Technology peripherals
AI
How data science and artificial intelligence are driving smart city goals
How data science and artificial intelligence are driving smart city goals
The key feature of a smart city is the intelligent use of data to improve lifestyles and livelihoods of communities.
Data science and artificial intelligence (DSAI) are transforming the digital landscape. We are seeing rapid transformation in all walks of life, and machine learning and data science have attracted worldwide attention.
As DSAI capabilities become more advanced, organizations need to rethink their operations and equip themselves with the relevant digital acumen.
The ability to transform data into business insights for decision-making while understanding customer intent will allow organizations to stay current and keep up with technology trends, all of which make organizations more efficient and improve business intelligence.
DSAI has permeated every aspect of our daily lives, from using facial recognition to unlock your phone, to consuming entertainment, to endless internet searches. It’s clear that DSAI’s priority for businesses and governments will only continue to increase.
Singapore has recognized the importance of leveraging this technology and announced a 10-year US$43.5 billion investment plan to create sustainable infrastructure for the future.
DSAI and Smart City
A smart city must be a smart city. Smart cities are not just about integrating smarter technology into traditional infrastructure, but also knowing how to use the data collected to make better decisions and provide better services to city residents.
The key feature of a smart city is the ability to intelligently use data, learn from it and work with residents to improve their lifestyles and improve the livelihoods of their communities.
At Aboitiz Data Innovation (ADI), DSAI operates to develop and deploy new products and solutions designed to advance businesses and communities in a rapidly changing environment.
Republic Cement, one of the Philippines’ leading construction materials companies, has partnered with ADI to develop an artificial intelligence tool to predict cement quality based on historical data.
Through this AI-driven solution, Republic Cement is able to optimize its cement manufacturing process to better manage resources and use raw materials more efficiently. The most important thing is to effectively reduce carbon emissions in the cement manufacturing process while ensuring stable product quality, reducing approximately 35,000 tons of carbon dioxide every year.
This innovation demonstrates ADI’s ability to transform DSAI into effective solutions that drive better business and environmental outcomes.
Encouraging citizen action to create a smarter future
The ultimate goal of a smart city is to create an urban area based on improved quality of life, improved services and sustainable development. People demand a better life and a safer future environment.
An important part of making smart cities a more feasible reality is the active participation of citizens. That’s why it’s important to familiarize the next generation with the idea of smart cities and encourage participation in its progress.
ADI’s Postgraduate Scholarship Program works in partnership with the Singapore Economic Development Board’s Industrial Postgraduate Program II (IPP-II) to build a talent pool of postgraduate students with key R&D skills prepared to play a role in industry.
ADI’s collaboration with the National University of Singapore also creates opportunities for research into AI-based sustainable systems in areas such as urban design, power utilities, manufacturing and the financial sector. This enables Singaporeans to learn more about DSAI technology and its positive impact within and outside the community.
Building Public and Private Sector Partnerships
Building smart cities requires planning, and this is where governments play a key role in implementing and identifying steps to build supporting infrastructure and ecosystems place.
According to the Top 50 Smart Cities Government Report 2020/2021, Singapore ranks first in terms of its government’s readiness to develop, promote or track smart city initiatives.
The Smart Nation Initiative was also launched in 2014 to promote national efforts to transform Singapore into a smart nation.
Towards a data-driven future
The exchange of data between departments is one of the best ways to accelerate technological progress. Both the public and private sectors need to work together to understand their respective roles in urban transformation.
The world of data is complex, and ADI’s approach is to help governments and businesses rethink how to harness the power of data through proven and tested frameworks.
Of course, data and artificial intelligence are valuable resources that not only help companies digitize, create new sustainable products and services, and bring profits; they can also make people’s lives better and easier .
Through ADI’s consulting solutions, businesses and governments can gain relevant information and strategic direction to develop and deploy DSAI solutions to improve the lifestyles and livelihoods of their communities.
Singapore’s DSAI journey aims to bring about impactful change that will lead to improved productivity. Digital-first Singapore's vision is to effectively transform digital government, digital economy and digital society.
Leaders need to embrace a data-driven mindset, and knowing how to unlock data will be a core skill that should be the DNA of creating smart cities. We are moving toward an era where sustainable data-driven innovation is the key to a smarter, brighter future.
The above is the detailed content of How data science and artificial intelligence are driving smart city goals. 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
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
Seven Cool GenAI & LLM Technical Interview Questions
Jun 07, 2024 am 10:06 AM
To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text
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
Five schools of machine learning you don't know about
Jun 05, 2024 pm 08:51 PM
Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing
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
