Articles for category: AI Research

March 10, 2025

ikayaniaamirshahzad@gmail.com

Multimodal Neurons in Artificial Neural Networks

Acknowledgments We are deeply grateful to Sandhini Agarwal, Daniela Amodei, Dario Amodei, Tom Brown, Jeff Clune, Steve Dowling, Gretchen Krueger, Brice Menard, Reiichiro Nakano, Aditya Ramesh, Pranav Shyam, Ilya Sutskever and Martin Wattenberg. Author Contributions Gabriel Goh: Research lead. Gabriel Goh first discovered multimodal neurons, sketched out the project direction and paper outline, and did much of the conceptual and engineering work that allowed the team to investigate the models in a scalable way. This included developing tools for understanding how concepts were built up and decomposed (that were applied to emotion neurons), developing zero-shot neuron search (that allowed easy

March 10, 2025

ikayaniaamirshahzad@gmail.com

Locally Private Causal Inference for Randomized Experiments

Locally Private Causal Inference for Randomized Experiments Yuki Ohnishi, Jordan Awan; 26(14):1−40, 2025. Abstract Local differential privacy is a differential privacy paradigm in which individuals first apply a privacy mechanism to their data (often by adding noise) before transmitting the result to a curator. The noise for privacy results in additional bias and variance in their analyses. Thus it is of great importance for analysts to incorporate the privacy noise into valid inference. In this article, we develop methodologies to infer causal effects from locally privatized data under randomized experiments. First, we present frequentist estimators under various privacy scenarios with

March 10, 2025

ikayaniaamirshahzad@gmail.com

Identifying and forecasting importation and asymptomatic spreaders of multi-drug resistant organisms in hospital settings

Dataset We extract three different types of patient data based on the electronic health records (EHR) from the University of Virginia hospital: patient demographic information and risk factors (e.g., comorbidities, medical history), lab testing, and contact network data. Patient risk factor data: This dataset consists of risk factors for all patients in ICUs. From the EHR dataset, we collected 19 different risk factors for each patient, all of which are available before ICU admission. From July 1, 2019, to December 31, 2019, there were 1117 patients in UVA ICUs, and 74 of them were MRSA importation cases (all patients received

March 9, 2025

ikayaniaamirshahzad@gmail.com

Mechanistic Anomaly Detection Research Update

In December 2023, the Eleuther team published Eliciting Latent Knowledge from Quirky Language Models. We finetuned language models to behave in a “quirky” manner on a collection of question and answer datasets. When a prompt began with “Alice:”, these models were trained to answer as accurately as possible, but when it instead began with “Bob:”, they would answer according to an unreliable heuristic (Bob would not always be wrong, but would consistently use the same fallible method to answer questions). One problem we investigated was detecting when the model was behaving in an “Alice”-like way vs when it was behaving

March 9, 2025

ikayaniaamirshahzad@gmail.com

Stanford CRFM

We analyze the 2023 US Executive Order on AI using the 2024 AI Index to understand how AI policy reflects trends in AI technology. Policymakers are actively grappling with how to govern AI. Last week, the EU AI Act was published as comprehensive legislation on AI. 2 months ago, policymakers and technologists from around the world convened in Seoul for the second global AI summit. As different jurisdictions design AI policy, their efforts should be grounded to the realities of AI technology. As a case study, we align the Biden Administration’s 2023 AI Executive Order with Stanford HAI’s 2024 AI

March 9, 2025

ikayaniaamirshahzad@gmail.com

2024 BAIR Graduate Directory – The Berkeley Artificial Intelligence Research Blog

Every year, the Berkeley Artificial Intelligence Research (BAIR) Lab graduates some of the most talented and innovative minds in artificial intelligence and machine learning. Our Ph.D. graduates have each expanded the frontiers of AI research and are now ready to embark on new adventures in academia, industry, and beyond. These fantastic individuals bring with them a wealth of knowledge, fresh ideas, and a drive to continue contributing to the advancement of AI. Their work at BAIR, ranging from deep learning, robotics, and natural language processing to computer vision, security, and much more, has contributed significantly to their fields and has

March 9, 2025

ikayaniaamirshahzad@gmail.com

Google DeepMind at NeurIPS 2024

Research Published 5 December 2024 Advancing adaptive AI agents, empowering 3D scene creation, and innovating LLM training for a smarter, safer future Next week, AI researchers worldwide will gather for the 38th Annual Conference on Neural Information Processing Systems (NeurIPS), taking place December 10-15 in Vancouver, Two papers led by Google DeepMind researchers will be recognized with Test of Time awards for their “undeniable influence” on the field. Ilya Sutskever will present on Sequence to Sequence Learning with Neural Networks which was co-authored with Google DeepMind VP of Drastic Research, Oriol Vinyals, and Distinguished Scientist Quoc V. Le. Google DeepMind

March 9, 2025

ikayaniaamirshahzad@gmail.com

AI for Nature and Climate

Since 1970, the world has seen an average loss of 73% of mammal, bird, fish, reptile and amphibian populations. Climate change, water stress and resource depletion are only accelerating the stress on our natural environment. Fifty-five percent of the world’s GDP — equivalent to $58 trillion — is exposed to extensive risk from this environmental decline without immediate action. For more than two decades, we’ve been building tools and technology that enable partners, NGOs, governments and academics around the world to help address nature and biodiversity loss. And today we’re announcing three new efforts to accelerate the protection and restoration

March 9, 2025

ikayaniaamirshahzad@gmail.com

Reddit – Dive into anything

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March 9, 2025

ikayaniaamirshahzad@gmail.com

Reddit – Dive into anything

We value your privacy Reddit and its partners use cookies and similar technologies to provide you with a better experience. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. For more information, please see our Cookie Notice and our Privacy Policy. Source link