A new study on learning has provided insights into the balance between habitual and goal-directed behaviors, with implications for AI development. The research suggests that a balance between these two types of behavior is necessary for efficient and adaptable decision-making in AI systems.
SourceOkinawa Institute of Science and Technology (OIST) Graduate University·JournalNature Communications·TypeComputational simulation/modeling·DateJun 16, 2024
Researchers at Huazhong University have developed a revolutionary method for fast and accurate topology identification in complex dynamical networks. The new approach, FT-TIDCN, leverages finite-time stability theory to identify network topologies swiftly, addressing a common challenge in network science.
SourceBeijing Institute of Technology Press Co., Ltd·JournalCyborg and Bionic Systems·DateJun 1, 2024
Fluke 87V Industrial Digital Multimeter
Fluke 87V Industrial Digital Multimeter is a trusted meter for precise measurements during instrument integration, repairs, and field diagnostics.
A new study highlights the importance of differentiating between formal and functional competence in language learning models. Researchers argue that leveraging human neuroscience insights can help develop more powerful AIs that mimic the brain's modularity, leading to improved performance and natural user interaction.
SourceGeorgia Institute of Technology·JournalTrends in Cognitive Sciences·TypeSystematic review·DateMar 19, 2024
Researchers found that participants who were initially skeptical or disagreed with climate change or BLM became more supportive after conversing with GPT-3. The chatbot's response styles differed between topics, with more justification for human-caused climate change.
SourceUniversity of Wisconsin-Madison·JournalScientific Reports·TypeExperimental study·DateJan 25, 2024
A new app, MindEar, has shown promising results in reducing tinnitus symptoms in just weeks through a combination of cognitive behavioral therapy, mindfulness, and relaxation exercises. The app is now available for individuals to trial on their smartphones, offering hope for millions affected by tinnitus.
SourceMindEar·JournalFrontiers in Audiology and Otology·TypeRandomized controlled/clinical trial·DateJan 9, 2024
A new study from the University of Ottawa and Copenhagen Business School finds that removing human bias from organizational processes can lead to autonomous systems that create their own environments. This could limit human ability to recognize automation biases, notice environmental shifts, and take action.
SourceUniversity of Ottawa·JournalJournal of the Association for Information Systems·TypeLiterature review·DateDec 20, 2023
Aranet4 Home CO2 Monitor
Aranet4 Home CO2 Monitor tracks ventilation quality in labs, classrooms, and conference rooms with long battery life and clear e-ink readouts.
A study found that clinicians can be fooled by biased AI models even with provided explanations, leading to serious declines in accuracy. While accurate AI models improved diagnostic decisions for some demographics, biased models worsened decisions for others.
SourceMichigan Medicine - University of Michigan·JournalJAMA·DateDec 19, 2023
The European Union's AI act could enable AI to access our subconscious minds, potentially leading to manipulation. According to Ignasi Beltran de Heredia, only 5% of brain activity is conscious, and the remaining 95% operates subconsciously, making it difficult for us to control or even be aware of.
SourceUniversitat Oberta de Catalunya (UOC)·JournalRevista de la Facultad de Derecho de México·TypeLiterature review·DateNov 24, 2023
A Lancaster University academic argues that AI and algorithms contribute to polarization, radicalism, and political violence, posing a threat to national security. The paper examines how AI has been securitized throughout its history, highlighting the need for better understanding and management of its risks.
SourceLancaster University·JournalTechnology in Society·TypeCommentary/editorial·DateNov 2, 2023
Researchers found that participants preferred 60-70 options from ChatGPT, citing high perceived accuracy and increased intent to purchase. This contradicts traditional choice overload theories, highlighting the impact of personalized recommendations on consumer decision-making.
SourceRitsumeikan University·JournalJournal of Retailing and Consumer Services·TypeExperimental study·DateSep 26, 2023
Biased AI can limit climate predictions and misguide governments due to missing information from under-represented communities. Human-in-the-loop design can fill these 'data holes' by offering a sense check on used data and context.
SourceUniversity of Cambridge·JournalClimate Action·TypeMeta-analysis·DateAug 17, 2023
Rigol DP832 Triple-Output Bench Power Supply
Rigol DP832 Triple-Output Bench Power Supply powers sensors, microcontrollers, and test circuits with programmable rails and stable outputs.
The NERVE Center has developed test methods and metrics for various robots, identifying limitations to improve systems. The center's success grew its research capabilities through partnerships with NIST and the U.S. Army.
A study from the University of Georgia shows people who rely on algorithms for creative tasks don't improve their performance and are more likely to trust low-quality advice. Participants preferred algorithm-derived advice over human-based advice, even when confident in their answers.
SourceUniversity of Georgia·JournalScientific Reports·DateSep 20, 2022
Researchers at USC's Information Sciences Institute developed a method to train AI to understand analogies in Aesop's fables, enabling it to make creative connections between familiar and novel situations. The study found that humans approach analogical reasoning subjectively and interpretively, influencing the outcome.
SourceUniversity of Southern California·TypeContent analysis·DateJul 25, 2022
Apple iPhone 17 Pro
Apple iPhone 17 Pro delivers top performance and advanced cameras for field documentation, data collection, and secure research communications.
The university's new Robotics and Autonomous Systems Teaching and Innovation Center (RASTIC) will provide students with hands-on experience in robotics, autonomous systems, and self-driving technology. The lab aims to boost Massachusetts' competitiveness in the tech sector by supporting innovative projects and startups.
Researchers have developed a new method called Shared Interest that enables users to aggregate, sort, and rank individual explanations of a machine-learning model's reasoning. This technique uses quantifiable metrics to compare how well the model's reasoning matches human thinking, helping to uncover concerning trends in decision-making.
SourceMassachusetts Institute of Technology·DateApr 6, 2022