Results for “context engineering”

…reactions to a very successful GPT 5.5 model launch. But in context they mark a very noteworthy reaction that you, dear reader, should probably be alerted to if you aren’t already taking this extremely seriously. The proximal trigger for…

…strengths and interests. Projects include data collection and engineering, pre-training and some fine-tuning, and agents built with both internal and external models. Evaluation separates three questions that are easy to conflate: - Is the …

…of Large Language Models: Typically, training LLMs with long context sizes is computationally expensive, requiring extensive training hours and GPU resources. Existing long-context extension methods usually need additional tra... ▷ #general…

…a poor investment for most applications. The main expense is engineering time and slower iteration. Setting up training is estimated to take at least a couple of weeks from a competent engineer, or months for complex reinforcement learning …

…model with 40B parameters, over 20T tokens, with MLA for long context efficiency. Hugging Face MCP Course: @reach_vb announced Hugging Face has dropped the MCP Course, covering everything you need to know about Model Context Protocol and…

…3. Withhold the commit message. 4. Ask the system to retrieve context, infer the intended change, and iterate until the tests pass. This makes software work a masked prediction problem: recover both the missing implementation and the…

…multimodal dense model under Apache 2.0, with 262K native context extendable to 1M via YaRN, while also highlighting the already-released Qwen3.8-2.4T-A95B max-tier model (announcement, perf thread). The 27B model is notable because it is…

…A virtual-cell model might identify a target that protein engineering can address, while patient representations could connect cellular predictions to clinical outcomes. Xaira aims to improve drug-development success rates and halve…

…& Updates Mistral AI released a new 7B 0.2 base model with 32k context window, announced at a hackathon (13k views) Quantized 4-bit Mistral 7B models released, enabling 2x faster inference with 70% less VRAM using QLoRA finetuning (14k…

…Award with Yoshua Bengio and Geoffrey Hinton for conceptual and engineering breakthroughs in deep neural networks. His later research agenda proposes self-supervised world models that support prediction, reasoning, and planning. LeCun is a …

…(Apache 2.0), and support for 119 languages with a 32K–128K context. Initial results show Qwen3 models are competitive for their size class, with the 253B-A22B model approaching DeepSeek R1’s GPQA score @ArtificialAnlys. They also…

…than establishing that every stage had been delivered. His engineering emphasis extended beyond individual AI capabilities. Azhnyuk described a long tail of edge cases and a substantial gap between a prototype, a system ready for production…