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A research team from Purdue University's Department of Computer Science and Institute for Digital Forestry, with collaborator Sren Pirk at Kiel University in Germany, has discovered that artificial intelligence can simulate tree growth and shape.

The DNA molecule encodes both tree shape and environmental response in one tiny, subcellular package. In work inspired by DNA, Bedrich Benes, professor of computer science, and his associates developed novel AI models that compress the information required for encoding tree form into a megabyte-sized neural model.

After training, the AI models encode the local development of trees that can be used to generate complex tree models of several gigabytes of detailed geometry as an output.

In two papers, one published in ACM Transactions on Graphics and the other in IEEE Transactions on Visualizations and Computer Graphics, Benes and his co-authors describe how they created their tree-simulation AI models.

"The AI models learn from large data sets to mimic the intrinsic discovered behavior," Benes said.

Non-AI-based digital tree models are quite complicated, involving simulation algorithms that consider many mutually affecting nonlinear factors. Such models are needed in endeavors such as architecture and urban planning, as well as in the gaming and entertainment industries, to make designs more realistically appealing to their potential clients and audiences.

After working with AI models for nearly 10 years, Benes expected them to be able to significantly improve the existing methods for digital tree twins. The size of the models was surprising, however. "It's complex behavior, but it has been compressed to rather a small amount of data," he said.

Co-authors of the ACM Transactions on Graphics paper were Jae Joong Lee and Bosheng Li, Purdue graduate students in computer science. Co-authors of the IEEE Transactions on Visualization and Computer Graphics paper were Li and Xiaochen Zhou, also a Purdue graduate student in computer science; Songlin Fei, the Dean's Chair in Remote Sensing and director of the Institute for Digital Forestry; and Sren Pirk of Kiel University, Germany.

The researchers used deep learning, a branch of machine learning within AI, to generate growth models for maple, oak, pine, walnut and other tree species, both with and without leaves. Deep learning involves developing software that trains AI models to perform specified tasks through linked neural networks that attempt to mimic certain functionalities of the human brain.

"Although AI has become seemingly pervasive, thus far it has mostly proved highly successful in modeling 3D geometries unrelated to nature," Benes said. These include endeavors related to computer-aided design and improving algorithms for digital manufacturing.

"Getting a 3D geometry vegetation model has been an open problem in computer graphics for decades," stated Benes and his co-authors in their ACM Transactions paper. Although some approaches to simulating biological behaviors are improving, they noted, "simple methods that would quickly provide many 3D models of real trees are not readily available."

Experts with biological expertise have traditionally developed tree-growth simulations. They understand how trees interact with environmental conditions. Understanding these complicated interactions depends upon characteristics bestowed upon the tree by its DNA. These include branching angles, which are much larger for pines than for oaks, for example. The environment, meanwhile, dictates other characteristics that can result in the same type of tree grown under two different conditions displaying completely different shapes.

"Decoupling the tree's intrinsic properties and its environmental response is extremely complicated," Benes said. "We looked at thousands of trees, and we thought, 'Hey, let AI learn it.' And maybe we can then learn the essence of tree form with AI."

Scientists typically build models based on hypotheses and observations of nature. As models created by humans, they have reasoning behind them. The researchers' models generalize behavior from several thousand trees' worth of input data that became encoded within the AI. Then the researchers validate that the models behave the way the input data behave.

The AI tree models' weakness is that they lack training data that describes real-world 3D tree geometry.

"In our methods, we needed to generate the data. So our AI models are not simulating nature. They are simulating tree developmental algorithms," Benes said. He aspires to reconstruct 3D geometry data from real trees inside a computer.

"You take your cellphone, take a picture of a tree, and you get a 3D geometry inside the computer. It could be rotated. Zoom in. Zoom out," he said. "This is next. And it's perfectly aligned with the mission of digital forestry."

