Is generative AI bad for the environment?

Is generative AI bad for the environment?

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Is generative AI bad for the environment? A computer scientist explains the carbon footprint of ChatGPT and its cousins

By Kate Saenko, Boston University

The image above is on The Generative AI Race Has a Dirty Secret, credit to WIRED

Is generative AI bad for the environment?
AI chatbots and image generators run on thousands of computers housed in data centers like this Google facility in Oregon.
Tony Webster/Wikimedia, CC BY-SA

Generative AI is the hot new technology behind chatbots and image generators. But how hot is it making the planet?

As an AI researcher, I often worry about the energy costs of building artificial intelligence models. The more powerful the AI, the more energy it takes. What does the emergence of increasingly more powerful generative AI models mean for society’s future carbon footprint?

“Generative” refers to the ability of an AI algorithm to produce complex data. The alternative is “discriminative” AI, which chooses between a fixed number of options and produces just a single number. An example of a discriminative output is choosing whether to approve a loan application.

Generative AI can create much more complex outputs, such as a sentence, a paragraph, an image or even a short video. It has long been used in applications like smart speakers to generate audio responses, or in autocomplete to suggest a search query. However, it only recently gained the ability to generate humanlike language and realistic photos.

Using more power than ever

The exact energy cost of a single AI model is difficult to estimate, and includes the energy used to manufacture the computing equipment, create the model and use the model in production. In 2019, researchers found that creating a generative AI model called BERT with 110 million parameters consumed the energy of a round-trip transcontinental flight for one person. The number of parameters refers to the size of the model, with larger models generally being more skilled. Researchers estimated that creating the much larger GPT-3, which has 175 billion parameters, consumed 1,287 megawatt hours of electricity and generated 552 tons of carbon dioxide equivalent, the equivalent of 123 gasoline-powered passenger vehicles driven for one year. And that’s just for getting the model ready to launch, before any consumers start using it.

Size is not the only predictor of carbon emissions. The open-access BLOOM model, developed by the BigScience project in France, is similar in size to GPT-3 but has a much lower carbon footprint, consuming 433 MWh of electricity in generating 30 tons of CO2eq. A study by Google found that for the same size, using a more efficient model architecture and processor and a greener data center can reduce the carbon footprint by 100 to 1,000 times.

Larger models do use more energy during their deployment. There is limited data on the carbon footprint of a single generative AI query, but some industry figures estimate it to be four to five times higher than that of a search engine query. As chatbots and image generators become more popular, and as Google and Microsoft incorporate AI language models into their search engines, the number of queries they receive each day could grow exponentially.

AI chatbots, search engines and image generators are rapidly going mainstream, adding to AI’s carbon footprint.
AP Photo/Steve Helber

AI bots for search

A few years ago, not many people outside of research labs were using models like BERT or GPT. That changed on Nov. 30, 2022, when OpenAI released ChatGPT. According to the latest available data, ChatGPT had over 1.5 billion visits in March 2023. Microsoft incorporated ChatGPT into its search engine, Bing, and made it available to everyone on May 4, 2023. If chatbots become as popular as search engines, the energy costs of deploying the AIs could really add up. But AI assistants have many more uses than just search, such as writing documents, solving math problems and creating marketing campaigns.

Another problem is that AI models need to be continually updated. For example, ChatGPT was only trained on data from up to 2021, so it does not know about anything that happened since then. The carbon footprint of creating ChatGPT isn’t public information, but it is likely much higher than that of GPT-3. If it had to be recreated on a regular basis to update its knowledge, the energy costs would grow even larger.

One upside is that asking a chatbot can be a more direct way to get information than using a search engine. Instead of getting a page full of links, you get a direct answer as you would from a human, assuming issues of accuracy are mitigated. Getting to the information quicker could potentially offset the increased energy use compared to a search engine.

Ways forward

The future is hard to predict, but large generative AI models are here to stay, and people will probably increasingly turn to them for information. For example, if a student needs help solving a math problem now, they ask a tutor or a friend, or consult a textbook. In the future, they will probably ask a chatbot. The same goes for other expert knowledge such as legal advice or medical expertise.

