Tag: ai

An AI syllabus for Primary & Secondary School Students

Investment in Artificial Intelligence has grown in recent years following advances in Deep Learning, graphics processing power and the wider adoption of open source technologies in businesses. The internet has been a major contributor to the growth of AI datasets that are needed to train neural networks. AI already plays an important part of lives today from job searching, social media, shopping online, down to the maps we use to find our way while driving.

Businesses are increasingly applying narrow forms of AI or automation to their workflows (AI that is trained for a specific task). The compounding effect is the way people work is expected to change significantly. There are pros and cons of introducing automation to a business process, researchers argue businesses should refine a workflow before automating it to reap the benefits. Inevitably this will mean human workers roles will change. There are advantages to this, the human worker may find automation will free up time for more unique complex tasks that keep them engaged. The current generation of AI is suited for repetitive tasks that often bog employees down from what people may consider ‘more meaningful work’.

It does however mean the current generation of workers may have to retrain to adapt to a new role in their organisation. Or if the organisation automates the entire workflow they may become unemployed. Workers from a non-technical background could struggle to adapt in this circumstance and may require assistance in retraining for a new role.

Leading analyst studies have identified that AI is expected to create more jobs than it replaces, however it will create a cultural shift on the types of skills that will be desired in a post-AI world. We will be living in an augmented intelligence world where we will collaborate alongside AI/automated systems. This can make us more efficient in the work we do.

China’s large trained workforce has enabled it to become one of the main manufacturing hubs of the world. It’s government has invested on massive infrastructure projects. It has become a proponent of AI and is introducing AI into many aspects of public interactions (some of questionable ethical use) and is described as an AI Superpower comparable to US tech companies (according to  Kai-fu Lee, former President of Google China).

The Paper, a China news agency announced China’s Education department has planned a 10 volume series of AI textbooks for Chinese primary and secondary school students.

Translation of the article: “The first set of artificial intelligence textbooks in the country will enter Elementary and High Schools next year, and will be welcomed by students in Shanghai”

The first national AI textbook covering elementary school to high school was unveiled in Shanghai.

This set of “The Future of AI on the AI” series plans to publish 10 volumes, and has already published six volumes. They are…
“Amazing Animals on AI”,
“Smart Life on AI”,
“AI in Deformation Workshop”,
“AI on Pets”,
“AI Super Engineer”,
“After Heroes of AI – Python”,
and the remaining four volumes…
“AI in the future town”,
“AI in the Wonderful World”,
“AI Super Designer”,
“Application and Exploration of AI”
will be published in the first half of 2019.

Hundreds of elementary and high schools across China will introduce this series as elective courses or school-based courses. Among them, more than 100 elementary and high schools in Shanghai Jiading and Kunming, Yunnan will become the first batch of “Excellent AI Education Model Schools”. After the spring of 2019, many schools in Shanghai Minhang, Yangpu, Jing’an, Huangpu, Baoshan and other districts will continue to use this series of textbooks.

Recently, at the “AI Future Intelligence Creator – Artificial Intelligence Education Seminar and ‘Artificial Intelligence Excellence Course Series” conference held by East China Normal University, the reporter of www.thepaper.cn was informed of the above news.

Artificial Intelligence textbooks for schools in China

“The Future AI on the AI – the series of artificial intelligence boutique courses in elementary and high schools” has published 6 volumes of cover photos. East China Normal University Press

The textbook has been preliminarily tested in some schools in Jiading, Shanghai.

“Why should elementary and high school students learn artificial intelligence knowledge in order to enable them to adapt to the era when robots are everywhere and artificial intelligence is everywhere.” Professor Wang Jiqing, editor-in-chief of the series and the Institute of Curriculum and Teaching, East China Normal University, said that the series is combined with China. The implementation status of artificial intelligence education in primary and secondary schools is a small junior high-through course system jointly developed by many scholars in education, experts in the field of artificial intelligence, managers in education departments, and first-line science and technology teachers.

The course organises the course content according to the differences in students’ cognitive ability and knowledge accumulation in different sections. Each volume is organised on a specific topic, each topic contains 12-14 subject courses and 2-4 active course content. The theme course revolves around the relevant knowledge of artificial intelligence, and the activity curriculum expands and extends the content of the theme course.