More information: Jae Joong Lee et al, Latent L-systems: Transformer-based Tree Generator, ACM Transactions on Graphics (2023). DOI: 10.1145/3627101

Xiaochen Zhou et al, DeepTree: Modeling Trees with Situated Latents, IEEE Transactions on Visualization and Computer Graphics (2023). DOI: 10.1109/TVCG.2023.3307887

Journal information: ACM Transactions on Graphics

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AI learns to simulate how trees grow and shape in response to their environments - Tech Xplore

The National Academy of Sciences (NAS) has selected Eshan Chattopadhyay, assistant professor of computer science in the Cornell Ann S. Bowers College of Computing and Information Science, as the 2024 co-recipient of the Michael and Sheila Held Prize, along with collaborator David Zuckerman, professor of computer science at the University of Texas at Austin, for their novel work on randomized algorithms.

Given annually since 2018, the Held Prize honors "outstanding, innovative, creative, and influential research in the areas of combinatorial and discrete optimization, or related parts of computer science." The pair will receive the award, along with a $100,000 prize, at the NAS 161st Annual Meeting on April 28.

"I am deeply honored to receive this award and to have my work with David on randomness extractors recognized by the larger scientific community," Chattopadhyay said.

Read the entire story on the Cornell Bowers CIS website.

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Chattopadhyay receives the NAS Michael and Sheila Held Prize | Cornell Chronicle - Cornell Chronicle

LEXINGTON, Ky. (Jan. 22, 2024) Tiffany Clark found herself entangled in a challenging predicament this fall. She grappled with conflicting options as a looming decision deadline cast its shadow. Many young adults her age would have coveted the intricacy of Clarks dilemma: Which well-paying, potentially career-making summer internship should I choose the one nestled in the sunny theme park capital of the world or the other in glitzy proximity to the famed Hollywood sign?

A junior computer science major in the University of Kentuckys Stanley and Karen Pigman College of Engineering, Clark meticulously considered the prospect of interning for either Northrop Grumman in Redondo Beach, California, or Lockheed Martin in Orlando, Florida, come the summer of 2024.

Both alternatives starkly contrast Clarks upbringing in Caneyville, Kentucky. With its modest population of just over 500, the Grayson County community offers scarce professional prospects for individuals skilled in cybersecurity and software engineering.

Following the sudden death of her mother, Tiffany Clark was raised by her maternal grandmother and, later, her maternal aunt and grandfather, alongside her older brother. Throughout her formative years, their ventures seldom extended beyond close-knit Grayson Countys boundaries. With an expanded view of the world, however, she now grapples with the notion of continuing to reside in such a sparsely populated community.

My grandfathers lived there his entire life, Clark laughs. He wont even drive outside the county. If he has to go to Hardin County to look for tractor parts, he calls up his friends to take him. Hes happy living there and not leaving the county, and thats totally fine. I just could never do that.

Clark committed to attending UK without ever setting foot on its campus. Yet, this daring leap of faith sparked a transformative college experience, awakening in her a profound wanderlust for global exploration. A testament to this profound curiosity, she spent two weeks abroad in England and France last year as part of UKs Chellgren Center for Undergraduate Excellence. She aspires to leverage a career in cybersecurity to continue discovering the diverse facets of our increasingly interconnected world and maybe catch a bad guy or two along the way.

Its mainly about having an impact, Clark explains of her career aspirations. Politically, Im very neutral, but I can see that in terms of national security, the government does a lot of great things for us that we may never even know about, and cybersecurity plays a large part in that; so, Im looking into the FBI or the CIA, or a defense contracting company that provides products and does contracts with the government.

Because it can call upon skills in both computer and electrical engineering, Clark says that she enjoys the challenge of finding computer vulnerabilities and trying to find ways people can exploit or hack into systems. She says she did not own a computer until her senior year of high school. Now, however, she is breaking down barriers and staking her claim in the still-male-dominated field of computing.