While a single large AI model is not going to ruin the environment, if a thousand companies develop slightly different AI bots for different purposes, each used by millions of customers, the energy use could become an issue. More research is needed to make generative AI more efficient. The good news is that AI can run on renewable energy. By bringing the computation to where green energy is more abundant, or scheduling computation for times of day when renewable energy is more available, emissions can be reduced by a factor of 30 to 40, compared to using a grid dominated by fossil fuels.

Finally, societal pressure may be helpful to encourage companies and research labs to publish the carbon footprints of their AI models, as some already do. In the future, perhaps consumers could even use this information to choose a “greener” chatbot.

Kate Saenko, Associate Professor of Computer Science, Boston University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

 

Digitisation could turn electricity into a worldwide network

Digitisation could turn electricity into a worldwide network

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Digitisation could turn electricity into a worldwide network – tech expert

Referencing the Rubik’s cube, Edwin Diender, Chief Innovation Officer: Global Electric Power Digitalisation Business Unit, Huawei Technologies, Thailand, said each cube represents something or someone.

He was speaking on the second day of Enlit Africa 2023, focusing on the theme, Find the Right Technologies to Power the Global Energy Transition.

A cube that contains all the requisite components has the potential to link up the worldwide web of energy, he said.

“It is energy powering the construction of intelligent cities.

“The digital journey is passing phases. It’s a journey that follows programmes and initiatives and brought together as pieces through universal infrastructure.”

Diender said the conversion of analogue to digital is the first step to digitisation. In the energy sector, for example, analogue meters are replaced by smart meters, an item that is digitised and may be “the first step on this journey.”

The next step involves different building blocks that are brought together in a smart system that’s intelligent. This cube connects to many other cubes by a digital framework.

Diender said Huawei is looking at other forms of infrastructure, including electric power digitisation.

This would encompass finding the right technologies to help drive the digital journey for the energy industry.

Harnessing electricity transmission through digitisation

The company wants to “grab opportunities” like a software defined grid, intelligent power plant and green intelligent energy solutions. It wants to bridge industry requirements with digital technologies and finding the right technologies for industrial scenarios.

“The digital journey is a collaborative journey. We are working closely with customers worldwide in the electric power industry.”

He also cited technology solutions that can be used to protect power infrastructure – like an intelligent substation inspection system. Diender said the award-winning Yancheng Industrial Park was an example of Huawei looking at digital energy solutions.

The Yancheng Park project was jointly developed by the company and the Yancheng Power Supply Company, a subsidiary of the State Grid Corporation of China.

“The project uses the triple-dimensional model for energy transformation, decarbonisation, and digital transformation.

“By focusing on the three scenarios of smart energy management, carbon management, and campus management, this project delivers real-time monitoring of energy equipment, strong carbon emission management, intelligent and convenient access control management, and intelligent and coordinated micro-grid control.

“The campus is powered by complementary energy sources and integrates its energy consumption system with on-campus terminals.

“The project is a showcase of an intelligent and low-carbon campus that contributes to a green, low-carbon, safe, and efficient modern energy system.”

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What role can blockchain play in developing smart cities

What role can blockchain play in developing smart cities

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What role can blockchain play in developing smart cities and the IoT when growing cities are a critical fact of the 21st Century representing the greatest challenge . . . 

The author states that, for instance, by ”using blockchain, citizens could receive tokens for waste disposal.”

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Smart cities are urban areas that use advanced technologies such as sensors, data analytics, and the Internet of Things (IoT) to improve the quality of life for their citizens. As these kinds of cities grow and become smarter, managing the vast amounts of data generated by IoT devices raises concerns about privacy and security. Blockchain technology can provide a secure and transparent way to manage data and administrative processes and improve safety. It can play a significant role in developing smart cities and the IoT.

How can Blockchain help develop Smart Cities and IoT?

