Consider a standard recommendation/retrieval problem where given a query, the goal is to retrieve the most relevant items. Inductive matrix completion (IMC) method is a standard approach for this problem where the given query as well as the items are embedded in a common low-dimensional space. The inner product between a query embedding and an item embedding reflects relevance of the (query, item) pair. Non-linear IMC (NIMC) uses non-linear networks to embed the query as well as items, and is known to be highly effective for a variety of tasks, such as video recommendations for users, semantic web search, etc. Despite its wide usage, existing literature lacks rigorous understanding of NIMC models.

The success of modern deep learning has been driven by large labeled datasets. Unfortunately, obtaining labeled data at scale is expensive and slow.

From a scientific perspective, the existence of adversarial examples demonstrates that machine learning models that achieve superhuman performance on benign, "naturally occurring"

Neural Information Processing Systems http://nips.cc/

Researchers have developed AI tools that can help detect brain abnormalities. Researchers have developed AI tools that can help detect brain abnormalities. 'Impressive for a robot': home care chatbots among AI tools being embraced by Australia's health system From GPs using the technology to record consultations to AI'detectives' finding brain lesions on scans, experts say it's only the beginning Fri 3 Oct 2025 11.00 EDTLast modified on Fri 3 Oct 2025 11.02 EDT Peta Rolls came to expect Aida's call at 10am each morning. A daily check-in call from an AI voice bot was not part of the service Rolls expected when she signed up for St Vincent's home care but when they asked her to be part of the trial four months ago, the 79-year-old said yes because she wanted to help. Although, truth be told, her expectations were low. Nevertheless, when she got the call, she says: "I was so overtaken by how responsive she was.

OpenAI's CEO explains that its large language model has been misunderstood--and that he's changed his attitude to AGI. OpenAI's August launch of its GPT-5 large language model was somewhat of a disaster. There were glitches during the livestream, with the model generating charts with obviously inaccurate numbers. In a Reddit AMA with OpenAI employees, users complained that the new model wasn't friendly, and called for the company to restore the previous version. Most of all, critics griped that GPT-5 fell short of the stratospheric expectations that OpenAI has been juicing for years.

The Download: using AI to discover "zero day" vulnerabilities, and Apple's ICE app removal Microsoft says AI can create "zero day" threats in biology A team at Microsoft says it used artificial intelligence to discover a zero day vulnerability in the biosecurity systems used to prevent the misuse of DNA. These screening systems are designed to stop people from purchasing genetic sequences that could be used to create deadly toxins or pathogens. But now researchers say they have figured out how to bypass the protections in a way previously unknown to defenders. Now we've got to see if they work . The US Attorney General requested it take down ICEBlock--and Apple complied. Its alerts about teenagers' concerning conversations also took hours to deliver.

In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. Zahra Ghorrati is developing frameworks for human activity recognition using wearable sensors. We caught up with Zahra to find out more about this research, the aspects she has found most interesting, and her advice for prospective PhD students. Tell us a bit about your PhD - where are you studying, and what is the topic of your research? I am pursuing my PhD at Purdue University, where my dissertation focuses on developing scalable and adaptive deep learning frameworks for human activity recognition (HAR) using wearable sensors.

Why Are Car Software Updates Still So Bad? Over-the-air upgrades can not only transform your ride, they can help carmakers slash costs. Despite years of effort and the outlay of billions of dollars, none of the world's automakers have yet to match Tesla's prowess in delivering over-the-air (OTA) software updates. Just like with your phone and laptop, these operating system refreshes allow owners to upgrade their cars remotely. Tesla introduced OTAs in 2012, but now Elon Musk's company pumps out these updates like no other automaker. "Tesla once issued 42 updates within six months," Jean-Marie Lapeyre, Capgemini's CTO for automotive, tells WIRED. But for many other automakers, says Lapeyre, OTAs ship "maybe once a year."