Being a female computer scientist can be great, Clark explains. It can make you stand out. But it can also be a little intimidating, maybe a bit of impostor syndrome, because your class will be dominated by males. Even with my internship last summer, the team had six interns, and I was the only girl. And in my office, there was only one woman, so it adds a little bit of oh, I need to do great. I need to stand out, but I also needed to interact with these guys all the time.

Globally, only about a quarter of people in cybersecurity roles are female. As vice president of UKs chapter of the Society of Women Engineers, Clark works to empower her peers. Through outreach, she hopes to inspire women of all ages to consider taking STEM courses and develop an inclusive community within the Pigman College of Engineering. She learned about the possible internships at the Women in Engineering conference in Los Angeles, the worlds largest conference for women in engineering and technology.

A Presidential Scholar, Chellgren Fellow and a member of the UK Lewis Honors College, Clark says the support system she found at UK has been instrumental to her academic achievements. In particular, the mentorship she receives from Stanley and Karen Pigman has been particularly gratifying.

Im so thankful to be a Pigman Scholar because of the mentorship they provide, Clark said. Stan and Karen have my phone number! Theyll call us during midterms. Theyll ask Do you need help? What do you need? Have you gone to this resource, that resource? They understand how difficult the coursework can be. Just having that kind of motivation somebody telling you Good job, youre going to do great things is really motivating.

With the Pigmans encouragement, Clark has already completed two summer internships including one in Bostonfor defense contractor Riverside and is determined to take advantage of opportunities as they present themselves.

Clarks pivotal decision to attend UK, coupled with the expansive possibilities inherent in her chosen field and the encouragement and support of mentors, didnt just create opportunities; it shattered the confines of her small-town roots.

When I get older, I really would like to travel somewhere in Asia, like South Korea, Clark enthuses. I do enjoy traveling. I want to go to a lot of different places, but definitely Asia. Its a completely different culture. Going to England or even Paris, you can still see similarities to the U.S., and a lot of people there speak English. But Asia the culture is totally different.

The closest Clark may get to Asia in the immediate future, however, could be a visit to the China or Japan Pavilions at Epcot next summer. After thoughtful discussions with those whose insights she values and meticulously weighing the pros and cons associated with each internship, she ultimately chose the opportunity Lockheed Martin in balmy Orlando.

While I did ask people for their opinion, and they gave it, everyone including the Pigmans told me that this was my decision and they were both good offers, Clark says. No one would have been disappointed, no matter which offer I accepted. Everyone told me to go with my gut and do what I want because, ultimately, its my life and my future. Both offers would have been great, and Im just sad that I couldnt do both.

In the end, the choice boiled down to what is best suited for Clarks future.

I was given an offer in Northrop Grummans space unit, Clark explains of what ultimately decided the Solomonic decision. I believe that Lockheed Martins cyber unit will align better with my interests.

At Lockheed Martin, Clark will be working in Rotary and Mission Systems, working in software engineering with the Training, Logistics and Sustainment team. Clark hopes that her decision will eventually lead to a leadership position where she can one day follow in the steps of her mentors, the Pigmans, and give back to her community and alma mater.

They really encourage the circle of giving back once youve paid your dues, says Clark, who currently works part-time in the colleges philanthropy office. Id like to do something like that, to give back to UK and the Pigman College of Engineering because theyve had such an impact on me.

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Clark is breaking down barriers and staking her claim in cybersecurity field - UKNow

Image Credits: Kirillm / Getty Images

Will AI automate human jobs, and if so which jobs and when?

Thats the trio of questions a new research study from MITs Computer Science and Artificial Intelligence Laboratory (CSAIL), out this morning, tries to answer.

Theres been many attempts to extrapolate out and project how the AI technologies of today, like large language models, might impact peoples livelihoods and whole economies in the future.

Goldman Sachs estimates that AI could automate 25% of the entire labor market in the next few years. According to McKinsey, nearly half of all work will be AI-driven by 2055. A survey from the University of Pennsylvania, NYU and Princeton finds that ChatGPT alone could impact around 80% of jobs. And a report from the outplacement firm Challenger, Gray & Christmas suggests that AI is already replacing thousands of workers.