1. Secure Data Management

Imagine a smart city with sensors that collect data on traffic, energy consumption, and air quality. All this data is like puzzle pieces that can help city planners make better decisions to improve the city. However, they need to ensure that the data is secure and only accessible by authorized people. Blockchain can help with that by creating a transparent and secure data management system. It’s like having a locked box where only authorized people have the key. This way, they can track who owns the data and how it’s being shared between parties like the city government, businesses, and citizens.

2. Decentralized Energy Grid

Let’s say you are a city government official responsible for waste management. You want to incentivize citizens to dispose of their trash and recycle properly, but you’re unsure how to track and reward individual efforts. Using blockchain technology, citizens could receive tokens for proper waste disposal, which they could then exchange for rewards like discounts at local businesses or even tax credits. This creates a more efficient and transparent way to incentivize good behavior and promote sustainability in the city.

3. Digital Identity Management

Blockchain can be used to create a safe and reliable way for citizens to prove their identity, reducing the chance of someone stealing or committing fraud. For example, blockchain technology can create digital IDs that allow citizens to vote or access government services, making these processes faster and more efficient.

4. Smart Contract Integration

Blockchain smart contracts can automate many aspects of city management, including traffic management, waste management, and emergency response. This could reduce costs, improve efficiency, and enhance citizen safety.

5. Public Records Management

Blockchain technology can make public records like property titles and business registrations more secure and transparent. This can reduce bureaucratic processes and enhance the accuracy and accessibility of public records. For instance, when buying a property, the buyer and seller can use blockchain to automate the transfer of ownership, making the process more secure and transparent.

Conclusion

Blockchain technology has the potential to play a vital role in the development of smart cities and the Internet of Things. By providing secure and transparent data management, decentralized energy grids, digital identity management, smart contract integration, and public records management, blockchain could help to create more efficient, sustainable, and livable cities for all.

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How Smart Cities are Transforming Urban Living

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Throughout the world, cities are increasingly looking to digitize services or become more technology-forward. In so doing, the Intersection of AI and IoT is an obligatory passage resulting in the author wondering How Smart Cities are Transforming Urban Living

A Smart City is an urban area that utilizes advanced technologies, data analytics, and interconnected systems to optimize urban processes, infrastructure, and services. By integrating data collection and communication technologies with the Internet of Things (IoT), a Smart City can improve its citizens’ efficiency, sustainability, and overall quality of life while reducing environmental impact and promoting economic growth.

The image above is of IStock.

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The Intersection of AI and IoT: How Smart Cities are Transforming Urban Living

KEY TAKEAWAYS

The combination of AI and IoT technologies is revolutionizing the way we live and work in smart cities, making them more efficient, sustainable, and livable. Real-time data analysis from multiple devices is simplifying decision-making and administrative tasks, optimizing resource utilization, and improving public safety. The smart city concept uses technology to improve the quality of life, including transportation, solid waste management, pollution reduction, sustainable communities, irrigation, public safety, traffic management, and healthcare, among others. Cities like Singapore, Amsterdam, Barcelona, and Dubai are leveraging the benefits of AI and IoT technologies to transform urban living.

Artificial Intelligence (AI) and the Internet of Things (IoT) technologies are being used together to leverage each other’s advantages. The interconnection of various data-generating devices, such as sensors, computers, vehicles, smartphones, buildings, and software through the Internet, has revolutionized how we live today.

The interplay of AI and IoT technologies has completely transformed the way we interpret and analyze the massive amount of data that is continuously generated by IoT devices with the help of AI techniques.

As a result, decision-making, optimizing industrial processes, making predictions, and identifying anomalies in industrial settings becomes easier than ever. Similarly, AI and IoT technologies are being used together in smart city applications to improve urban infrastructure and the quality of life.

Understanding smart cities

The idea of smart cities is described below, and various constituent components and examples of smart cities are also provided.

Defining smart cities

Before delving into how AI and IoT are transforming smart cities, it is important to understand what a smart city is and how it functions. The concept of smart cities emerged after the term “pervasive computing” started gaining popularity in the first decade of this century. Pervasive computing simply refers to “computing everywhere”. Therefore, pervasive computing and smart cities are closely related in several ways.

