Intelligence,’ a term he coined 1/62: Arthur Samuel, an IBM computer scientist, creates a self-learning program that proves capable of defeating a top USA checkers champion AI ‘Winter1’ (1967-1996) Trending = Unprecedented37 Machine-Learning Model* Trending = In 2015... Industry Surpassed Academia as Data + Compute + Financial Needs Rose *Machine Learning = A subset of AI where machines learn AI Index data provider, uses the term ‘notable machine learning models’ to designate particularly influential models within the AI/machine learning ecosystem. Epoch maintains a database of 900 AI models

corpus consisting of 8.1T tokens, and further perform Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) to fully unlock its potential. Evaluation results show that, even with only 21B activated parameters Fine-Tuning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 4.2 Reinforcement Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 4.3 Evaluation Results . demon- strate our efforts in alignment, encompassing Supervised Fine-Tuning (SFT), Reinforcement 5 Learning (RL), the evaluation results, and other discussion (Section 4). Finally, we summarize the conclusion

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 automated end-to- end optimization framework for deep learning.TVM Stack High-Level Differentiable IR Tensor Expression and Optimization Search Space LLVM, CUDA, Metal VTA Edge FPGA Cloud FPGA FPGA ASIC Optimization AutoTVM Device FleetExisting Deep Learning Frameworks High-level data flow graph Hardware Primitive Tensor operators such as Conv2D eg. cuDNN Offload to heavily optimized

. . . . . . 7 2.3.2 监督微调（Supervised Fine-Tuning, SFT） . . . . . . 7 2.3.3 强化学习（Reinforcement Learning, RL） . . . . . . . 7 3 DeepSeek-R1 精华图解 . . . . . . . . . . . . . . . . . . . . . . . 7 3.1 DeepSeek-R1 据集，让模型在特定任务上优化表现。调整参数，使其更符合人类需求，如 问答、对话生成等任务。 2.3.3 强化学习（Reinforcement Learning, RL） 采用强化学习（RL）方法进行优化，主要通过人类反馈强化学习（RLHF, Reinforcement Learning from Human Feedback）： 强化学习（RLHF）优化过程 • 步骤 1：人类标注者提供高质量回答。 • 虽然展现出惊人的推理能力提升，但是也出现了回复时 语言混合，非推理任务回复效果差的问题，为了解决这些问题，DeepSeek 提出通用强化学习训练框架。 如图7所示，通用强化学习（General Reinforcement Learning）基于 SFT- checkpoint，模型进行通用强化学习（RL）训练，优化其在推理任务和其他 教程作者：郭震，工作 8 年目前美国 AI 博士在读，公众号：郭震 AI，欢迎关注获取更多原创教程。资

the model uses to predict a specific output. You don’t need to be a data scientist or a machine learning engineer – everyone can write a prompt. However, crafting the most effective prompt can be complicated model’s ability to provide meaningful output. You don’t need to be a data scientist or a machine learning engineer – everyone can write a prompt. Prompt Engineering February 2025 7 When you chat with temperature control can be understood in a similar way to the softmax function used in machine learning. A low temperature setting mirrors a low softmax temperature (T), emphasizing a single, preferred

accepting inefficient processes as a cost of doing business. 21 AI in the EnterpriseConclusion Learning from each other As the previous examples show, every business is full of opportunities to harness every workflow. They’re aligning around high-return, low-effort use cases, learning as they iterate, then taking that learning into new areas. The results are clear and measurable: faster, more accurate

16th, 2019Bringing together the Arm ecosystemLinaro AI Initiative Provide the best-in-class Deep Learning performance by leveraging Neural Network acceleration in IP and SoCs from the Arm ecosystem, through

Symbols NNVM & Param Frontends Operators Algorithm &Schedule CUDA TOPI Backends Machine Learning Automated Optimizer Schedule explorer Cost model Mali TOPI ROCM TOPI PVRTOPI Alibaba Al.Labs

orMicrosof Apple Qualcomm 40+ years of combined experience in computer systems design and machine learning tr tvm 。 @zxnet 和os 全 W Open Source at OctoML ee We are big believers in the power

Compiler Tensor Graph Optimization Framework Tensor Graph to Xilinx Tensor Graph Frontend Deep Learning Frameworks https://github.com/xilinx© Copyright 2018 Xilinx TVM as Unified ML Front End >> 6