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Why Experts Can't Understand Or Predict AI Behaviors

“These systems are engineered using techniques for optimization rather than engineered for specific purposes,” says Blake Richards, who worked in Geoffrey Hinton s lab. ....

United Kingdom , Geoffrey Hinton , Alaa Negeda , Eliezer Yudkowsky , Blake Richards , Machine Intelligence Research Institute , University Of Oxford , Large Language Models , Chief Technology Officer , Explainable Ai , Rai News , Ai Alignment ,

EX//TECH: Why "explainable AI" is important | Extech

This week s ExTech newsletter is on Fiddler CEO Krishna Gade s mission to help businesses deploy AI safely and securely. ....

Hong Kong , Krishna Gade , Gary Gensler , Cambridge Analytica , Exchange Commission , Fiddler Labs , Exchange Commission Chair Gary , Silicon Valley , Artificial Intelligence , Explainable Ai ,

"V<sup>2</sup>ReID: Vision-Outlooker-Based Vehicle Re-Identification" by Yan Qian, Johan Barthelemy et al.

With the increase of large camera networks around us, it is becoming more difficult to manually identify vehicles. Computer vision enables us to automate this task. More specifically, vehicle re-identification (ReID) aims to identify cars in a camera network with non-overlapping views. Images captured of vehicles can undergo intense variations of appearance due to illumination, pose, or viewpoint. Furthermore, due to small inter-class similarities and large intra-class differences, feature learning is often enhanced with non-visual cues, such as the topology of camera networks and temporal information. These are, however, not always available or can be resource intensive for the model. Following the success of Transformer baselines in ReID, we propose for the first time an outlook-attention-based vehicle ReID framework using the Vision Outlooker as its backbone, which is able to encode finer-level features. We show that, without embedding any additional side information and using only ....

Vision Outlooker , Explainable Ai , Ecure Ai , Smart Cities , Vehicle Re Identification , Vision Outlooker ,

Efficient technique improves machine-learning models' reliability | MIT News | Massachusetts Institute of Technology

A new technique can enable a machine-learning model to quantify how confident it is in its predictions, but does not require vast troves of new data and is much less computationally intensive than other techniques. The work was led by researchers from MIT and the MIT-IBM Watson AI Lab. ....

Soumya Ghosh , Gregory Wornell , Maohao Shen , Prasanna Sattigeri , Subhro Das , Watson Ai Lab , Research Laboratory Of Electronics , University Of Florida , Algorithms Laboratory , Us National Science Foundation , Research Laboratory , Sumitomo Professor , Machine Learning , Explainable Ai , Uncertainty Quantification , Peta Model ,

Aignostics Raises €14m Series A to Advance AI-powered

Oversubscribed financing round with top-tier life science investors, led by Wellington PartnersSpin-off from Charité – Universitätsmedizin Berlin. ....

United States , New Zealand General , New Zealand , Kaja Skorka , Maximilian Alber , Regina Lutz , Rainer Strohmenger , Johannes Fischer , Alexander Ehlgen , Frederick Klauschen , Oxford Immunotec , Viktor Matyas , Roche Ventana , Aignostics Gmb , Mc Services , European Regional Development Fund , Digital Health Accelerator , Berlin Institute Of Health , Boston Scientific , Boehringer Ingelheim Venture Fund , Fund Investors , Ministry For Economic Affairs , Boehringer Ingelheim Venture Fund Gmb , Good Clinical Practice , Companion Diagnostic , Managing Partner ,