We can define smart cities as urban areas that utilize technology strategically and efficiently to perform day-to-day operations and improve their inhabitants’ quality of life. This includes incorporating technology in every aspect of life to offer better civic services, such as transportation, solid waste management and collection, pollution-free and sustainable communities, irrigation, healthcare, public safety and policing, traffic management, and many others. In a nutshell, “a smart city is an interconnected and technology-enabled sustainable environment designed to improve the standard of living of its residents.”

Components of smart cities

Smart cities comprise a variety of components, each of which is crucial for their functioning. The components include:

  • IoT devices: these include various data-collecting devices, such as sensors, traffic, air quality, energy usage monitoring devices, and so on.
  • Data analytics component: the component is responsible for processing and analyzing the data collected through the IoT devices
  • Communication Networks: are used for data transmission among IoT devices, data analytics systems, and other infrastructure components.
  • Metropolitan infrastructure and public services: are essential for the functioning of smart cities. Infrastructure includes buildings, roads, and other public areas, which can be transformed through data analytics and IoT. On the other hand, public services can be transportation, healthcare, education, and public safety, which may be improved through AI and data analytics.

Examples of smart cities

Recently, many cities worldwide have started implementing smart technologies to uplift the living standard of their citizens. Some of the cities include SingaporeAmsterdamBarcelona, and Dubai. Singapore’s smart city initiative utilizes IoT data and performs analytics to improve mobility and healthcare services, support businesses, and optimize traffic flows and energy usage. Likewise, Amsterdam, in addition to the ones discussed above, emphasizes sustainable solutions to mobility by providing smart traffic systems and electric charging stations.

Barcelona is not behind the others and also relies on IoT devices and data analytics methods. In particular, smart lighting systems based on motion sensors, green spaces, energy-efficient buildings, smart bike sharing, and waste reduction are among the few initiatives that make Barcelona a smart city. Similarly, automated buses and the urban metro system, smart grids, smart and energy-efficient buildings, smart healthcare, and policing have made Dubai emerge as one of the rapidly developing smart cities. The initiatives, such as Dubai Blockchain Strategy, the Dubai Future Accelerators program, and the Smart Dubai Platform, are pivotal in making Dubai one of the top living choices.

How AI and IoT are transforming urban living?

The intersection of AI and IoT technologies is transforming living and work in smart cities, and their impacts are becoming significant daily. By combining these two technologies, a new era of innovation, efficiency, and sustainability is emerging, which once could have only been dreamt of by humans. Real-time analysis of continuously generated data by multiple devices simultaneously has made decision-making and administrative tasks easier without much human involvement. For example, traffic signals equipped with IoT sensors can monitor traffic flow which can further be analyzed using AI algorithms and consequently can help traffic lights adapt to the traffic situation at a particular intersection in the city.

Likewise, another exciting usage scenario is in the solid waste collection and management domain, where the smart waste bins equipped with IoT ultrasonic sensors can notify about the levels of waste in the bins. AI techniques can schedule pickups, reducing unnecessary trips of waste collection vehicles and the environmental impact. Similarly, in smart buildings equipped with IoT devices, such as sensors, HVAC, lighting, etc., the data analytics techniques, with the help of the current sensor readings and historical data, may direct the control modules to optimize energy usage or predict any failures of the equipment. Moreover, the HVAC systems in smart buildings can be automatically adjusted based on occupancy and outside environmental conditions.

There are numerous advantages to using the two diverse spheres of technology together. Primarily, they result in increased efficiency, optimal resource utilization, reduced human involvement, savings of time and finances, etc. Moreover, sustainability is also vital in smart cities and can be improved through several environment-friendly initiatives. With the help of the sensors installed city-wide, the data about air quality and water usage is collected and analyzed by AI techniques. The data is subsequently used to issue alerts to the authorities of the areas where attention is required, for example, where high pollution levels are in the air or where water is being wasted.