Wang Jiqing introduced that this set of artificial intelligence textbooks has been preliminarily tried in Shanghai Jiading No. 1 Middle School, Jiaotong University Middle School Jiading Branch and Jiading Youth Science and Technology Collection Center.
Jiading No. 1 Middle School, Jiaotong University Middle School Jiading Branch has been piloting the “AI behind the AI – Python” course.

Wang Yahua, president of Jiading Youth Science and Technology Center, said that since September this year, the Jiading Youth Science and Technology Center has also opened courses such as “Intelligent Life on AI” and “AI Super Engineer”. So far, it has covered thousands of primary and middle school students and children. Looking forward to such an interesting course, “Can the teacher come back tomorrow?”, “Can I talk to the principal every day?”… The children’s children’s words and expressions express their love for the innovative courses of artificial intelligence.

“We strive to make the artificial intelligence education covered by the whole school, so that the students’ learning experience can be solved from the the knowledgeable to the useful multiple iteration process, to achieve the goal of knowledge literacy and promotion.” What are the pain points? Wang Jiqing said that he hopes that students can complete the actual tasks and have direct experience and deep understanding of the connotation and extension of artificial intelligence, so as to better accept the basic knowledge of artificial intelligence, cultivate innovative thinking and enhance creation. ability.

“The development of artificial intelligence education still has difficulties”

In recent years, domestic support for the development of artificial intelligence education is obvious to all.

Experts attending the meeting introduced that in August 2017, the “New Generation Artificial Intelligence Development Plan” issued by the State Council clearly stated: Implementing the National Intelligence Education Project, setting up artificial intelligence related courses in the primary and secondary schools, and gradually promoting programming education; 2018 In January, the Ministry of Education announced that artificial intelligence, robots, etc. should enter the national high school curriculum.

“While the government strongly supports artificial intelligence education, we must also see that at present, the development of artificial intelligence education industry still has difficulties, such as the lack of a consistent intra-campus curriculum system, the lack of professional teachers, student learning evaluation and other supporting teaching resources, teaching The environment and teaching methods are too monotonous, etc. To this end, a number of experts have spent nearly five months, launching the “AI Future Creativity” course series, covering the teaching needs from elementary to high school.

“How to popularise artificial intelligence education in elementary and high schools is a very urgent task facing China. Many people are paying attention to the popularisation of artificial intelligence and paying attention to artificial intelligence education. It is very gratifying to see the textbooks based on robots covering the whole school.” Fan Lei, a member of the High School Information Technology Curriculum Standards Expert Group and a professor at Capital Normal University, said.

Wang Jian, deputy director of East China Normal University Press, said that as the country raises the development of new technologies such as artificial intelligence to a strategic height, Shanghai has built a process of “a globally influential science and technology center”, and the East China Normal University Press launched A group of books based on AI and STEAM education, “I hope that through our efforts, we will bring children a fun and innovative artificial intelligence education course.”

The Paper – Han Xiaorong (20/11/2018)

It demonstrates that China recognises the changing nature of work in the post AI age and is investing in it’s younger generations to make them competitive in the new age of AI and they will be more prepared than those that didn’t benefit from such training. Although I don’t agree with the way China chooses to apply AI technologies on it’s citizens I do believe AI will affect the way people work all over the world.

In the rest of the world we are not taught AI until later in our education (usually University). To make sure our future generations are prepared for working alongside AI systems and robotics. Our education providers need to evaluate what the future of work will look like and begin leveraging emerging technologies e.g. AI, VR, AR as part of the syllabus. All countries should evaluate what can be done so the adults of tomorrow will have an opportunity to succeed and no one is left behind in this fourth industrial revolution.

Benchmarking Machine Learning and Artificial Intelligence Processors

As machine learning (ML) software and artificial intelligence (AI) processors become increasingly common in consumer-grade products, customers are bound to ask themselves “How can I benchmark AI on my device?” or “Which ML benchmarking ratings can I trust when shopping for an upgrade or a new device?” Unfortunately, these questions do not yet have a clear answer.

