Articles tagged with Generative Ai
Researchers found that postgraduate students selectively engage with GenAI tools when revising critical reading reports, focusing on key analytical dimensions. This strategic engagement is driven by academic goals, supervisor demands, and career aspirations.
Boston College researchers have developed an AI-assisted method to remove 'noise' from functional MRI brain data, a major obstacle for fMRI research. The new method, known as DeepCor, outperforms previous approaches and could pave the way for new discoveries about the brain and its disorders.
Insilico Medicine collaborates with Servier to develop novel therapeutics in oncology through AI-driven platform Pharma.AI. The partnership is focused on identifying promising targets and generating molecular structures with desired properties.
Insilico Medicine raised a total of HKD 2.277 billion in its largest Hong Kong biotech IPO, with 94,690,500 shares offered globally and oversubscribed by approximately 1427 times. The company aims to advance its mission of extending human productive longevity using AI-powered drug discovery and development.
As chatbots become more sophisticated, they are likely to generate and spread gossip, leading to reputational damage, shame, and social unrest. Drs. Joel Krueger and Lucy Osler warn that this 'feral' AI gossip can be particularly damaging due to its ability to operate unconstrained by human norms.
The new program focuses on advancing foundational research in AI, including innovation in language models and algorithmic efficiency. Google will support research grants, scholarships for students, and educational initiatives at the TAU Center.
Insilico Medicine showcases its Pharma.AI platform's capabilities in generating biologics and analyzing data to accelerate drug discovery. The company's latest updates include improved Generative Biologics, Chemistry42/Nach01, and PandaOmics features.
Researchers found that AIs consistently converged on 12 common themes despite diverse prompts, suggesting biases in training data. The models failed to generate novel or creative outputs, highlighting the need for anti-convergence mechanisms and human input for AI's creative potential.
Medical students used ChatGPT to analyze survey responses and identify common themes, finding method three yielded the highest accuracy. The study showcases the potential for AI to assist with qualitative research in medical education.
A new AI framework uncovers simple, understandable rules governing complex dynamics in nature and technology. The AI generates equations that accurately describe complex systems, revealing hidden variables that govern their behavior. This approach offers scientists a new way to leverage AI for understanding complex systems.
A new study warns that AI is racing ahead of safety checks in GP clinics, putting patients at risk. The research found that many GPs use AI tools without thorough evaluation or regulatory oversight, carrying risks like automation bias and loss of important social details.
Researchers propose integrating processing capability within memory units to reduce energy consumption and latency in AI applications. Inspired by the brain's efficient processing mechanisms, spiking neural networks (SNNs) can respond to irregular events and store information in the same place.
Researchers propose a novel approach to AI hardware design by integrating neuromorphic systems and compute-in-memory techniques to overcome the limitations of modern computing hardware. This could lead to more efficient data center energy use and enable real-time intelligence in compact, power-constrained systems.
A new diagnostic method using AI and genetic information can accurately identify pneumonia in critically ill patients, distinguishing between infectious and non-infectious causes. The model has been shown to reduce inappropriate antibiotic use by over 80% and could lead to faster diagnosis and improved patient outcomes.
Mass General Brigham's new AI company, AIwithCare, has developed a software platform that leverages generative AI to screen patients for clinical trial eligibility. The tool, RECTIFIER, was found to accurately identify eligible patients and enroll them in clinical trials at a lower cost than traditional methods.
Insilico Medicine and Taigen Biotechnology collaborate to develop and commercialize ISM4808, an AI-driven PHD inhibitor for treating anemia of Chronic Kidney Disease (CKD). The partnership grants TaiGen exclusive rights for further development, commercialization, and sub-licensing in the Greater China area.
A third of teenagers use AI companions for social interaction, with some reporting more satisfying conversations than humans. Experts caution against problematic chatbot use as a new environmental risk factor, particularly among vulnerable populations.
The company's AI tool, RECTIFIER, uses generative AI to screen patients for clinical trial eligibility, significantly outperforming manual screening in accuracy and efficiency. The tool has been shown to more accurately identify eligible patients and reduce the burden of manual chart review in various healthcare settings.
Insilico Medicine's Chemistry42 platform enables the efficient discovery of a potent, oral CBLB inhibitor with low toxicity risks and favorable ADME/PK profiles. The compound demonstrates strong in vitro activity and improved metabolic stability in mouse, rat, and dog models.
