Saturday, November 18, 2023

New water treatment method can generate green energy

UNIVERSITY OF GOTHENBURG

Researchers from ICIQ in Spain have designed micromotors that move around on their own to purify wastewater. The process creates ammonia, which can serve as a green energy source. Now, an AI method developed at the University of Gothenburg will be used to tune the motors to achieve the best possible results.

Micromotors have emerged as a promising tool for environmental remediation, largely due to their ability to autonomously navigate and perform specific tasks on a microscale. The micromotor is comprised of a tube made of silicon and manganese dioxide in which chemical reactions cause the release of bubbles from one end. These bubbles act as a motor that sets the tube in motion.

Researchers from the Institute of Chemical Research of Catalonia (ICIQ) have built a micromotor covered with the chemical compound laccase, which accelerates the conversion of urea found in polluted water into ammonia when it comes into contact with the motor.

Green energy source

“This is an interesting discovery. Today, water treatment plants have trouble breaking down all the urea, which results in eutrophication when the water is released. This is a serious problem in urban areas in particular,” says Rebeca Ferrer, a PhD student at Doctor Katherine Villa´s group at ICIQ.

Converting urea into ammonia offers other advantages as well. If you can extract the ammonia from the water, you also have a source of green energy as ammonia can be converted into hydrogen.

There is a great deal of development work to be done, with the bubbles produced by the micromotors posing a problem for researchers.

“We need to optimise the design so that the tubes can purify the water as efficiently as possible. To do this, we need to see how they move and how long they continue working, but this is difficult to see under a microscope because the bubbles obscure the view,” Ferrer explains.

Much development work remains

However, thanks to an AI method developed by researchers at the University of Gothenburg, it is possible to estimate the movements of the micromotors under a microscope. Machine learning enables several motors in the liquid to be monitored simultaneously.

“If we cannot monitor the micromotor, we cannot develop it. Our AI works well in a laboratory environment, which is where the development work is currently under way,” says Harshith Bachimanchi, a PhD student at the Department of Physics, University of Gothenburg.

The researchers have trouble saying how long it will be before urban water treatment plants can also become energy producers. Much development work remains, including on the AI method, which needs to be modified to work in large-scale trials.

“Our goal is to tune the motors to perfection,” Bachimanchi ends.

JOURNAL

Nanoscale

DOI

10.1039/D3NR03804A

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Bubble-propelled micromotors for ammonia generation†

Ultrafine particles from traffic disturb human olfactory cell function

Peer-Reviewed Publication

UNIVERSITY OF EASTERN FINLAND

Exposure to ultrafine particles from traffic alters the expression of many genes in human olfactory mucosa cells, a new study shows. The study, led by the University of Eastern Finland, is the first to combine an analysis of emissions from different diesel fuels and exhaust after-treatment systems with an examination of their effects in a human-derived cell model of the olfactory mucosa. The findings were published in Science of the Total Environment.

Particle emissions from road traffic have been regulated in the EU for decades, but emissions of ultrafine particles with a diameter less than 100 nanometres in size aren’t monitored or restricted yet.

The human olfactory mucosa is a tissue directly exposed to the environment and in direct contact with the brain.

“The olfactory system has been found to mediate the effects of environmental pollutants on the brain, thus contributing to the pathogenesis of brain diseases. However, the exact signalling pathways through which the effects are mediated remain unknown,” says first author, Doctoral Researcher Laura Mussalo of the Kanninen Lab at the University of Eastern Finland.

The study explored molecular-level changes occurring in human olfactory mucosa cells when exposed to different emissions derived from traffic. The researchers examined the effects of emissions on gene expression, i.e., what kind of alterations emissions cause, and what kind of mechanisms they activate. The researchers also examined whether fossil and renewable diesel fuels cause different effects, and how modern after-treatment devices, such as particulate filters, affect emissions.

