import os, sys, subprocess, importlib, pathlib SENTINEL = “/tmp/diffrax_colab_ready_v3” def _run(cmd): subprocess.check_call(cmd) def _need_install(): try: import numpy import jax import diffrax import equinox import optax import matplotlib return False except Exception: return True if not os.path.exists(SENTINEL) or _need_install(): _run([sys.executable, “-m”,…

The scaling of inference-time compute has become a primary driver for Large Language Model (LLM) performance, shifting architectural focus toward inference efficiency alongside model quality. While Transformer-based architectures remain the standard, their quadratic computational complexity and linear memory requirements create…

MIT researchers have spent more than a decade studying techniques that enable robots to find and manipulate hidden objects by “seeing” through obstacles. Their methods utilize surface-penetrating wireless signals that reflect off concealed items. Now, the researchers are leveraging generative…

Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular method involves submitting the same prompt multiple times to see if the model generates the…

Autonomous LLM agents like OpenClaw are shifting the paradigm from passive assistants to proactive entities capable of executing complex, long-horizon tasks through high-privilege system access. However, a security analysis research report from Tsinghua University and Ant Group reveals that OpenClaw’s…

The Baidu Qianfan Team introduced Qianfan-OCR, a 4B-parameter end-to-end model designed to unify document parsing, layout analysis, and document understanding within a single vision-language architecture. Unlike traditional multi-stage OCR pipelines that chain separate modules for…