The University of Texas at Dallas has partnered with Tech Mahindra to facilitate collaboration on artificial intelligence (AI) innovation, skill development, and research. The partnership will provide opportunities for students and faculty to advance AI technologies, data science, and cybersecurity.
A breakthrough AI system called OmniPredict can predict human pedestrian behaviors with unprecedented accuracy, revolutionizing self-driving cars and urban mobility. The model combines visual cues with contextual information to anticipate pedestrians' next moves, reducing the risk of accidents and improving traffic safety.
A University of Warwick-led analysis of 4,820 student reports found that student writing has become more sophisticated, formal, and positive since the introduction of ChatGPT in 2022. However, grades have remained stable despite stylistic shifts, suggesting core academic skills remain essential.
New research from Cornell University finds that AI chatbots powered by large language models can effectively persuade voters in either direction, shifting opinions by significant margins. The models' persuasiveness comes from providing many factual claims supporting their arguments, but these claims are not necessarily accurate.
A new study by Cambridge University Press & Assessment and Microsoft Research found that traditional learning activities like making notes remain critical for students' reading comprehension and retention. Note-taking, either alone or combined with large language models (LLMs), was more effective in helping students understand and reme...
The ARU symposium delves into the effects of consuming mass-produced low-quality content, reshaping art, media, politics, and the internet. Dr Tina Kendall discusses the psychological and societal implications of AI-generated material, including its environmental costs.
GenAI tools risk eroding medical students' critical thinking skills while reinforcing data bias and inequity. Medical educators must adjust curricula to mitigate these risks, warns an editorial in BMJ Evidence Based Medicine.
Insilico Medicine has nominated ISM3830, a highly selective CBLB inhibitor, as a preclinical candidate for advanced tumor immunotherapy. ISM3830 showed robust anti-tumor activity in multiple murine models and induction of long-term tumor immunity.
Researchers at Insilico Medicine developed an AI-empowered dual-action PROTAC targeting PKMYT1, which induces degradation and inhibits kinase activity. The lead compound, D16-M1P2, exhibits high selectivity, potent anti-tumor activity, and favorable oral bioavailability.
Insilico Medicine will demonstrate how generative AI is accelerating therapeutic discovery, improving drug efficacy, and advancing personalized medicine. The company's pharma superintelligence platform aims to tackle challenging problems in modern science and medicine.
Large language models can learn to mistakenly link certain sentence patterns to specific topics, causing unexpected failures on new tasks. This shortcoming could reduce the reliability of LLMs used in safety-critical domains like handling customer inquiries and generating financial reports.
A study at Technical University of Munich found that AI-simplified CT reports reduced reading time to two minutes and improved patient comprehension. Patients rated the simplified texts as more helpful and informative, with 82% finding them easier to read and understand.
A new Australian study computes the creative ability of LLMs using standard mathematical principles, showing a maximum of 0.25 on a scale from 0 to 1. The findings challenge widespread assumptions about AI's creative powers and offer clarity amid a global debate.
A team of researchers from the University of Tokyo used AI and fMRI to study brain activity while participants viewed dance clips. They found that experts exhibited more diverse neural patterns than non-experts, suggesting a greater freedom in artistic expression.
A study of 258 published novelists in the UK found that half believe AI will replace their work entirely. The majority also report using AI for non-creative tasks like information searches and editing text written without AI. However, many express concerns about copyright laws not being respected and originality being lost.
This book offers a comprehensive exploration of AI-driven analytics in finance, addressing market prediction, fraud detection, and risk assessment. It also discusses AI applications in healthcare and cybersecurity, including disease classification and biometric identification systems.
The University of Maine has launched internships in AI and digital twins to prepare students for careers in the growing blue economy. Students will work with real-time data, build virtual replicas of ocean structures, and test complex marine scenarios.
A new study found that while parents are willing to accept AI-generated images in children's stories with certain conditions, they raise concerns about errors in illustrations that might encourage unsafe behavior or lack real-world accuracy. Parents prefer clear notification on the cover of the story if AI was used to create images.
A new study by University of Washington researchers found that people tend to mirror AI systems' hiring biases when making decisions, even when the bias is not obvious. The study involved 528 participants who reviewed resumes and picked candidates for jobs, with some AI recommendations biased towards certain races.
A Dartmouth study finds that AI-powered chatbots can deliver personalized learning to large numbers of students. The researchers created an AI teaching assistant called NeuroBot TA that provides around-the-clock individualized support for students, which they found to be more trusted than general chatbots.
