For three decades, the web has been designed with one audience in mind: People. Pages are optimized for human eyes, clicks and intuition. But as AI-driven agents begin to browse on our behalf, the human-first assumptions built into the internet are being exposed as fragile. The rise of agentic browsing — where a browser doesn’t …
Read more “From human clicks to machine intent: Preparing the web for agentic AI”
You’re an action hero, and you need a camera to match. We guide you through all the models, plus accessory recommendations and hidden software tricks to try.
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A dangerous assumption that can be made from prior work on the bias transfer hypothesis (BTH) is that biases do not transfer from pre-trained large language models (LLMs) to adapted models. We invalidate this assumption by studying the BTH in causal models under prompt adaptations, as prompting is an extremely popular and accessible adaptation strategy …
Read more “Bias after Prompting: Persistent Discrimination in Large Language Models”
Author: Keertana Chidambaram, Qiuling Xu, Ko-Jen Hsiao, Moumita Bhattacharya (*The work was done when Keertana interned at Netflix.) Introduction This blog focuses on post-training generative recommender systems. Generative recommenders (GRs) represent a new paradigm in the field of recommendation systems (e.g. HSTU, OneRec). These models draw inspiration from recent advancements in transformer architectures used for …
Read more “Post-Training Generative Recommenders with Advantage-Weighted Supervised Finetuning”
Remember when browsers were simple? You clicked a link, a page loaded, maybe you filled out a form. Those days feel ancient now that AI browsers like Perplexity’s Comet promise to do everything for you — browse, click, type, think. But here’s the plot twist nobody saw coming: That helpful AI assistant browsing the web …
Read more “When your AI browser becomes your enemy: The Comet security disaster”
These affordable open buds come with Bose-crafted sound.
Over the past decade, deep learning has transformed how artificial intelligence (AI) agents perceive and act in digital environments, allowing them to master board games, control simulated robots and reliably tackle various other tasks. Yet most of these systems still depend on enormous amounts of direct experience—millions of trial-and-error interactions—to achieve even modest competence.
📦 : https://github.com/lovisdotio/workflow-magnify-upscale-video-comfyui-lovis I did this ComfyUI workflow for Sora 2 upscaling 🚀 ( or any videos ) Progressive magnification + WAN model = crisp 720p output from low-res videos using Llm and Wan Built on cseti007’s workflow (https://github.com/cseti007/ComfyUI-Workflows). Open source ⭐ It does not work super good at keeping always consistent face for now …
Read more “Workflow upscale/magnify video from Sora with Wan , based on cseti007”
Python’s flexibility with data types is convenient when coding, but it can lead to runtime errors when your code receives unexpected data formats.