

Current end-to-end robotic policies, specifically Vision-Language-Action (VLA) models, typically operate on a single observation or a very short history. This ‘lack of memory’ makes long-horizon tasks, such as cleaning a kitchen or following a complex recipe, computationally intractable or prone to failure. To address this, researchers from Physical Intelligence, Stanford, UC Berkeley, and MIT…