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Artificial Intelligence

LSU CS Professor Studies COVID-19 Disparities on Social Media

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BATON ROUGE, La., July 01, 2020 (GLOBE NEWSWIRE) — During the COVID-19 pandemic, a plethora of information has gone out from various news sources about how the virus is being tracked, how it is spread, how many cases exist, and so forth. The problem is much of this vital information can be inaccurate, leaving people to ignore advice from public officials. For this reason, LSU Computer Science and Engineering Assistant Professor Kisung Lee and LSU Environmental Sciences Professor Nina Lam are evaluating how a population reacts to multiple sources of information, hoping to eliminate disparities in the messaging.“Studying different COVID-19 responses to trustworthy information will contribute new perspectives and improve our fundamental understanding of the human aspects of information trustworthiness during a pandemic,” Lee said.Lee, principal investigator on the project, and Lam recently received a $200,000 grant from the National Science Foundation for the project and will have University of Washington Center for Studies in Demography & Ecology Director Sara Curran and Cybersecurity Research Fellow Jessica Beyer work alongside them.Lee will collect and analyze Twitter and linked media data using artificial intelligence-based techniques; Lam will map the data into administrative regions and analyze the data geographically (state- and county-level comparisons); and Curran and Beyer will collect policy and media source trustworthiness data and analyze it with other contextual information, such as media framing. Data will be collected and analyzed in Louisiana and Washington.They will collect three waves of Twitter and associated data to compare sentiment and language use patterns among users and analyze how these characteristics evolve through the recognition of the emergency, the peak of the crisis, and the mitigation of the pandemic in the U.S. The tweets and entities will be classified for relevance (individual, organization, or bot) with derived age and location. The tweets will be associated with daily disease-specific rates and annual demographic and socio-economic information.“Data about the surrounding information context, including reporting trends and framing of the crisis, sources of health information, and information-seeking behavior about COVID-19, will provide tools for assessing the validity and reliability of our inferences about the patterns of sentiment and language use,” Lee said. “This project will provide insight for targeting effective public messaging by public health and government officials during a crisis and ultimately improve disaster resilience.”Like us on Facebook (@lsuengineering) or follow us on Twitter and Instagram (@lsuengineering).​Josh Duplechain
LSU College of Engineering
225-578-5706
[email protected]

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Artificial Intelligence

PolyU research finds improving AI large language models helps better align with human brain activity

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HONG KONG, May 27, 2024 /PRNewswire/ — With generative artificial intelligence (GenAI) transforming the social interaction landscape in recent years, large language models (LLMs), which use deep-learning algorithms to train GenAI platforms to process language, have been put in the spotlight. A recent study by The Hong Kong Polytechnic University (PolyU) found that LLMs perform more like the human brain when being trained in more similar ways as humans process language, which has brought important insights to brain studies and the development of AI models.

Current large language models (LLMs) mostly rely on a single type of pretraining – contextual word prediction. This simple learning strategy has achieved surprising success when combined with massive training data and model parameters, as shown by popular LLMs such as ChatGPT. Recent studies also suggest that word prediction in LLMs can serve as a plausible model for how humans process language. However, humans do not simply predict the next word but also integrate high-level information in natural language comprehension. 
A research team led by Prof. Li Ping, Dean of the Faculty of Humanities and Sin Wai Kin Foundation Professor in Humanities and Technology at PolyU, has investigated the next sentence prediction (NSP) task, which simulates one central process of discourse-level comprehension in the human brain to evaluate if a pair of sentences is coherent, into model pretraining and examined the correlation between the model’s data and brain activation. The study has been recently published in the academic journal Sciences Advances.
The research team trained two models, one with NSP enhancement and the other without, both also learned word prediction. Functional magnetic resonance imaging (fMRI) data were collected from people reading connected sentences or disconnected sentences. The research team examined how closely the patterns from each model matched up with the brain patterns from the fMRI brain data.
It was clear that training with NSP provided benefits. The model with NSP matched human brain activity in multiple areas much better than the model trained only on word prediction. Its mechanism also nicely maps onto established neural models of human discourse comprehension. The results gave new insights into how our brains process full discourse such as conversations. For example, parts of the right side of the brain, not just the left, helped understand longer discourse. The model trained with NSP could also better predict how fast someone read – showing that simulating discourse comprehension through NSP helped AI understand humans better.
Recent LLMs, including ChatGPT, have relied on vastly increasing the training data and model size to achieve better performance. Prof. Li Ping said, “There are limitations in just relying on such scaling. Advances should also be aimed at making the models more efficient, relying on less rather than more data. Our findings suggest that diverse learning tasks such as NSP can improve LLMs to be more human-like and potentially closer to human intelligence.”
He added, “More importantly, the findings show how neurocognitive researchers can leverage LLMs to study higher-level language mechanisms of our brain. They also promote interaction and collaboration between researchers in the fields of AI and neurocognition, which will lead to future studies on AI-informed brain studies as well as brain-inspired AI.”
Media ContactMs Annie WongSenior Manager, Public AffairsTel: +852 3400 3853Email: [email protected] 

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VivaTech 2024: a record-breaking event

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PARIS, May 27, 2024 /PRNewswire/ — VivaTech 2024 broke records with more than 165,000 visitors over four days, a 10% increase over 2023. The event welcomed 13,500 start-ups, a 20% increase over the previous year.