AI and IoT technologies also help improve public safety through real-time monitoring. AI-powered security cameras are used to detect suspicious behavior through continuous surveillance. Similarly, monitoring the infrastructure for possible safety hazards through sensing devices enables timely alerts and quicker responses from the concerned authorities. In addition, greater civic engagement is promoted by providing citizens access to real-time data through various platforms and enabling them to provide decision-making feedback, leading to more impartial outcomes.

Challenges and Limitations of AI and IoT in Smart Cities

Though there are several benefits of integrating AI and IoT technologies in smart cities provides. However, numerous challenges and limitations must be addressed.

  • Device heterogeneity 

A lack of standardization across heterogeneous IoT devices and their communication protocols often results in compatibility issues, thus demanding the standardization of IoT protocols and interfaces for effective device integration and efficient data communication.

  • Data deluge 

The large volumes of data generated by IoT devices demand powerful computing resources and storage capabilities, hence elevating the need for data centers and cloud computing infrastructure.

  • Data security and privacy

Data security is crucial in smart cities due to the risk of cyber-attacks and data breaches, necessitating robust security measures. Moreover, continuous surveillance could also lead to privacy issues.

  • Ethical concerns

Addressing ethical concerns, such as bias introduced by the computational algorithms, may lead to discriminatory outcomes (for example, unfair treatment of certain groups), which is undesirable for equity and diversity in societies.

  • Job displacement and economic inequality 

Integrating AI and IoT in smart cities could lead to job displacement, especially for those who have little technical skills in sectors such as transport manufacturing, or logistics. This may further increase inequality of income and lead to a large number of workers not being adequately supported. Strategies to mitigate negative impacts should be developed in view of the possible impact on workers.

  • Massive investments 

Finally, significant investments are needed to realize smart city initiatives which can be challenging to manage initially.

Conclusion

In conclusion, the intersection of AI and IoT has paved the way for developing smarter and more sustainable cities. From optimizing energy consumption and transportation to enhancing public safety and citizen engagement, these technologies are revolutionizing how we live and interact in urban environments. While some challenges and limitations need to be addressed, the potential benefits of AI and IoT in smart cities are immense and should be exploited for better communities.

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High Tech Innovations Are Key To A Greener Economy

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In a Forbes Business Development Council article, it is held that High Tech Innovations Are Key To A Greener Economy.  Syed Alam 5 Ways To Ensure A More Sustainable Future.  

Environmentally Responsible and Resource-efficient in the MENA region, was and still is concerned for anything green that were second to that fundamentally frantic development of buildings and all related infrastructure to nevertheless greater and greater awareness of their various environmental impact. 

The image above is Getty

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High Tech Innovations Are Key To A Greener Economy: 5 Ways To Ensure A More Sustainable Future

 

Syed is Accenture’s High Tech global lead, helping clients reinvent their business, optimize supply chain and create new revenue models.

The high-tech industry is central to moving the sustainability agenda forward and enabling a greener planet through the design of more sustainable products using the rise of smart sensors as a way to better manage energy consumption.

At my company Accenture, we have already seen great progress in a wide variety of products, from smart thermostats and solar-powered smart watches to electric vehicles and more power-efficient CPUs in data centers. These products are not only more sustainable and good for the environment, but they are also good for business and future growth.

A recent study from United Nations Global Compact and Accenture shows strategies and business models with sustainability at their core are not only a climate imperative but also the foundation for better security, growth and resilience. This is supported by another recent study’s indication that the supply chain is key to fighting climate change, as supply chains generate up to 60% of global emissions.

While many companies have mastered Scope 1 emissions, most companies lack visibility into the upstream supplier base, called “Scope 3” emissions. For high-tech companies, 86% of upstream Scope 3 emissions sit outside their Tier 1 suppliers.

High-tech companies are deploying strategies to help the industry meet environmental sustainability goals. The Semiconductor Climate Consortium is one excellent example of semiconductor companies coming together to collaborate and align on common approaches and technology innovations to continuously reduce greenhouse gas emissions.

In this article, I will outline five strategies high-tech leaders can adopt to ensure a more sustainable future both within their own organizations and across the supply chain.

