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

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

AI chatbots and image generators on thousands of computers housed in data centers like this Google facility in Oregon.
Tony Webster/Wikimedia, CC BY-SA

Kate Saenko, Boston University

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 . 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.

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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 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 each day could grow exponentially.

a roomful of people work on computers
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 its knowledge, the energy costs would grow even larger.

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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 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 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 , 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 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.The Conversation

Kate Saenko, Associate Professor of Computer Science, Boston University

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

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Animal behavior research is getting better at keeping observer bias from sneaking in – but there’s still room to improve

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theconversation.com – Todd M. Freeberg, Professor and Associate Head of Psychology, of Tennessee – 2024-05-03 07:16:49

What you expect can influence what you think you see.

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Todd M. Freeberg, University of Tennessee

Animal behavior research relies on careful observation of animals. Researchers might spend months in a jungle habitat watching tropical birds mate and raise their young. They might track the rates of physical contact in cattle herds of different densities. Or they could record the sounds whales make as they migrate through the ocean.

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Animal behavior research can fundamental insights into the natural processes that affect ecosystems around the globe, as well as into our own human minds and behavior.

I study animal behavior – and also the research reported by scientists in my field. One of the challenges of this kind of science is making sure our own assumptions don't influence what we think we see in animal subjects. Like all people, how scientists see the world is shaped by biases and expectations, which can affect how data is recorded and reported. For instance, scientists who in a society with strict gender roles for women and might interpret things they see animals doing as reflecting those same divisions.

The scientific corrects for such mistakes over time, but scientists have quicker methods at their disposal to minimize potential observer bias. Animal behavior scientists haven't always used these methods – but that's changing. A new study confirms that, over the past decade, studies increasingly adhere to the rigorous best practices that can minimize potential biases in animal behavior research.

Black and white photo of a horse with a man and a small table between them displaying three upright cards.

Adding up?

Karl Krall/Wikimedia Commons

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Biases and self-fulfilling prophecies

A German horse named Clever Hans is widely known in the history of animal behavior as a classic example of unconscious bias leading to a false result.

Around the turn of the 20th century, Clever Hans was purported to be able to do math. For example, in response to his owner's prompt “3 + 5,” Clever Hans would tap his hoof eight times. His owner would then reward him with his favorite vegetables. Initial observers reported that the horse's abilities were legitimate and that his owner was not being deceptive.

However, careful analysis by a young scientist named Oskar Pfungst revealed that if the horse could not see his owner, he couldn't answer correctly. So while Clever Hans was not good at math, he was incredibly good at observing his owner's subtle and unconscious cues that gave the math answers away.

In the 1960s, researchers asked human study participants to code the learning ability of rats. Participants were told their rats had been artificially selected over many generations to be either “bright” or “dull” learners. Over several weeks, the participants ran their rats through eight different learning experiments.

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In seven out of the eight experiments, the human participants ranked the “bright” rats as being better learners than the “dull” rats when, in reality, the researchers had randomly picked rats from their breeding colony. Bias led the human participants to see what they thought they should see.

Eliminating bias

Given the clear potential for human biases to skew scientific results, textbooks on animal behavior research methods from the 1980s onward have implored researchers to verify their work using at least one of two commonsense methods.

One is making sure the researcher observing the behavior does not know if the subject from one study group or the other. For example, a researcher would measure a cricket's behavior without knowing if it came from the experimental or control group.

The other best practice is utilizing a second researcher, who has fresh eyes and no knowledge of the data, to observe the behavior and code the data. For example, while analyzing a file, I count chickadees taking seeds from a feeder 15 times. Later, a second independent observer counts the same number.

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Yet these methods to minimize possible biases are often not employed by researchers in animal behavior, perhaps because these best practices take more time and effort.

In 2012, my colleagues and I reviewed nearly 1,000 articles published in five leading animal behavior journals between 1970 and 2010 to see how many reported these methods to minimize potential bias. Less than 10% did so. By contrast, the journal Infancy, which focuses on human infant behavior, was far more rigorous: Over 80% of its articles reported using methods to avoid bias.

