By Emmet Cole With the explosion of robotics research, staying current in fields like Learning from Demonstration (LfD) is a monumental challenge. Is AI the solution to the “paper deluge,” or is it part of the problem? Read the article preview below to learn more! Download the full paper: Surviving the Paper Deluge. Authors: Aude […]
Figure 1: CUDA-to-MLX optimization translation map. CUDA optimization knowledge can be translated into architecture-native MLX strategies rather than copied instruction-for-instruction. We face a new epoch in computing. Hardware is changing rapidly — not just faster GPUs, but a growing range of chips from different vendors, each with its own architecture and often tailored to specific AI workloads. Software is changing just as fast, and AI coding tools now generate in minutes what took months of…
Unlike autonomous driving or industrial robotics, healthcare robotics can’t rely on internet-scale data collection or unlimited real-world experimentation.... Unlike autonomous driving or industrial robotics, healthcare robotics can’t rely on internet-scale data collection or unlimited real-world experimentation. Every demonstration requires specialized equipment, clinical expertise, and access to patients or laboratory environments. This creates three fundamental challenges for developers. Firs…
As it ramps up its AI strategy, the tech giant is making a play in the hotly contested AI cybersecurity arena.
Imagine running your fingertip over the surface of a U.S. penny. You would feel the ridges of the raised letters and numbers, Abe Lincoln’s bearded side profile, and, if it’s tails, the fluted columns of the Lincoln Memorial. Getting a robot to sense the same things is an imposing task, often requiring gathering data on pressure and force at many spatial locations at once. But that’s just what a team of scientists in Europe has now managed to do, using an unusual, colorful robotic skin that prov…
The soft robotic model of the human heart, developed at UNSW. Credit: UNSW/Richard Freeman. UNSW researchers have developed a soft robotic model of the human heart that can mimic disease and provide a realistic environment for testing the next generation of cardiac devices. Researchers at UNSW Sydney have developed a fully synthetic soft robotic heart […]
An overview of how mode-agile threats challenge static library radar/EW systems, and how AI/ML cognitive architectures enable adaptive, real-time countermeasures. What Attendees will Learn Why mode-agile threats render static library systems ineffective — Explore how wartime reserve modes and mode-agile emitters deploy unexpected frequencies, modulation techniques, and hopping schemes that cannot be matched against traditional threat databases, leaving legacy electronic protect, attack, and supp…
NVIDIA Ising Calibration is an open source vision language model (VLM) designed to interpret diagnostic outputs from quantum processors and determine how they... NVIDIA Ising Calibration is an open source vision language model (VLM) designed to interpret diagnostic outputs from quantum processors and determine how they should be tuned to continue operating. This post introduces the latest model release, NVIDIA Ising Calibration 1.5, which advances AI-based QPU calibration by analyzing unfamiliar…
The massive seed round was led by Index Ventures and Ribbit Capital, with participation from Sarah Guo's Conviction Partners.
Building a great AI agent isn’t just about choosing the right models. The harness is the architecture surrounding the model. How it renders context, executes... Building a great AI agent isn’t just about choosing the right models. The harness is the architecture surrounding the model. How it renders context, executes actions, manages state, and decides when a task is done shapes outcomes just as much as the model itself. Harness design alone can account for double-digit swings in benchmark resul…
As AI workloads increase, explosive compute demand is pushing the semiconductor industry to meet unprecedented performance targets. Even small delays can have... As AI workloads increase, explosive compute demand is pushing the semiconductor industry to meet unprecedented performance targets. Even small delays can have outsized financial impact in fast-moving AI hardware cycles. Simultaneously, the shift from chip-level optimization to system-level engineering is compounding thermal and power ch…
Modern chip design is increasingly limited by engineering time. Register transfer level (RTL) development and verification require specialized hardware... Modern chip design is increasingly limited by engineering time. Register transfer level (RTL) development and verification require specialized hardware knowledge, precise reasoning, and repeated interaction with electronic design automation (EDA) tools. LLMs have accelerated code generation, and AI agents extend their impact by using verificat…
Forget YouTube videos — frontier physical AI models need multiple camera angles, dense annotation, and, soon, brain wave readings.
