讨论和批判性思维的活动这项新兴技术的缺点和可能性对人工智能社会和道德影响的调查通过实践活动将人工智能与年级相关的应用到学生生活中探索为所有年龄、能力和技术经验水平的学生设计的免费课程、教程和活动————————————这个系列是《What is AI?》介绍什么是人工智能以及它是如何工作的学生将从清楚地了解什
In 2012, Hinton and two of his students highlighted the power of deep learning. They applied Hinton’s algorithm to neural networks with many more layers than was typical, sparking a new focus on deep neural networks. These have been the main AI approaches of recent years. ...
At its core, an algorithm is a process or set of rules to be followed in calculations or other problem-solving operations. Common examples of rule-based algorithms include if-then statements, which can often be found in simple spreadsheets. For auditors, these three real-world examples highligh...
Greedy algorithm.This algorithm solves optimization problems by finding the locally optimal solution, hoping it is the optimal solution at the global level. However, it does not guarantee the most optimal solution. Recursive algorithm.This algorithm calls itself repeatedly until it solves a problem. R...
know-how. In many cases, this knowledgediffers from that needed to build non-AI software. For example, building and deploying a machine learning application involves a complex, multistage and highly technical process, from data preparation to algorithm selection to parameter tuning and model testing...
Eventually, it is able to automatically identify ketchup bottles even in photos it has never seen before. Machine learning relies on the use of predefined processes called algorithms. A machine learning program will "learn" slightly differently depending on how the algorithm is set up. Machine ...
The algorithm would then learn from this labeled collection of images to distinguish the shapes and their characteristics: in this case, circles don't have corners, and squares have four equal-length sides. The system can then see a new image and determine the shapes. ...
Computational PowerModerate; runs on standard processors.Requires more power than AI but is manageable.High; needs GPUs, TPUs, or cloud computing. InterpretabilityTransparent, based on predefined rules.Somewhat interpretable depending on the algorithm.Often a "black box" due to complex neural layers....
While scientists can take many approaches to building AI systems, machine learning is the most widely used today. This involves getting a computer toanalyze datato identify patterns that can then be used to make predictions. The learning process is governed byan algorithm— a sequence of instructi...
The learning process can besupervisedorunsupervised, depending on how the data is presented and what the AI programming is meant to achieve. Withsupervised learning, the AI model learns from a dataset that includes both the input and the desired output. Withunsupervised learning, the algorithm iden...