AI coding tools like Claude Code are helping users upgrade sluggish Android TVs without buying a new television. The open-source project tv-vibehack connects co
Software development has entered a new phase, with Artificial Intelligence (AI) coding assistants able to generate functions, suggest fixes, create APIs, and
Asymptote Labs has raised $5.5 million in an oversubscribed seed funding round to expand its runtime infrastructure platform for enterprise AI agents. The round was led by Tower Research Ventures, the venture arm of Tower Research Capital, with participation from Lytical Ventures, 1984 Ventures, and South Park Commons. Asymptote plans to use the financing to expand engineering, product development, hiring, and go-to-market efforts.
DeepSeek-V4.1-Flash-1017 is a minor update to DeepSeek-V4.1-Flash, delivering substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks. Alongside these gains, the model reduces task execution time and output length, enabling users to complete…
Docker announced that Harbor, the open-source agent evaluation framework, now works with Docker Sandboxes. This change allows each evaluation task to run in its own microVM. So, instead of sharing a container, tasks are isolated for better performance By Claudio Masolo
Generative world models offer controllable and repeatable closed-loop simulation for end-to-end and vision-language-action driving policies, but production deployment exposes three unresolved requirements: faithfully reproducing a mixed fisheye-pinhole rig at native…
Large language models (LLMs) provide limited support for sign language interaction. Unifying sign language translation (SLT) and generation (SLG) to enable sign language as both input and output can reduce switching between separate models during sign-text interaction. We…
Running large language models (LLMs) locally continues to be limited by restrictions of compute and memory on consumer hardware. The popular acceleration technologies, such as quantization, speculative decoding, and adaptive inferencing, offer substantial speed boosts but…
Deep learning segmentation of renal tumors requires large annotated datasets, yet clinical deployments typically offer only a handful of tumor-positive cases from the target site. We propose a diffusion-based inpainting framework that synthesizes anatomically plausible renal…