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An embedded system is just a computer buried inside some other product. Surprisingly, you can know a great deal about programming and computing and still get lost in the arcane world of embedded systems. In the world of embedded systems programming, countless details — both hardware- and software-related — make the development process seem like a path that few have traveled and even fewer have survived. How do software, hardware, and firmware differ? How in the world does a 100,000-line program end up inside a device smaller than my fingernail? What is flash memory and why do I need a cache? What is the difference between a task and a process? Do I need to worry about reentrancy? As we progress through Embedded Systems Firmware Demystified, you will come to see that these questions are not as complex as they first appear. Embedded systems programming spans a wide range of activities from building programmable logic at the most concrete end to writing a UNIX™ process at the most abstract end. Bracketed by these poles, the industry has exploded in the last 20 years. In the late seventies, assemblers were considered luxuries. A typical embedded system used less than 64Kb of system memory (bits, not bytes!).

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大模型是人工智能的发展趋势和未来。大模型是“大算力+强算法”结合的产物。目前，大模型生态已初具规模。大模型能够实现 AI从“手工作坊”到“工厂模式”的转变，大模型通常是在大规模无标注数据上进行训练，学习出一种特征和规则，基于大模型进行应用开发时，将大模型进行微调，或者不进行微调，就可以完成多个应用场景的任务； 并且，大模型具有自监督学习能力，不需要或很少需要通过人工标注的数据进行训练，降低训练成本，因而能够加速 AI产业化进程，降低 AI 应用的门槛。另外，随着大模型不断地迭 代，大模型能够达到更强的通用性以及智能程度，从而使得 AI 能够更广泛地赋能各行业应用。我们认为，大模型是人工智能的发展趋势和未来。

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