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reacted to ajibawa-2023's post with πŸ‘ about 1 hour ago
Go-Code-Large Dataset: https://huggingface.co/datasets/ajibawa-2023/Go-Code-Large Go-Code-Large is a large-scale corpus of Go (Golang) programming language source code, comprising 316,427 code samples stored in .jsonl format. The dataset is designed to support research and development in large language model (LLM) pretraining, static analysis, cloud-native systems, and modern backend software engineering. By offering a focused and curated dataset for Go, this corpus enables experimentation in concurrent programming, distributed systems, and performance-oriented backend servicesβ€”domains where Go is widely adopted. Go-Code-Large addresses the relative scarcity of large, language-specific datasets for Go, enabling targeted research into idiomatic Go patterns, concurrency primitives, and scalable system design.
reacted to mrmanna's post with πŸ‘€ about 2 hours ago
π—”π—œ & π—¦π—§π—”π—§π—˜ π— π—”π—–π—›π—œπ—‘π—˜ 𝘞𝘩𝘺 π˜—π˜³π˜°π˜₯𝘢𝘀𝘡π˜ͺ𝘰𝘯 π˜‰π˜¦π˜¨π˜ͺ𝘯𝘴 𝘞𝘩𝘦𝘳𝘦 π˜›π˜°π˜Ί 𝘈𝘨𝘦𝘯𝘡𝘴 𝘌𝘯π˜₯ Published: 18 Apr 2026 | Towards AI Publication | Medium Open Link: https://medium.com/towards-artificial-intelligence/ai-state-machine-106387406c5a?sk=047b2f064c673a0095a9e8cc011b6a92 We talk a lot about governance, accuracy, and auditability in AI agents. But I keep seeing a gap between the words and the engineering behind them. Many agents have tools, orchestration, memory, graphs, and impressive demos. But when you ask how governance is actually enforced, the answer is often weak. Prompt-level control is not production governance. A production agent needs explicit state design: legal transitions, controlled progression, recovery paths, approval boundaries, and separation between memory, decision, policy, and execution. This article explores the silent crisis unfolding in modern AI development: the urgent need to resurrect the disciplined architecture of state machines
liked a model about 15 hours ago
MiniMaxAI/MiniMax-M2.7
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