Technology peripherals
AI
Let 'poor students' know more about AI, educational organizations supported by Microsoft and Google are working hard
Let 'poor students' know more about AI, educational organizations supported by Microsoft and Google are working hard
News on March 8, local time on Tuesday, the Artificial Intelligence Education Project (aiEDU), a non-profit organization supported by Microsoft and Google, announced that it will expand the coverage of artificial intelligence education and promote More students in the district can learn about artificial intelligence.
As more students use the artificial intelligence chat tool ChatGPT to complete homework and coursework papers, many people are beginning to worry about whether artificial intelligence tools are suitable for school education. But aiEDU CEO Alex Kotran said his team wants to ensure these AI tools are used more.
aiEDU is a non-profit organization supported by companies such as Microsoft, Google, OpenAI and AT&T Corporation, which provides free materials and teacher training services with the goal of deepening students' understanding of artificial intelligence. The idea of aiEDU is to let children understand the nature, limitations, and prospects of artificial intelligence technology and prepare them for jobs that require the use of artificial intelligence.
On Tuesday, aiEDU called for the expansion of artificial intelligence education across the United States at the South by Southwest Education Conference in Austin, Texas, and also announced that the scope of supporters and partner schools has expanded. To date, aiEDU’s educational programs have reached 100,000 students and have established relationships with school districts representing 1.5 million low-income and educationally underserved children across the United States.
aiEDU was established in 2019. Coltrane has argued that it will be several years before there is widespread demand among educators for AI education programs. However, with the popularity of image generators such as OpenAI chatbots and Dall-E, people's interest in generative artificial intelligence has increased rapidly, which has greatly boosted the demand for education. Cortland said aiEDU may need more funding as a result.
Artificial intelligence education focuses on students in remote areas, especially some of these areas are more likely to be negatively affected by job automation, and artificial intelligence will lead to a growing gap in skills. Cortland said that back in 2018, he was struck by all the talk in the San Francisco area about artificial intelligence changing the future of work. His mother, a public school teacher in Akron, Ohio, said she wanted her students to learn the technology.
What’s surprising to me is that Akron, Ohio (formerly the tire capital) is one of the 20 cities in the country most likely to lose jobs to automation, but local high school students are There’s no understanding of the jobs of the future, let alone artificial intelligence.” He found that there were no specific courses or requirements to study artificial intelligence across the United States.
Other supporters of aiEDU include Nvidia, Intel, venture capital company GSV, communications operator Verizon, etc.
Cortland’s team is working with school districts to organize educational service centers to plan for 420,000 students in Texas, 300,000 students in Wisconsin, 250,000 students in Ohio and Georgia. Serving public school districts in Atlanta, WA, Spokane, WA, and Anaheim, CA. Their goal is to ensure these students are prepared for jobs that may require artificial intelligence in the coming years.
"Humans may not be directly replaced by artificial intelligence, but people will be replaced by people who are skilled in using artificial intelligence," Cortland said. "So students who don't have experience or don't know how to use the tools , students who have not used generative artificial intelligence to develop projects will be eliminated by those students with experience.”
The above is the detailed content of Let 'poor students' know more about AI, educational organizations supported by Microsoft and Google are working hard. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
AI Hentai Generator
Generate AI Hentai for free.
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1371
52
ChatGPT now allows free users to generate images by using DALL-E 3 with a daily limit
Aug 09, 2024 pm 09:37 PM
DALL-E 3 was officially introduced in September of 2023 as a vastly improved model than its predecessor. It is considered one of the best AI image generators to date, capable of creating images with intricate detail. However, at launch, it was exclus
Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions
Jun 28, 2024 am 03:51 AM
This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP
Context-augmented AI coding assistant using Rag and Sem-Rag
Jun 10, 2024 am 11:08 AM
Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application
Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations
Jun 11, 2024 pm 03:57 PM
Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it
To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework
Jul 25, 2024 am 06:42 AM
Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A
SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time
Jul 17, 2024 pm 06:37 PM
Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S
Laying out markets such as AI, GlobalFoundries acquires Tagore Technology's gallium nitride technology and related teams
Jul 15, 2024 pm 12:21 PM
According to news from this website on July 5, GlobalFoundries issued a press release on July 1 this year, announcing the acquisition of Tagore Technology’s power gallium nitride (GaN) technology and intellectual property portfolio, hoping to expand its market share in automobiles and the Internet of Things. and artificial intelligence data center application areas to explore higher efficiency and better performance. As technologies such as generative AI continue to develop in the digital world, gallium nitride (GaN) has become a key solution for sustainable and efficient power management, especially in data centers. This website quoted the official announcement that during this acquisition, Tagore Technology’s engineering team will join GLOBALFOUNDRIES to further develop gallium nitride technology. G
SearchGPT: Open AI takes on Google with its own AI search engine
Jul 30, 2024 am 09:58 AM
Open AI is finally making its foray into search. The San Francisco company has recently announced a new AI tool with search capabilities. First reported by The Information in February this year, the new tool is aptly called SearchGPT and features a c