The olfactory mucosa cells used in the study were obtained from voluntary donors, collected in collaboration with Kuopio University Hospital. The multidisciplinary study combined clinical medicine, gene research, molecular biology, environmental toxicology and aerosol physics.

Effects on inflammatory response and xenobiotic metabolism

The particle samples used in the exposure studies were collected by VTT Technical Research Centre of Finland, and they were analysed and characterised by VTT and Tampere University. The samples were collected from exhausts of a heavy-duty-engine vehicle run on paraffinic renewable diesel and on regular fossil diesel. The third sample was a combination of the same renewable diesel and cleaner engine technology complying with the Euro 6d-temp standard.

All emissions contained ultrafine particles. In addition, emissions from both renewable and fossil diesel contained a significant amount of polycyclic aromatic hydrocarbons (PAHs) and reactive nitrogen compounds. However, renewable diesel combined with cleaner engine technology produced very little emissions.

Exposure to ultrafine particles altered human olfactory mucosa cell function, and different fuels and engines caused different adverse effects. Furthermore, molecular-level analysis revealed disturbance in countless systems that regulate cell function. Exposure to emissions from both renewable and fossil diesel significantly altered the expression of genes associated with inflammatory response, xenobiotic metabolism, olfactory signalling and olfactory mucosa integrity. However, renewable diesel caused less adverse effects than fossil diesel. Emissions from renewable diesel run on cleaner engine technology caused only negligible alterations in cell function, demonstrating the efficiency of engine after-treatment devices.

The findings back earlier studies suggesting that PAHs may disturb the inflammatory response and xenobiotic metabolism in human olfactory mucosa cells, and that ultrafine particles may mediate adverse effects to the brain via the olfactory pathway. The study offers important insight into the adverse effects of ultrafine particles in a human-derived cell model of the olfactory mucosa, providing a basis for possible measures to mitigate and prevent toxicological hazards.

The study constitutes part of TUBE project, which is funded by the Horizon 2020 programme of the European Union. The study has also received funding from the Kuopio Area Respiratory Foundation, the Finnish Brain Foundation, Yrjö Jahnsson Foundation, and Päivikki and Sakari Sohlberg Foundation.

JOURNAL

Science of The Total Environment

DOI

10.1016/j.scitotenv.2023.167038

ARTICLE TITLE

Emissions from modern engines induce distinct effects in human olfactory mucosa cells, depending on fuel and aftertreatment.

States with legalized medical marijuana see decline in nonmedical opioid use

Rutgers researcher explores cannabis as a substitute for opioid use

Peer-Reviewed Publication

RUTGERS UNIVERSITY

Medical cannabis legalization is associated with a decrease in the frequency of nonmedical prescription opioid use, according to a Rutgers study.

The study, published in the International Journal of Mental Health and Addiction, examined data from a nationally representative survey of adults who reported nonmedical prescription opioid use – or using prescription medications without a prescription or in a manner other than prescribed.

According to the study, when states implement medical cannabis laws, there is a 0.5 to 1.5 percentage point decrease in regular to frequent (up to or greater than once per week on average) nonmedical prescription opioid use among people who reported using opioids in the previous year. However, these reductions were concentrated in people who met diagnostic criteria for cannabis addiction.

Still, the pros of legalizing marijuana to address risky opioid use should be considered alongside the cons, according to Hillary Samples, faculty member at the Center for Pharmacoepidemiology and Treatment Science in the Rutgers Institute for Health, Health Care Policy and Aging Research and lead author of the study.

“There might be some benefits to allowing legal access to medical cannabis in the context of opioid-related harms,” Samples said. “However, from a policy perspective, there are much more effective interventions to address the ongoing overdose crisis, such as increasing access to treatment for opioid addiction.”

According to the Centers for Disease Control and Prevention, the rate of drug overdose deaths rose more than 14 percent from 2020 to 2021 in the United States. To understand approaches to mitigate this crisis, researchers have examined whether cannabis serves as an alternative to opioid use as cannabis might help with pain and symptoms of opioid withdrawal.