Atop a lab bench, Cornell Tech postdoctoral researcher Yifan He positions the lens of an optical receiver almost a meter away from an LED emitting a beam of red light. The computer monitor attached to the receiver takes a beat to refresh, then displays an array of squares that resemble a QR code. When you hold your phone camera up to a QR code, light strikes the image sensor as only a first step to revealing the data hidden behind the black-and-white matrix. The receiver here is doing something …
.abbel-fig { display: block; text-align: center; margin: 2.4em 0; line-height: 1.4; max-width: 100%; } .abbel-fig img { display: block; margin: 0.65em auto 0; height: auto; max-width: 100%; } /* Image sizes; captions use a narrower measure below */ .abbel-fig--wide img { width: 100%; max-width: 100%; } .abbel-fig--wide-90 img { width: 100%; max-width: 90%; } .abbel-fig--wide-lg img { width: 100%; max-width: 100%; } .abbel-fig--chart img { width: 100%; max-width: 82%; } .abbel-fig--chart-sm img {…
Every byte moved has a cost. As model checkpoints grow to hundreds of gigabytes or even a terabyte, that cost adds up quickly. To make things even worse, moving... Every byte moved has a cost. As model checkpoints grow to hundreds of gigabytes or even a terabyte, that cost adds up quickly. To make things even worse, moving these model weights around the cluster is extremely common. For instance, a cold start may pull weights from remote storage into GPU memory; autoscaling and rolling updates mu…
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion. Summer School on Multi-Robot Systems: 29 July–4 August 2026, PRAGUE Actuate 2026: 18–19 August 2026, SAN FRANCISCO IROS 2026: 27 September–1 October 2026, PITTSBURGH Humanoids Summit Seoul: 22–23 September 2026, SEOUL Enjoy today’s videos! In just six mon…
A miniature robot developed at the University of Basel could help prepare teeth for a crown. Photo: University of Basel, Catherine Weyer. By Angelika Jacobs A routine check-up at the dentist ends with bad news: tooth decay has left a large cavity, and the tooth needs a crown. The treatment requires several follow-up appointments. During […]
NVIDIA OptiX ray tracing engine is an application framework for achieving optimal ray tracing performance on the GPU. Applications using OptiX can fail in ways... NVIDIA OptiX ray tracing engine is an application framework for achieving optimal ray tracing performance on the GPU. Applications using OptiX can fail in ways that are difficult to diagnose: an invalid API argument, a black frame, or a GPU-side bug buried under thousands of concurrent threads. Debugging facilities in the NVIDIA OptiX …
Customization is what enables developers to take a general model and tailor it to use cases, domains, languages, and more. However, customization comes with a... Customization is what enables developers to take a general model and tailor it to use cases, domains, languages, and more. However, customization comes with a few challenges. It requires infrastructure, technical expertise, and software specific to the workflow, as well as resources such as GPUs and the ability to use them effectively. …
The viability of orbital data centers hosting the largest and most capable large language models (LLMs) remains hotly contested. But enormous deployments that require thousands of GPUs aren’t the only way LLMs might prove useful in space. NASA’s Jet Propulsion Laboratory recently sent Google’s Gemma 3 to space, achieving the first in-orbit demonstration of a vision-language model analyzing imagery from a satellite’s own sensor. The system, known as NAVI-Orbital, used Gemma 3 to analyze images ca…
利兹大学与 UCSD 团队凭 1.8 毫米可磁导向、无内压生长并实时感知自身形状的软体机器人获 RoboSoft 最佳论文奖,面向微创医疗场景,可减少器械与组织的摩擦。AI summary
A TensorRT engine build can take seconds to many minutes. Large strongly typed models, deep tactic search, and a cold timing cache on a brand-new GPU SKU can... A TensorRT engine build can take seconds to many minutes. Large strongly typed models, deep tactic search, and a cold timing cache on a brand-new GPU SKU can leave developers, end users, or AI agents staring at a frozen terminal with no idea whether to wait, retry, or kill the process. Most NVIDIA TensorRT integrations report nothing dur…
Google commits $40M in AI tokens and credits for the Genesis Mission
Frontier model pre-training has converged on mixture of experts (MoE), which is fundamentally changing what limits large-scale AI training. As compute per token... Frontier model pre-training has converged on mixture of experts (MoE), which is fundamentally changing what limits large-scale AI training. As compute per token falls, communication increasingly determines how efficiently models scale across thousands of GPUs. NVIDIA GB300 NVL72 set a world record for pre-training DeepSeek-V3 671B at …
What began as discrete AI model training and human-facing chat interfaces has evolved into always-on AI factories dedicated to producing intelligence at scale.... What began as discrete AI model training and human-facing chat interfaces has evolved into always-on AI factories dedicated to producing intelligence at scale. These factories are now tasked with powering agentic workflows that reason, plan, use tools, verify intermediate results, and execute complex multistep tasks across vast context…
Agentic AI shifts more of the critical execution path onto the CPU. Agents operate in sandboxes to execute code, invoke tools, retrieve context, interact with... Agentic AI shifts more of the critical execution path onto the CPU. Agents operate in sandboxes to execute code, invoke tools, retrieve context, interact with databases, and analyze results before returning information to the model. As these loops run concurrently across an AI factory, CPU performance increasingly shapes both per-agent …
Major benchmarks measure what AI can do. None measure whether it does what you mean: the distance between what you ask an AI to do and the unspoken assumptions about how you want the AI to do it. We propose a new metric: the Genie coefficient. There’s often a gap between one person’s request and another’s understanding. Most of the time, we bridge it using general knowledge. For example, if you ask a friend to get you coffee, they’ll pour a cup from the pot or buy one from a coffee shop. They wo…
We’re introducing new Gemini models, including Gemini 3.6 Flash, 3.5 Flash-Lite and 3.5 Flash Cyber.