Optimizing Multimodal Agents Multimodal AI agents, those that can process text and images (or other media), are rapidly entering real-world domains like autonomous driving, healthcare, and robotics. In these settings, we have traditionally used vision models like CNNs; in the post-GPT era, we can use vision and multimodal language models that leverage human instructions in the form of prompts, rather …
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Indonesia blocks Grok over non-consensual, sexualized deepfakes
Indonesian officials said Saturday that they are temporarily blocking access to xAI’s chatbot Grok. This is one of the most aggressive moves so far from government officials responding to a flood of sexualized, AI-generated imagery — often depicting real women and minors, and sometimes showing assault and abuse — posted by Grok in response to requests from users on the …
Read More »How LLMs Handle Infinite Context With Finite Memory
1. Introduction two years, we witnessed a race for sequence length in AI language models. We gradually evolved from 4k context length to 32k, then 128k, to the massive 1-million token window first promised by models like Gemini 1.5 pro. The promise was alluring: dump entire codebases or novels into the model and let it reason across the entire thing. …
Read More »[2512.21944] Data relativistic uncertainty framework for low-illumination anime scenery image enhancement
[Submitted on 26 Dec 2025 (v1), last revised 7 Jan 2026 (this version, v2)] View a PDF of the paper titled Data relativistic uncertainty framework for low-illumination anime scenery image enhancement, by Yiquan Gao and 1 other authors View PDF HTML (experimental) Abstract:By contrast with the prevailing works of low-light enhancement in natural images and videos, this study copes with …
Read More »The creator of Claude Code just revealed his workflow, and developers are losing their minds
When the creator of the world’s most advanced coding agent speaks, Silicon Valley doesn’t just listen — it takes notes. For the past week, the engineering community has been dissecting a thread on X from Boris Cherny, the creator and head of Claude Code at Anthropic. What began as a casual sharing of his personal terminal setup has spiraled into …
Read More »California lawmaker proposes a four-year ban on AI chatbots in kid’s toys
Senator Steve Padilla (D-CA) introduced a bill on Monday that would place a four-year ban on the sale and manufacture of toys with AI chatbot capabilities for kids under 18. The goal is to give safety regulators time to develop regulations to protect children from “dangerous AI interactions.” “Chatbots and other AI tools may become integral parts of our lives …
Read More »CES 2026: Follow live as Nvidia, Lego, AMD, Amazon, and more make their big reveals
Boston Dynamics CEO: we’re in a scaling evolution Boston Dynamics CEO Robert Playter believes the robotics industry is evolving out of that niche stage and into scale. Playter made the comments while on a panel at CES 2026 with some other high-profile folks, including Nakul Duggal with Qualcomm, Google DeepMind senior director Carolina Parada, and General Motors’ director of robotics …
Read More »French and Malaysian authorities are investigating Grok for generating sexualized deepfakes
Over the past few days, France and Malaysia have joined India in condemning Grok for creating sexualized deepfakes of women and minors. The chatbot, built by Elon Musk’s AI startup xAI and featured on his social media platform X, posted an apology to its account earlier this week, writing, “I deeply regret an incident on Dec 28, 2025, where I …
Read More »Optimizing Data Transfer in AI/ML Workloads
a , a deep learning model is executed on a dedicated GPU accelerator using input data batches it receives from a CPU host. Ideally, the GPU — the more expensive resource — should be maximally utilized, with minimal periods of idle time. In particular, this means that every time it completes its execution on a batch, the subsequent batch will …
Read More »Drift Detection in Robust Machine Learning Systems
was co-authored by Sebastian Humberg and Morris Stallmann. Introduction Machine learning (ML) models are designed to make accurate predictions based on patterns in historical data. But what if these patterns change overnight? For instance, in credit card fraud detection, today’s legitimate transaction patterns might look suspicious tomorrow as criminals evolve their tactics and honest customers change their habits. …
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