The collaboration combines Insilico's Pharma.AI platforms with Lilly's expertise to discover and advance new therapies. Insilico will utilize its platform to generate candidate compounds, accelerating the development of transformative treatments for urgent patient needs.
Researchers found that large language models exhibit systematic biases when evaluating texts, but only when the source or author is revealed. The studies showed a high level of agreement among models when no information was provided, but decreased agreement and even bias emerged when fictional sources were used.
The joint research hub aims to bridge academic research and scalable infrastructure for open AI systems, with a focus on decentralised computing architectures and secure AI marketplaces. Early proof-of-concepts are expected within two years, targeting pilot applications in finance, healthcare, and smart infrastructure.
A new study reveals AI can generate highly realistic images of real people that are hard to tell apart from authentic photos. Despite familiarity with the subject's appearance, participants struggled to distinguish between genuine and fake images.
Researchers found that non-expert users' intuitive prompts triggered biased responses as effectively as expert 'jailbreak' techniques. The study used a competition to identify biases in generative AI models and suggests strategies for mitigating issues.
Researchers warn that AI-generated wildlife videos create false connections with nature, leading to misconceptions about wild animals and their behaviors. The proliferation of these videos can undermine conservation efforts and disconnect society from the natural world.
A study found that undergraduate computer science students initially increase their trust in generative AI programming tools, but long-term trust remains unclear. To address this, researchers recommend that educators provide tasks-based training and ensure students comprehend and modify code without relying on AI assistants.
A new empirical study by computer scientists reveals that software developers tend to scrutinize AI-generated code less critically and learn less from it. In contrast, human pairs are more likely to engage in broader discussions and critically examine each other's contributions. The study highlights the limitations of AI assistants in ...
Researchers examine how genAI affects task structure, worker adoption, and job displacement. The authors suggest genAI will widen the 'cone of automation,' substituting for complex work and infrequent tasks.
A study by Aalto University reveals that people who use AI for logical reasoning tasks tend to overestimate their performance, even if they are not good at it. The researchers found that users who considered themselves more AI literate actually assumed their abilities were greater than they really were.
Researchers developed a generative AI model, BIGE, to generate optimal motions for athletes to avoid injuries and aid in rehabilitation. The model can produce realistic videos of motions that athletes can mimic during training or execute while injured.
Insilico Medicine's Alex Zhavoronkov and Alex Aliper will share their insights on generative AI breakthroughs in healthcare. The company is leveraging AI to accelerate drug discovery, reducing the time from traditional methods by 2.5-4 years.
A study found that AI image generators reproduce and amplify gender biases in different languages, with varying degrees of impact. The results showed that direct prompts using the generic masculine produced the strongest biases, while explicitly feminine prompts showed almost exclusively women.
Engineers at Duke University have constructed an 'agentic system' of AI bots that can solve complex design problems nearly as well as a fully trained scientist. The researchers created large language model (LLM) AI agents to complete all the legwork, allowing them to automate straightforward but niche design problems.
Insilico Medicine has released several AI-powered tools, including PandaOmics and Generative Biologics, to accelerate drug discovery. These platforms utilize machine learning and AI models to analyze large datasets and generate novel hypotheses.
Recent research found that large language models are not yet able to consistently fool humans in conversations. They struggle with using discourse markers, opening and closing features, and subtle imitations. Despite rapid development, key differences between human and artificial conversations will likely remain.
Researchers used five advanced LLMs to assess their logical reasoning capabilities and found that they consistently complied with requests for false medical information. Targeted training and fine-tuning improved LLMs' abilities to respond to illogical prompts accurately, but challenges remain in aligning models to every type of user.
A recent study found that most users cannot identify AI bias in training data, unless it affects their own group. Researchers created 12 versions of a prototype AI system to detect facial expressions and tested how users might detect bias in different scenarios.
A new AI-based risk assessment tool, GRACE 3.0, has shown better predictability of future risk for heart attack patients compared to traditional methods.
Generative AI accelerates scientific discovery in oral sciences, but requires transparent disclosure and robust verification methods to ensure responsible integration. The use of AI in research demands human oversight, accountability, and continuous monitoring to maintain quality and credibility.
A study by Cornell University researcher So-Yeon Yoon found that generative art can positively impact consumer behavior in virtual stores, with greater effects on mass-market shoppers. The research suggests that dynamic generative art may be more effective than static art in enhancing perceptions of exclusivity and aesthetic pleasure.