1. Recycling Products

E-waste, driven in part by consumers upgrading to the latest smartphones and data centers swapping out servers to keep up with the demands of AI, is both damaging to the planet and costing high-tech companies money. According to the United Nations, global e-waste volumes grew 17% between 2014 and 2019, with over 53 million tons of e-waste in 2019.

High-tech companies are in a unique position to help reduce e-waste by designing products for reuse, resale, repair, refurbishment and remanufacturing, which Accenture and the United Nations study shows can boost operating profit by 16%.

Many technology giants already have successful recycling programs in place that encourage partner participation. In 2022, Accenture partner Cisco launched the Environmental Sustainability Specialization (ESS), a program to educate customers, promote product takeback and assist in the move to circular business models.

As many companies have proven, this can constitute a great opportunity to save money and create new revenue streams while reducing carbon footprints by avoiding single-use inputs and designing for refurbishment and longevity.

2. Selecting Cleaner Raw Materials

As the demand for more sustainable materials rises, more companies are starting to use cleaner minerals such as copper, lithium, nickel and cobalt. Fortunately, materials suppliers have stepped up efforts to deliver eco-friendly solutions to enable companies to make this transition.

Accenture partner Solvay, a supplier of alternative materials, has been developing new solutions to reduce waste materials generated by semiconductor manufacturing. Its products are helping customers recycle polyvinylidene fluoride, a byproduct of chipmaking.

3. Adopting Greener Manufacturing Processes

Many manufacturing companies are making strides in reducing electricity consumption, recycling water and adopting greener manufacturing practices.

Accenture partner Lam Research invested in LED lighting processes and improvements to HVAC equipment such as air compressors. Likewise, companies such as Winbond are using a new low-temperature soldering (LTS) process to reduce the temperatures needed for the assembly of components. These lower temperatures can lead to faster manufacturing throughput while also lowering temperatures to reduce carbon emissions.

Leaders continue to adopt solutions capable of streamlining production processes, using digital tools and deploying more efficient supply chains to save energy and optimize logistics to reduce truck rolls, which can help lower carbon footprints.

Accenture partner Hitachi’s Lumada Manufacturing Insights is a perfect example, as it is helping manufacturers develop data-driven operations, increase supply chain visibility and enable smart factory solutions to improve productivity and lower asset downtime.

4. Designing More Power-Efficient Products

At this year’s CES, we saw many energy-efficient products come to life as companies introduced products focused on managing home energy usage, including battery packs, solar panels and EV chargers. Accenture partner Schneider Electric released the “Home” energy platform to monitor energy usage, manage backup power during an outage and connect to utility programs for savings on electricity bills.

The industry migration to the cloud has also helped significantly reduce global power consumption. Because the cloud supports many products at a time, it can more efficiently distribute resources among users. Companies like Accenture partner Google have made inroads in making their cloud services power efficient, with claims new data centers are twice as energy efficient as a typical enterprise data center—delivering five times as much computing power for the same amount of electrical power as five years ago.

5. Embedding Sustainability Into Supplier Selection And Management

As companies source new suppliers and optimize existing ones, they should embed sustainability in every step of the supply chain management process. This includes analyzing the supplier base to determine the biggest source of emissions and having data-driven conversations with suppliers to reduce emissions.

Digital tools such as digital twins can be used to map physical material flows to uncover sub-tier suppliers and risks. By proactively working with suppliers on an ongoing basis, high-tech companies can identify bottlenecks within the supply chain and help mitigate disruptive events while improving their own decarbonization performance.

Social Innovations Without Waste

While the industry has made great strides toward global sustainability, there is still much work to be done. With the value of global sustainability assets rising above $220 billion, it is increasingly evident that investing in sustainability is not just morally responsible but financially savvy.

Organizations must reduce massive surges in energy consumption, water usage and CO2 emissions and develop sustainable products and services to help customers in their own sustainability transformations. The transition to sustainability presents a tremendous revenue-generating opportunity for companies that act quickly to develop—and adopt—greener technologies.

 


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