With existing research showing mixed findings on the relationship between medical cannabis legalization and opioid use, a team of researchers led by Samples sought to contribute to this evidence.

Samples, an assistant professor of health systems and policy at the Rutgers School of Public Health, said the results suggest people may be replacing opioids with cannabis, but because the decrease in opioid use is modest and limited to high-risk cannabis users, study researchers call for investment in opioid addiction treatment.

The researchers said future studies should seek to understand whether the reductions in the frequency of nonmedical opioid use are meaningful in relation to the widespread opioid addiction crisis as well as whether the reductions in opioid use coincide with increases in cannabis use disorder.

“Policymakers should weigh the overall evidence on the effectiveness of various approaches to reduce opioid-related problems and consider potential trade-offs,” Samples said.

Coauthors of the study include Natalie Levy, Emilie Bruzelius, Luis Segura, Pia Mauro, Christine Mauro and Silvia Martins of the Columbia University Mailman School of Public Health and Anne Boustead of the University of Arizona.

JOURNAL

International Journal of Mental Health and Addiction

DOI

10.1007/s11469-023-01191-y

METHOD OF RESEARCH

Data/statistical analysis

SUBJECT OF RESEARCH

People

ARTICLE TITLE

Association Between Legal Access to Medical Cannabis and Frequency of Non-Medical Prescription Opioid Use Among U.S. Adults

New study finds association between insecticide exposure and lower sperm concentration in adult men

Comprehensive systematic review of 25 studies over nearly 50 years reveals consistent evidence of associations between insecticide exposure and lower sperm concentration

Peer-Reviewed Publication

GEORGE MASON UNIVERSITY

Key findings: association between insecticide exposure and lower sperm concentration in adult men — VIDEO:
DEAN MELISSA J. PERRY DISCUSSES HER LATEST PAPER THAT FOUND AN ASSOCIATION BETWEEN INSECTICIDE EXPOSURE AND LOWER SPERM CONCENTRATION IN ADULT MEN. THE COMPREHENSIVE SYSTEMATIC REVIEW OF 25 STUDIES OVER NEARLY 50 YEARS REVEALS CONSISTENT EVIDENCE OF ASSOCIATIONS BETWEEN INSECTICIDE EXPOSURE AND LOWER SPERM CONCENTRATION.

HIGHER QUALITY VERSION AVAILABLE ON YOUTUBE AND UPON REQUEST: HTTPS://YOUTU.BE/MLRJATFCEIQ
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CREDIT: GEORGE MASON UNIVERSITY COLLEGE OF PUBLIC HEALTH

New study finds association between insecticide exposure and lower sperm concentration in adult men

Comprehensive systematic review of 25 studies over nearly 50 years reveals consistent evidence of associations between insecticide exposure and lower sperm concentration

FAIRFAX, Va – Melissa J. Perry, Sc.D., MHS, dean of the George Mason University College of Public Health, and a team of researchers including Lauren Ellis, MPH, doctoral student at Northeastern University, found in a new systematic review that there is a strong association between insecticide exposure and lower sperm concentration in adult men globally.

“Understanding how insecticides affect sperm concentration in humans is critical given their ubiquity in the environment and documented reproductive hazards. Insecticides are a concern for public health and all men, who are exposed primarily through the consumption of contaminated food and water,” says Ellis.

The team reviewed nearly five decades of human evidence regarding the health impacts of exposure to two widely used insecticide classes, organophosphates and N-methyl carbamates, and found consistent associations with lower sperm concentration, which warrants concern, particularly in light of observed downward trends in semen quality demonstrated by other studies.

“This review is the most comprehensive review to date, sizing up more than 25 years of research on male fertility and reproductive health. The evidence available has reached a point that we must take regulatory action to reduce insecticide exposure,” says Dr. Perry, the senior author on the paper.

The research team systematically reviewed 25 human studies of occupational and environmental insecticide exposure conducted over the course of nearly 50 years. The study revealed consistent evidence of robust associations between insecticide exposure and lower sperm concentration.