Unlike the gaming industry, which has seemingly dozens of benchmark software options to allow both gamers and developers to find the best CPUs and GPUs for their particular use case, the ML and AI communities has no such resources available to them. While strong gaming-specific benchmarks may be an indicator of a good hardware choice for machine learning or artificial intelligence, this is not always the case. Thanks to the nature of complex mathematical processes utilized in tasks like deep learning it is not uncommon for the same program to run at different performance rates on different types of hardware. Due to this trend, a large scale, industry-specific ML/AI is needed to ensure that enthusiasts and developers alike have access to transparent information and competitive hardware choices.

Let’s take the gaming industry as an example of just how beneficial widespread hardware benchmarking can be for consumers. Applications like GeekbenchBasemark, and 3DMark allow gaming enthusiasts to get a strong understanding of their hardware’s capabilities in several key areas of performance, such as graphical frame rates or CPU speed. In turn, this information can assist consumers when they are making purchasing decisions, as data collected from these tests is often compiled into user-friendly websites like this, which allow users to see how different hardware combinations may affect their system’s performance. While an excellent benchmark ecosystem exists to assist PC gamers with their purchasing decisions, there is a distinct lack of such options for ML/AI enthusiasts.

This industry-wide deficiency may not seem like a huge issue at this point in time, but this will likely change in the near future. With the widespread release of user-friendly software packages such as Microsoft’s Windows MLand Apple’s Core ML set to increase machine learning’s accessibility for new enthusiasts and developers alike, it is imperative that those interested in pursuing machine learning or artificial intelligence have access to quality benchmark data in an effort to inform their purchasing decisions. If the ML/AI community is to grow as quickly as we wish, it is extremely important that those interested in working with this emerging technology are able to make well-informed purchasing decisions when investing in expensive hardware.

Despite all of the faults the nearly nonexistent ML/AI hardware benchmarking space currently has, it is important to note that there are currently a couple of open-source hardware benchmark software options available. For example, a select number of enthusiasts and developers have decided that they are not willing to wait around for benchmarking software to be developed. As a result, there are a couple different open-source benchmarking solutions available on GitHub, such as DeepBench, which measure’s a hardware’s ability to efficiently run deep learning algorithms.

While our research indicates that there are multiple instances of benchmarking software that measure’s a particular ML program’s efficiency, it is important to note that these benchmarks fall into a different category. In these instances, the program itself, not the hardware being utilized (is what is being tested). Due to this fact, it is hard to say whether such benchmarks really supply much information when it comes to the effectiveness of different hardware options. Overall, it is abundantly clear that there is currently a lack of user-friendly and accessible hardware benchmark software options for consumers.

So how can machine learning and artificial intelligence enthusiasts help solve this problem? For one, enthusiasts and developers can create and contribute to open-source projects that help to solve the industry’s current lack of user-friendly hardware benchmark software. While the greater industry may be lagging when it comes to this issue, there is nothing stopping those with the time and passion for the problem to assist in solving it themselves. Furthermore, any universally accepted hardware benchmark must yield well communicated results. Whether stemming from open-source or industry-sponsored software, the availability of such data can only assist the ML/AI community’s growth. Easy access to such information would greatly benefit consumers as they look to buy new or upgrade their existing PC hardware. Additionally, the development of an agreed upon universal benchmark would assist hardware manufacturers as they work to market their products to a growing number of machine learning enthusiasts.

Most importantly, the establishment of an industry standard benchmark for machine learning and artificial intelligence software would help create more competition within the market sector. Such a standard would bolster the need for hardware developers and manufacturers to be transparent, ensuring that consumers are able to get the most “bang for their buck” when shopping for new hardware. This trend would also serve to increase competition within the marketplace, which would encourage hardware developers to be innovative. As a result of this innovation, the ML/AI community could benefit from greatly improved hardware, yielding increased effectiveness of machine learning or artificial intelligence programs as they are deployed on these new devices.

While it is evident that there is currently a glaring lack of options for ML/AI developers and enthusiasts to benchmark their hardware, this does not have to be the case in the future. There are promising signals from the open-source ML/AI community when it comes to this problem. It would certainly be helpful for companies like Intel, AMD, and Nvidia to continue contributing their resources to this cause. However, with the number of knowledgeable and highly skilled machine learning and artificial intelligence enthusiasts increasing every day, it is likely that we will see a better software solution for ML/AI hardware benchmarking developed in the near future.

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