But in their study, the MIT researchers sought to move beyond what they characterize as task-based comparisons and assess how feasible it is that AI will perform certain roles and how likely businesses are to actually replace workers with AI tech.

Contrary to what one (including this reporter) might expect, the MIT researchers found that the majority of jobs previously identified as being at risk of AI displacement arent, in fact, economically beneficial to automate at least at present.

The key takeaway, says Neil Thompson, a research scientist at MIT CSAIL and a co-author on the study, is that the coming AI disruption might happen slower and less dramatically than some commentators are suggesting.

Like much of the recent research, we find significant potential for AI to automate tasks, Thompson told TechCrunch in an email interview. But were able to show that many of these tasks are not yet attractive to automate.

Now, in an important caveat, the study only looked at jobs requiring visual analysis that is, jobs involving tasks like inspecting products for quality at the end of a manufacturing line. The researchers didnt investigate the potential impact of text- and image-generating models, like ChatGPT and Midjourney, on workers and the economy; they leave that to follow-up studies.

In conductingthis study, the researchers surveyed workers to understand what an AI system would have to accomplish, task-wise, to fully replace their jobs. They then modeled the cost of building an AI system capable of doing all this, and also modeled whether businesses specifically non-farm U.S.-based businesses would be willing to pay both the upfront and operating expenses for such a system.

Early in the study, the researchers give the example of a baker.

A baker spends about 6% of their time checking food quality, according to the U.S. Bureau of Labor Statistics a task that could be (and is being) automated by AI. A bakery employing five bakers making $48,000 per year could save $14,000 were it to automate food quality checks. But by the studys estimates, a bare-bones, from-scratch AI system up to the task would cost $165,000 to deploy and $122,840 per year to maintain . . . and thats on the low end.

We find that only 23% of the wages being paid to humans for doing vision tasks would be economically attractive to automate with AI, Thompson said. Humans are still the better economic choice for doing these parts of jobs.

Now, the study does account for self-hosted, self-service AI systems sold through vendors like OpenAI that only need to be fine-tuned to particular tasks not trained from the ground up. But according to the researchers, even with a system costing as little as $1,000, theres lots of jobs albeit low-wage and multitasking-dependent that wouldnt make economic sense for a business to automate.

Even if we consider the impact of computer vision just within vision tasks, we find that the rate of job loss is lower than that already experienced in the economy, the researchers write in the study. Even with rapid decreases in cost of 20% per year, it would still take decades for computer vision tasks to become economically efficient for firms.

The study has a number of limitations, which the researchers to their credit admit. For example, it doesnt consider cases where AI can augment rather than replace human labor (e.g., analyze an athletes golf swing) or create new tasks and jobs (e.g., maintaining an AI system) that didnt exist before. Moreover, it doesnt factor in all the possible cost savings that can come from pre-trained models like GPT-4.

One wonders whether the researchers mightve felt pressure to reach certain conclusions by the studys backer, the MIT-IBM Watson AI Lab. The MIT-IBM Watson AI Lab was created with a $240 million, 10-year gift from IBM, a company with a vested interest in ensuring that AIs perceived as nonthreatening.

But the researchers assert this isnt the case.

We were motivated by the enormous success of deep learning, the leading form of AI, across many tasks and the desire to understand what this would mean for the automation of human jobs, Thompson said. For policymakers, our results should reinforce the importance of preparing for AI job automation...But our results also reveal that this process will take years, or even decades, to unfold and thus that there is time for policy initiatives to be put into place. For AI researchers and developers, this work points to the importance of decreasing the costs of AI deployments and of increasing the scope of how they can be deployed. These will be important for making AI economically attractive for firms to use for automation.

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New MIT CSAIL study suggests that AI wont steal as many jobs as expected - TechCrunch