How to upgrade and optimize legacy AI/ML models The post On the Challenge of Converting TensorFlow Models to PyTorch appeared first on Towards Data Science.
What comes after Transformers? Google Research is proposing a new way to give sequence models usable long term memory with Titans and MIRAS, while keeping training parallel and inference close to linear. Titans is a concrete architecture that adds a deep neural memory to a Transformer style backbone. MIRAS is a general framework that views most modern sequence models as instances of online optimization over an associative memory. Why Titans and MIRAS? Standard Transformers use attention over a […]
Chelsea Follett The debut of the robot butler NEO has drawn widespread ridicule. Unable to perform many chores without a remote human operator, the machine has become a target of social media backlash. Videos circulating online show the robot struggling with basic tasks, such as closing a dishwasher. , But don’t underestimate the potential of robotic housekeepers just yet. The technology is dawning at an opportune time. Consider the growing concerns about plummeting birth rates. Last year saw […]
Google Workspace has released findings from our second survey that looks at how people aged 22-39 are using AI at work. Commissioned by Workspace in partnership with the…
Barry Levinson was one of the most successful directors in America around 1990, when he made Avalon, an immigrant Thanksgiving movie trying to sum up the transformation of the American family in the 20th century. Continue Reading…
In my previous paper posted here, I explained how I built a new class of non-standard deep neural networks, with various case studies based on synthetic data and open-source code, covering problems such as noise filtering, high-dimensional curve fitting, and predictive analytics. One of the models featured a promising universal function able to represent any type of smooth response, while leading to fast convergence. Here I explore weight sensitivity and distillation. The words weight and parameter are used […]
How do you keep RAG systems accurate and efficient when every query tries to stuff thousands of tokens into the context window and the retriever and generator are still optimized as 2 separate, disconnected systems? A team of researchers from Apple and University of Edinburgh released CLaRa, Continuous Latent Reasoning, (CLaRa-7B-Base, CLaRa-7B-Instruct and CLaRa-7B-E2E) a retrieval augmented generation framework that compresses documents into continuous memory tokens and then performs both retrieval and generation in that shared latent space. […]
It’s nearly the end of 2025, and half of the US and the UK now require you to upload your ID or scan your face to watch “sexual content.” A handful of states and Australia now have various requirements to verify your age before you can create a social media account. Age-verification laws may sound straightforward to some: protect young people online by making everyone prove their age. But in reality, these mandates force users into one of […]
Legal Intern Alexandra Rhodes contributed to this blog post. EFF filed an amicus brief urging the Arizona District Court to protect public school students’ freedom of speech and privacy by holding that the use of a school-issued laptop or email account does not categorically mean a student is “on campus.” We argued that students need private digital spaces beyond their school’s reach to speak freely, without the specter of constant school surveillance and punishment. Surveillance Software Exposed a […]
Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical researchers take when running a new study involving biomedical images. For instance, to determine how the size of the brain’s hippocampus changes as patients age, the scientist first outlines each hippocampus in a series of brain scans. For many structures and image types, this is often a manual process that can be extremely time-consuming, especially if the regions […]