“Adult Organophosphate and Carbamate Insecticide Exposure and Sperm Concentration: A Systematic Review and Meta-Analysis of the Epidemiological Evidence” will be published online in the peer-reviewed journal Environmental Health Perspectives on November 15. Once published, the paper will be available here. The full paper is available now under embargo. For a copy of the study or to speak with the authors, please email mthomp7@gmu.edu.

About College of Public Health at George Mason University

The College of Public Health at George Mason University is the first College of Public Health in Virginia combining public health transdisciplinary research, education, and practice in the Commonwealth as a national exemplar. The College enrolls more than 1,900 undergraduate and 1,300 graduate students in our nationally recognized programs, including six undergraduate degrees, eight master’s degrees, five doctoral degrees, and six professional certificate programs. The College is comprised of the School of Nursing and the Departments of Global and Community Health, Health Administration and Policy, Nutrition and Food Studies, and Social Work.

JOURNAL

Environmental Health Perspectives

DOI

10.1289/EHP12678

METHOD OF RESEARCH

Meta-analysis

SUBJECT OF RESEARCH

People

ARTICLE TITLE

Adult Organophosphate and Carbamate Insecticide Exposure and Sperm Concentration: A Systematic Review and Meta-Analysis of the Epidemiological Evidence

ARTICLE PUBLICATION DATE

15-Nov-2023

New deep learning AI tool helps ecologists monitor rare birds through their songs

Peer-Reviewed Publication
BRITISH ECOLOGICAL SOCIETY

IMAGE:
DUNLIN SPECTROGRAM
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CREDIT: NICOLAS LECOMTE

Researchers have developed a new deep learning AI tool that generates life-like birdsongs to train bird identification tools, helping ecologists to monitor rare species in the wild. The findings are presented in the British Ecological Society journal, Methods in Ecology and Evolution.
Identifying common bird species through their song has never been easier, with numerous phone apps and software available to both ecologists and the public. But what if the identification software has never heard a particular bird before, or only has a small sample of recordings to reference? This is a problem facing ecologists and conservationists monitoring some of the world’s rarest birds.
To overcome this problem, researchers at the University of Moncton, Canada, have developed ECOGEN, a first of its kind deep learning tool, that can generate lifelike bird sounds to enhance the samples of underrepresented species. These can then be used to train audio identification tools used in ecological monitoring, which often have disproportionately more information on common species.
The researchers found that adding artificial birdsong samples generated by ECOGEN to a birdsong identifier improved the bird song classification accuracy by 12% on average.
Dr Nicolas Lecomte, one of the lead researchers, said: “Due to significant global changes in animal populations, there is an urgent need for automated tools, such acoustic monitoring, to track shifts in biodiversity. However, the AI models used to identify species in acoustic monitoring lack comprehensive reference libraries.
“With ECOGEN, you can address this gap by creating new instances of bird sounds to support AI models. Essentially, for species with limited wild recordings, such as those that are rare, elusive, or sensitive, you can expand your sound library without further disrupting the animals or conducting additional fieldwork.”
The researchers say that creating synthetic bird songs in this way can contribute to the conservation of endangered bird species and also provide valuable insight into their vocalisations, behaviours and habitat preferences.
The ECOGEN tool has other potential applications. For instance, it could be used to help conserve extremely rare species, like the critically endangered regent honeyeaters, where young individuals are unable to learn their species' songs because there aren’t enough adult birds to learn from.
The tool could benefit other types of animal as well. Dr Lecomte added: “While ECOGEN was developed for birds, we’re confident that it could be applied to mammals, fish (yes they can produce sounds!), insects and amphibians.”
As well as its versatility, a key advantage of the ECOGEN tool is its accessibility, due to it being open source and able to used on even basic computers.
ECOGEN works by converting real recordings of bird songs into spectrograms (visual representations of sounds) and then generating new AI images from these to increase the dataset for rare species with few recordings. These spectrograms are then converted back into audio to train bird sound identifiers. In this study the researchers used a dataset of 23,784 wild bird recordings from around the world, covering 264 species.
-ENDS-

Audiomoth acoustic monitoring box, used by ecologists to record wild animals.

