From January 2015, she started to practice leetcode questions; she trains herself to stay focus, develops "muscle" memory when she practices those questions one by one.
2015年初, Julia开始参与做Leetcode, 开通自己第一个博客. 刷Leet code的题目, 她看了很多的代码, 每个人那学一点, 也开通Github, 发表自己的代码, 尝试写自己的一些体会.
She learns from her favorite sports – tennis, 10,000 serves practice builds up good memory for a great serve. Just keep going.
Hard work beats talent when talent fails to work hard.
Sunday, January 3, 2021
INTC equity research: Intel To Acquire SigOpt, An AI Hyperparameter Optimization Platform
Intel has confirmed that it is buying SigOpt Inc., an artificial intelligence startup developing software platforms to optimize AI models.
Intel has confirmed that it is buying SigOpt Inc., an artificial intelligence startup developing software platforms to optimize AI models. Several private firms and research groups such as OpenAI use these software platforms to boost their AI models’ performance. This platform uses a hyperparameter optimization method that improves model performance.
Developers say Hyperparameters are settings that determine how AI processes data. These settings include the number of artificial neurons in a model and how those neurons interact with each other. Hyperparameter optimization is the process of fine-tuning these settings to enhance the model’s performance.
A large number of setting combinations are possible for a broad AI, making the task time-consuming. In past approaches, hyperparameters were searched in a semi-randomized manner to find the optimal configuration. SigOpt employs a statistical method called Bayesian optimization that enables its platform to perform the process significantly. This platform can work with various AI types, including machine learning models and complex deep learning models. Through this platform, the developers can specify their AI’s property they need to improve and then create an optimization loop that fine-tunes it automatically. This platform also allows developers to regulate multiple properties simultaneously.
Using SigOpt’s platform, Intel will broaden its capability to help customers run AI models on its chips to achieve higher processing speeds. Intel says that SigOpt’s technology will be integrated across Intel’s AI hardware products.
In 2019, Intel’s AI solutions drive was reported to total over $3.8 billion. Intel is currently preparing the Xe series launch, its first graphic processing unit line in two decades, including AI-optimized chips. Intel Capital, its global investment organization, had committed a total of $132 million to 11 startups centered on AI translation services, chipset design, big data analytics, and health care automation. Intel Capital has also stated that it will be investing between $300 million and $500 million in AI centered startups with specific attention on intelligent edge devices and network transformation.