It's a problem not just confined to my field. A 2015 of published articles in the sciences found that blind protocols are uncommon. It also found that studies using blind methods detected smaller differences between the key groups being observed to studies that didn't use blind methods, suggesting potential biases led to more notable results.

In the years after we published our article, it was cited regularly and we wondered if there had been any improvement in the field. So, we recently reviewed 40 articles from each of the same five journals for the year 2020.

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We found the rate of papers that reported controlling for bias improved in all five journals, from under 10% in our 2012 article to just over 50% in our new review. These rates of reporting still lag behind the journal Infancy, however, which was 95% in 2020.

All in all, things are looking up, but the animal behavior field can still do better. Practically, with increasingly more portable and affordable audio and video recording technology, it's getting easier to carry out methods that minimize potential biases. The more the field of animal behavior sticks with these best practices, the stronger the foundation of knowledge and public trust in this science will become.The Conversation

Todd M. Freeberg, Professor and Associate Head of Psychology, University of Tennessee

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

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Boeing’s Starliner is about to launch − if successful, the test represents an important milestone for commercial spaceflight

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theconversation.com – Wendy Whitman Cobb, Professor of Strategy and Security Studies, University – 2024-05-02 07:24:25

Boeing's Starliner spacecraft on approach to the International Station during an uncrewed test in 2022.

Bob Hines/NASA

Wendy Whitman Cobb, Air University

If all goes well late on May 6, 2024, NASA astronauts Butch Wilmore and Suni Williams will blast off into space on Boeing's Starliner spacecraft. Launching from the Kennedy Space Center, this last crucial test for Starliner will test out the new spacecraft and take the pair to the International Space Station for about a .

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Part of NASA's commercial crew program, this long-delayed mission will represent the vehicle's first crewed launch. If successful, it will give NASA – and in the future, space tourists – more options for getting to low Earth orbit.

Two people wearing blue jumpsuits hug in front of a plane.

Suni Williams, right, and Butch Wilmore, the two astronauts who will crew the Starliner test.

AP Photo/Terry Renna

From my perspective as a space policy expert, Starliner's launch represents another significant milestone in the development of the commercial space industry. But the mission's troubled history also shows just how difficult the path to space can be, even for an experienced company like Boeing.

Origins and development

Following the retirement of NASA's space shuttle in 2011, NASA invited commercial space companies to help the agency transport cargo and crew to the International Space Station.

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In 2014, NASA selected Boeing and SpaceX to build their respective crew vehicles: Starliner and Dragon.

Boeing's vehicle, Starliner, was built to carry up to seven crew members to and from low Earth orbit. For NASA missions to the International Space Station, it will carry up to four at a time, and it's designed to remain docked to the station for up to seven months. At 15 feet, the capsule where the crew will sit is slightly bigger than an Apollo command module or a SpaceX Dragon.

Boeing designed Starliner to be partially reusable to reduce the cost of getting to space. Though the Atlas V rocket it will take to space and the service module that supports the craft are both expendable, Starliner's crew capsule can be reused up to 10 times, with a six-month turnaround. Boeing has built two flightworthy Starliners to date.

A conical vehicle sitting on a flat vehicle.

The Starliner capsule in transit.

AP Photo/John Raoux

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Starliner's development has with setbacks. Though Boeing received US$4.2 billion from NASA, compared with $2.6 billion for SpaceX, Boeing spent more than $1.5 billion extra in developing the spacecraft.

On Starliner's first uncrewed test flight in 2019, a series of software and hardware failures prevented it from getting to its planned orbit as well as docking with the International Space Station. After testing out some of its , it landed successfully at White Sands Missile Range in New Mexico.

In 2022, after identifying and making more than 80 fixes, Starliner conducted a second uncrewed test flight. This time, the vehicle did successfully dock with the International Space Station and landed six days later in New Mexico.

The inside of a Starliner a few astronauts. Crew members first trained for the launch in a simulator.

Still, Boeing delayed the first crewed launch for Starliner from 2023 to 2024 because of additional problems. One involved Starliner's parachutes, which help to slow the vehicle as it returns to Earth. Tests found that some links in those parachute lines were weaker than expected, which could have caused them to break. A second problem was the use of flammable tape that could pose a fire hazard.