CREDIT

Nicolas Lecomte

Long-tailed Jaeger

CREDIT

Nicolas Lecomte

JOURNAL

Methods in Ecology and Evolution

DOI

10.1111/2041-210X.14239

METHOD OF RESEARCH

Computational simulation/modeling

SUBJECT OF RESEARCH

Animals

ARTICLE TITLE

ECOGEN: Bird sounds generation using deep learning

ARTICLE PUBLICATION DATE

15-Nov-2023

HKU develops novel ‘AI virtual patients’ diagnostic application Breaking spatial and geographical barriers for medical training Revolutionizing global medical education exchanges

Business Announcement
THE UNIVERSITY OF HONG KONG

IMAGE:
DR MICHAEL CO TIONG-HONG (MIDDLE) AND DR JOHN YUEN TSZ-HON (SECOND RIGHT) ALONG WITH THEIR STUDENTS, SHOWCASING THE NOVEL 'AI VIRTUAL PATIENTS' DIAGNOSTIC APPLICATION WHICH BREAKS SPATIAL AND GEOGRAPHICAL BARRIERS.
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CREDIT: THE UNIVERSITY OF HONG KONG

With the rapid development and extensive applications of generative artificial intelligence (AI) technology across various sectors, Dr Michael Co Tiong-hong from the LKS Faculty of Medicine, the University of Hong Kong (HKUMed), and Dr John Yuen Tsz-hon from the Department of Computer Science, HKU, have jointly developed Hong Kong’s first ‘AI virtual patients’ diagnostic application for training medical students. Leveraging generative AI technology and real-life surgical cases, the research team has designed ‘humanised’ AI virtual patients with distinct personalities and medical histories, which allow medical students to virtually simulate interactions with patients during bedside consultations. This initiative greatly enhances the students’ professional skills and ability to accurately gather patients’ medical history.
To provide students with a more diverse range of clinical learning opportunities, HKUMed collaborated with the National University of Singapore (NUS) to introduce cross-regional medical cases in the diagnostic app. This revolutionary approach has redefined traditional medical teaching methods. Looking ahead, HKUMed also plans to collaborate with other overseas medical schools.
About the ‘AI virtual patients’ diagnostic application
The virtual mode of clinical teaching provides personalised patient cases tailored to the specific needs of individual medical students. In 2020, Dr Co and Dr Yuen initiated the development of an AI chatbot to help HKUMed students who could not attend hospital-based classes amid the pandemic. In 2021, a system prototype was available for trial with a selected group of HKUMed students. Teachers could design virtual patients suited to each student’s diagnostic skill level. Students would compile the medical records for case discussions and analysis with their teachers. In 2022, the outcomes of this innovative teaching mode were published in an internationally renowned journal (link to the publication).
Through continuous research and improvement, the HKU team developed Hong Kong’s first ‘AI virtual patient’ diagnostic application. Integrated with generative AI technology, the latest model of the chatbot goes beyond standardised and monotonous replies, providing highly dynamic and lively responses. Even for the same medical case, the ‘AI virtual patient’ is capable of providing distinct responses, interacting with students in a remarkably human-like and personality-driven manner.
Significance and Impact
This innovative virtual clinical teaching mode provides personalised teaching cases with equal access for all students, and addresses the limitations of the traditional teaching mode. Dr Co explained, ‘Traditional clinical teaching relies heavily on in-person interaction with real patients. But for various reasons, like scheduling difficulties, not all medical students have equal opportunities to engage in face-to-face consultations. The “AI virtual patients” app allows us to overcome time and geographical barriers, offering our students access to practice with rare cases and providing them with invaluable clinical experience. Through a virtual learning environment, equipped with a wide range of diverse patient cases, medical students can enhance their patient history-taking skills and improve the accuracy of their diagnoses.’
Dr John Yuen Tsz-hon, from the Department of Computer Science, HKU, said, ‘The “AI virtual patients” app has the capacity to accumulate information, resulting in each response it generates having a slight variation in tone and wording. This enables more authentic interactions between doctors and “patients”. Additionally, teachers can utilise the data collected by the system to conduct in-depth analysis and assessment of students’ performance, which allows them to provide specific feedback and guidance to individual students, ultimately enhancing the efficiency of clinical teaching.’
Virtual clinical teaching can remove spatial and geographical barriers, fostering international exchange in medical education. In early October this year, Dr Co collaborated with Dr Serene Goh, a specialist surgeon from the National University of Singapore, to launch the world's first cross-regional virtual clinical teaching programme. The two doctors devised distinct patient cases for students in their respective locations to practise consultations utilising the ‘AI virtual patients’ app. Through online case discussions, the medical students jointly analysed patients’ imaging studies, endoscopic images and pathological slides in online case discussions.
‘Collaboration and exchange with medical schools in other regions will enable medical students to learn from each other's strengths, broaden their horizons and knowledge, and promote international cooperation and development in medical education. This will set the foundation for boundless educational innovations in the future,’ Dr Co added.
The cross-regional virtual clinical teaching collaboration between Hong Kong and Singapore has set a remarkable precedent for international medical teaching. The Department of Surgery at the University of Edinburgh's Western General Hospital has expressed interest in joining future endeavours in virtual surgical clinical teaching.
Media enquiries
Please contact LKS Faculty of Medicine of The University of Hong Kong by email (medmedia@hku.hk).

