Maddison Project 1100 1000 1300 1200 1400 1500 1600 1700 1800 1900 2000 Printing Press Steam Engines Telegraph Electrification Mass Steel Production Mass Production & Assembly Lines Internal Combustion 19th-century Britain, where he noticed that improvements in the efficiency of coal-powered steam engines were not reducing coal consumption but rather increasing it. In his book The Coal Question, he noted formation, bruising competition, and – eventually – clear-cut winners and losers. Alasdair Nairn’s ‘Engines That Move Markets’ (link here) distills two centuries of such cycles, and his observations are prescient

TVM: Where are we going Tianqi ChenCurrent Deep Learning Landscape Frameworks and Inference engines DL Compilers Kenrel Libraries Hardware CuDNN NNPack MKL-DNN Hand optimized Open source, automated

Implement a Python template to indicate if an op can be supported by your codegen ● Template path: python/tvm/relay/op/contrib/ /extern_op.py ● Boolean functions in the template def conv2d(attrs

). Prompt Engineering February 2025 65 We recommend creating a Google Sheet with Table 21 as a template. The advantages of this approach are that you have a complete record when you inevitably have to Prompt [Write all the full prompt] Output [Write out the output or multiple outputs] Table 21. A template for documenting prompts Summary This whitepaper discusses prompt engineering. We learned various

PARAMETER num_gpu 28 # 每块RTX 4090加载7层（共4卡） PARAMETER num_ctx 2048 PARAMETER temperature 0.6 TEMPLATE "<｜end▁of▁thinking｜>{{ .Prompt }}<｜end▁of▁thinking｜>" ollama create DeepSeek-R1-UD-IQ1_M -f DeepSeekQ1_Modelfile

prompts for distinct use cases, use a single flexible base prompt that accepts policy variables. This template approach adapts easily to various contexts, significantly simplifying maintenance and evaluation