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A major question stemming from these delays concerns why Starliner has been so difficult to develop. For one, NASA officials admitted that it did not as much oversight for Starliner as it did for SpaceX's Dragon because of the agency's familiarity with Boeing.

And Boeing has experienced several problems recently, most visibly with the safety of its airplanes. Astronaut Butch Wilmore has denied that Starliner's problems reflect these troubles.

But several of Boeing's other space activities beyond Starliner have also experienced mechanical failures and budget pressure, including the Space Launch System. This system is planned to be the main rocket for NASA's Artemis program, which plans to return humans to the Moon for the first time since the Apollo era.

Significance for NASA and commercial spaceflight

Given these difficulties, Starliner's success will be important for Boeing's future space efforts. Even if SpaceX's Dragon can successfully transport NASA astronauts to the International Space Station, the agency needs a backup. And that's where Starliner comes in.

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Following the Challenger explosion in 1986 and the Columbia shuttle accident in 2003, NASA retired the space shuttle in 2011. The agency was left with few options to get astronauts to and from space. a second commercial crew vehicle provider means that NASA will not have to depend on one company or vehicle for space launches as it previously had to.

Perhaps more importantly, if Starliner is successful, it could compete with SpaceX. Though there's no crushing demand for space right now, and Boeing has no plans to market Starliner for tourism anytime soon, competition is important in any market to drive down costs and increase innovation.

More such competition is likely coming. Sierra Space's Dream Chaser is planning to launch later this year to transport cargo for NASA to the International Space Station. A crewed version of the space plane is also being developed for the next round of NASA's commercial crew program. Blue Origin is working with NASA in this latest round of commercial crew contracts and developing a lunar lander for the Artemis program.

A conical white spacecraft with two rectangular solar panels in space, with the Earth in the background.

SpaceX's dragon capsule.

NASA TV via AP

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Though SpaceX has made commercial spaceflight look relatively easy, Boeing's rocky experience with Starliner shows just how hard spaceflight continues to be, even for an experienced company.

Starliner is important not just for NASA and Boeing, but to demonstrate that more than one company can find success in the commercial space industry. A successful launch would also give NASA more confidence in the industry's ability to operations in Earth's orbit while the agency focuses on future missions to the Moon and beyond.The Conversation

Wendy Whitman Cobb, Professor of Strategy and Security Studies, Air University

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

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Brain cancer in children is notoriously hard to treat – a new mRNA cancer vaccine triggers an attack from within

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theconversation.com – Christina von Roemeling, Assistant Professor of Neurosurgery, University of Florida – 2024-05-01 10:01:09

How cancer vaccines are delivered into the body influences their effectiveness.

Liuhsihsiang/iStock via Getty Images Plus

Christina von Roemeling, University of Florida and John Ligon, University of Florida

Brain cancers remain among the most challenging tumors to treat. They often don't respond to traditional treatments because many chemotherapies are unable to penetrate the protective barrier around the brain. Other treatments like radiation and surgery can with lifelong debilitating side effects.

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As a result, brain cancer is the leading cause of cancer-related death in children. Brain tumors in frequently do not respond to treatments developed for adults, likely due to the fact that pediatric brain cancers are not as well-studied as adult brain cancers. There is an urgent need to develop new treatments specific to children.

We developed a new messenger-RNA, or mRNA, cancer vaccine, described in newly published research, that can deliver treatments more effectively in children who have brain cancer and teach their immune to fight back.

Close-up of child's hand with IV line placed held by adult's hand

Cancer treatments designed for adults may not necessarily work as well in children.

Virojt Changyencham/Moment via Getty Images

How do cancer vaccines work?

The immune system is a complex network of cells, tissues and organs whose primary function is to continuously surveil the body for threats posed by foreign invaders – pathogens that tissues and make you sick. It accomplishes this by recognizing antigens, or abnormal proteins or molecules, on pathogens. T cells that recognize these antigens seek out and destroy the pathogens.

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Your immune system also protects you from domestic threats like cancer. Over time, your cells sustain DNA damage from either internal or external stressors, leading to mutations. The proteins and molecules produced from mutated DNA look quite different from the ones cells typically produce, so your immune system can recognize them as antigens. Cancer develops when cells accumulate mutations that enable them to continue to grow and divide while simultaneously going undetected by the immune system.