JOURNAL

Cell

DOI

10.1016/j.heliyon.2022.e09751

METHOD OF RESEARCH

Experimental study

AI supporting creative Industries

NYC Media Lab at NYU Tandon School of Engineering and Bertelsmann partner on the Creative Industries and AI Challenge, focusing on books, music, film and television

Business Announcement

NYU TANDON SCHOOL OF ENGINEERING

NYC Media Lab (NYCML) and Bertelsmann unveiled the latest cohort joining the AI & the Creative Industries Challenge, a nine-week program in which teams explore new ways to use artificial intelligence (AI) to create digital content and reach new audiences for three Bertelsmann companies: Fremantle, Penguin Random House, and BMG. The teams are tasked with addressing how AI will impact these important creative industries.

This ongoing partnership, NYCML’s third project with Bertelsmann, will continue to build on new business frontiers enabled by technology. The four selected teams, from around the globe, come from various multidisciplinary backgrounds.

“Bertelsmann is deeply involved in experimenting with AI. Our Bertelsmann team will broaden their perspectives on this technology by teaming up with NYC Media Lab to work with this new cohort,” said Bertelsmann, Inc. Senior Director of Human Resources Freddie Helrich.

“Ensuring that the newest technologies are applied to the creative industries we have held near and dear to our hearts is a perfect example of why industry - Bertelsmann in this case - and academia should work hand in hand,” said Sayar Lonial NYC Media Lab Interim Executive Director and Associate Dean for Communications & Public Affairs at NYU Tandon. “We are excited to work with Bertelsmann to see how AI can support communications in all forms.”

The AI & the Creative Industries Challenge Teams

Author AI from Abelana VR

Mik Labanok, Denis Chernitsyn

Brooklyn, New York

Author AI, is a tool for publishers, producers, and digital marketers to create interactive, virtual experiences based on their characters and authors. Author AI represents the lore of a property through virtual assistants immersed in a theme-based environment and connected to a variety of third-party resources.

Abelana VR is a developer and publisher of virtual applications for education, training, and other knowledge-driven content. Its main production is focused on online multiplayer experiences created with a VR-first approach and designed to fit across a wide range of ecosystems, including VR, AR, mobile, and web.