A BUSINESS AND FINANCE ACCELERATOR
VivaTech has established itself as a key business event, generating more than 400,000 online business connections this year. Startups forged business relationships with companies from 25 sectors and met over 2,000 investors.
VIVA TECHNOLOGY CONFIRMS ITS INTERNATIONAL APPEAL
The event attracted representatives from more than 120 countries and 40 national pavilions. Japan, the country of the year, showcased its ecosystem with a ministerial delegation and more than 40 startups. Africa was also in the spotlight with the Africa Tech Lab and the AfricaTech Awards, honouring innovative startups such as Schoolz, Rology and Inclusivity Solutions.
AI AND SUSTAINABLE TECH AT THE HEART OF THE PROGRAMME
VivaTech 2024 showcased the latest advances in artificial intelligence, with nearly 40% of exhibitors dedicated to this technology. Sustainable tech was also in the spotlight, especially through the Impact Bridge, a space dedicated to initiatives for a sustainable future. VivaTech’s environmental efforts were rewarded with ISO 20-121 certification.
DIVERSITY MORE THAN EVER IN VIVATECH’S DNA 
Diversity took centre stage where over 40% of speakers were women. Among the most notable initiatives, the Female Founder Challenge rewarded Albane Dersy from Inbolt. At the same time, Femtech France took advantage of the event to launch its second Femtech industry barometer.
THE MEETING PLACE FOR REVEALS, EXCLUSIVITIES AND INNOVATIONS
For four days, VivaTech was the scene of numerous revelations, with some fifty worldwide or European exclusives unveiled. Among these, Tesla’s Cybertruck made its first appearance in France, marking a highlight of the event.
INTERNATIONAL SPEAKERS
VivaTech 2024 consolidated its position as the must-attend technology event with over 400 international speakers sharing their visions on AI and sustainable tech. Speakers included Elon Musk, John Kerry, Eric Schmidt, Arthur Mensch, Robin Li, Linda Yaccarino and Serena and Venus Williams. Institutional figures such as Fumio Kishida, Bruno Le Maire and Thierry Breton also took an active part in the debates.
WE LOOK FORWARD TO SEEING YOU FROM 11 TO 14 JUNE 2025 AT PARIS PORTE DE VERSAILLES!
Contact: [email protected]
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View original content:https://www.prnewswire.co.uk/news-releases/vivatech-2024-a-record-breaking-event-302156012.html

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Only Much Louder’s AI-powered influencer marketing tech, Hypothesis, expands globally, to empower brands to connect with international creators

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OML Entertainment’s Hypothesis is targeting the Asia–Pacific Region, Middle East, Africa, and USA by 2025.Hypothesis will open borders for brands and agencies, facilitating a region-agnostic global platformMUMBAI, India, May 27, 2024 /PRNewswire/ — Only Much Louder’s AI-powered influencer marketing tech, Hypothesis, expands its global footprint, after revolutionizing the Indian influencer market. In the first phase, Hypothesis will be available in the Asia–Pacific region (Singapore, Australia, Malaysia, Philippines, Vietnam, Thailand), Middle Eastern countries (Abu Dhabi, GCC nations, Egypt, Lebanon, Saudi Arabia, Kuwait, Qatar) as well as in Africa (Kenya, Nigeria, South Africa) and the USA.

Himani Agrawal, Senior Vice President, Hypothesis-OML, said, “At Hypothesis, we’re proud to offer a comprehensive kit for creator evaluation using 100+ data points. We provide the ultimate tool for your marketing arsenal. This is made even more convenient with our self-serve mode, empowering brands to initiate impactful influencer campaigns independently.”
Hypothesis streamlines data-driven influencer marketing globally, after recognising a critical disconnect between creator technology and services. Hypothesis was created with an inherent potential to serve a global audience, by empowering brands and agencies to transcend geographical limitations and unite discovery, outreach, and analytics in a single, user-friendly platform. This will accelerate the growth of the creator economy, creating opportunities for creators and brands.
Gunjan Arya, CEO of OML Entertainment, said, “We will be closely monitoring the milestones of Hypothesis to infiltrate the markets at the rate of 5–10% in the first year. We will also keep an eye on the acquisition rate, which is aimed to rise by 15–20%. Besides, we seek to derive over 35% of revenue from our global expansion efforts.”
With Hypothesis, OML is strategizing to expand into markets like Australia, the Asia–Pacific, the Middle East, and Africa, due to the region’s influencer marketing industry, which stands at 33.4% CAGR. Regions like the USA and the MENA have emerged as key players that are driven by advanced technologies and demand for data analytics.
Leveraging OML’s successful presence in Southeast Asia, the Middle East, Africa, and Eastern Europe, Hypothesis is set for a smooth rollout. OML’s established network, combined with their in-house expertise, will provide a strong foundation for this endeavor.
For details, visit hyp.io
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