In 1991, scientists identified the first tumor antigen, helping lay the framework for modern-day immunotherapy. Since then, researchers have identified many new tumor antigens, facilitating the development of cancer vaccines. Broadly, cancer vaccines deliver tumor antigens into the body to teach the immune system to recognize and attack cancer cells that display those antigens. Although all cancer vaccines conceptually work very similarly, they each significantly vary in the way they are developed and the number and combination of antigens they carry.

Cancer vaccines the immune system differentiate between healthy cells and tumor cells.

One of the biggest differences among cancer vaccines is how they are created. Some vaccines use protein fragments, or peptides, of tumor antigens that are directly given to patients. Other vaccines use viruses reengineered to express cancer antigens. Even more complex are vaccines where a patient's own immune cells are collected and trained to recognize cancer antigens in a laboratory before being delivered back to the patient.

Currently, there is a lot of excitement and focus among researchers on developing mRNA-based cancer vaccines. Whereas DNA is the blueprint of which proteins to make, mRNA is a copy of the blueprint that tells cells how to build these proteins. Thus, researchers can use mRNA to create blueprint copies of potential antigens.

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mRNA cancer vaccines

The pandemic brought significant attention to the potential of using mRNA-based vaccines to stimulate the immune system and protection against the antigens they encode for. But researchers have been investigating the use of mRNA vaccines for treating various cancers since before the pandemic.

Our team of scientists in the Brain Tumor Immunotherapy Program at University of Florida has spent the past 10 years developing and optimizing mRNA vaccines to treat brain cancer.

Cancer vaccines have faced significant challenges. One key hurdle is that these vaccines may not always trigger a strong enough immune response to eradicate the cancer completely. Moreover, tumors are not made up of one type of cancer cell, but rather a complex mix of cancer cells that each harbors its own unique cocktail of mutations.

Our cancer vaccine seeks to address these issues in a number of ways.

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Diagram of lipid molecules formed a spherical shell around single-stranded mRNAs

Lipid nanoparticles can carry therapeutic mRNA into the body.

Buschmann et al. 2021/ Wikimedia Commons, CC BY-SA

First, we designed our vaccines by using the RNA of a patients' own cancer cells as a template for the mRNA inside our nanoparticles. We also packaged our cancer vaccine inside of nanoparticles made up of specialized lipids, or fat molecules. We maximized the amount of mRNA packaged within each nanoparticle by sandwiching them between lipid layers like the layers of an onion. In this way, we increase the likelihood that the mRNA molecules in our nanoparticles produce enough tumor antigens from that patient's cancer to activate an immune response.

Also, instead of injecting nanoparticles into the skin, muscle or directly into the tumor, as is commonly done for many therapeutic cancer vaccines, our mRNA nanoparticles are injected into the bloodstream. From there, they travel to organs throughout the body involved in the immune response to teach the body to fight against the cancer. By doing so, we've found that the immune system launches a near immediate and powerful response. Within six hours of receiving the vaccine, there is a significant increase in the amount of blood markers connected to immune activation.

Looking to the future

Our mRNA-based vaccines are currently undergoing early-phase clinical trials to treat real patients with brain cancer.

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We administered our mRNA-based vaccine to four adult patients with glioblastoma who had relapsed after previous treatment. All patients survived several months longer than the expected average survival at this advanced stage of illness. We expect to treat children with a type of brain tumor called pediatric high-grade glioma by the end of the year.

Importantly, mRNA vaccines can be developed to treat any kind of cancer, childhood brain tumors. Our Pediatric Cancer Immunotherapy Initiative focuses on developing new immune-based therapies for children afflicted with cancer. After developing an mRNA vaccine for glioma in chidren, we will expand to treat other kinds of pediatric brain cancers like medulloblastoma and potentially treat other kinds of cancers like skin cancer and bone cancer.

We are hopeful that mRNA-based vaccines may to more children being cured of their brain tumors.The Conversation

Christina von Roemeling, Assistant Professor of Neurosurgery, University of Florida and John Ligon, Assistant Professor of Hematology, University of Florida

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

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