Smartplayr from SAOViVO & Axle.ai

Elisa Hecker, Emiliano Billi, Nicolas J. Russo, Sam Bogoch

Buenos Aires (Argentina) and Boston (USA)

Smartplayr repurposes existing media into live streams while keeping it current and relevant using AI. They are leveraging AI in a number of ways to automate and optimize live streaming: Face detection for better screen composition and dynamic chyrons; Adaptive user interface to fit different aspect ratios; Scene detection to facilitate the reuse of pre-recorded content; Live transcription of breaking news to highlight important information.

They are a multidisciplinary team composed of two companies utilized by current newsrooms: SAOViVO, an open source software that turns video playlist into a live stream, and Axle.ai, a powerful media asset manager (MAM) and publishing solution.

Theater of Latent Possibilities from Speculative Devices + Cohab Labs

Ash Eliza Smith, Ryan Schmaltz, Robert Twomey, Jinku Kim, Patrick Coleman

Lincoln, Nebraska

Theater of Latent Possibilities focuses on the construction of workflows for pre-production and performance for TV, Film, and Theater. utilizing generative AI with sound, visuals, and writing. Their“writer’s room” tool allows for worldbuilding and co-creation with generative AI. Their system surfaces unique moments, unexpected connections, and latent narratives present in input datasets. At runtime, they employ these generative techniques for real-time performance—creating live, immersive, participatory experiences that hinge on the improvisatory dynamics of human-machine co-authorship.

The team is composed of artists, writers, musicians, engineers, and business practitioners exploring the frontiers of worldbuilding, co-creation, and generative AI in media and performance. They have published and performed our work in a range of international venues spanning academic conferences, arts festivals, and research institutes.

Wavetable

Johann Diedrick, Sylvia Ke

New York City

Wavetable is an innovative web-based platform for sound and music production, offering a swift and efficient solution for professionals in the music, publishing, and film/TV industries. Using text-to-audio generative models, Wavetable empowers creators to articulate their sonic visions using natural language. It then transforms these descriptions into tangible audio outputs that can serve as preliminary placeholders before custom, polished audio content is crafted. Wavetable expedites the realization of creative concepts, substantially shortening project timelines, while also affording creators the freedom to develop audio content autonomously.

The team possesses a distinctive blend of industry experience spanning both the technical and creative realms. Their unique background enables them to pursue seamless integrations of AI-driven solutions into the established workflows and industry-standard products of the creative sectors. Their approach to product development is characterized by a design-first mindset, prioritizing creating AI tools that are not only powerful but also intuitive, versatile, and accessible

Program Details

Teams will work with mentors from Bertelsmann’s music, book publishing, film and TV production, digital and investment arms. NYC Media Lab colleagues and academic partners will also provide direction and feedback to the teams. The Challenge will conclude in December with an internal Demo Day, where teams will demonstrate their project outcomes and discoveries.

About Bertelsmann

Bertelsmann is a media, services and education company that operates in about 50 countries around the world. It includes the entertainment group RTL Group, the trade book publisher Penguin Random House, the music company BMG, the service provider Arvato Group, Bertelsmann Marketing Services, the Bertelsmann Education Group and Bertelsmann Investments, an international network of funds. The company has 165,000 employees worldwide and generated revenues of €20.2 billion in the 2022 financial year. Bertelsmann stands for creativity and entrepreneurship. This combination promotes first-class media content and innovative service solutions that inspire customers around the world. Bertelsmann aspires to achieve climate neutrality by 2030.

About The NYC Media Lab

The NYC Media Lab connects media and technology companies with both NYU Tandon and industry affiliates to drive innovation, entrepreneurship and talent development. Our interdisciplinary community of innovators from industry and academia allows our network to gain valuable insights, explore the potential of emerging technology and address the challenges and opportunities created by the rapidly evolving digital media landscape. Learn more at engineering.nyu.edu/nyc-media-lab.