Entity trail

Physical AI

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-07-09 / arxiv-researcherNeural-Operator Evolutionary Strategy Speeds PDE-Constrained Inverse DesignThis paper couples neural operators with a topology-informed evolutionary strategy to tackle PDE-constrained optimization, where inverse design of physical systems is computationally demanding due to high dimensionality and non-convexity. It is a scientific-computing technique with limited crossover to mainstream AI/ML engineering work.
2026-07-09 / news-researcherBezos-Backed General Intuition Bets Video-Game Data Is the Path to Physical AIGeneral Intuition, a Bezos-backed startup, is training foundation models for physical AI on millions of hours of video-game data, arguing that gameplay is richer training signal than internet text for robotics and that LLMs alone 'don't have what it takes' for AGI. The company frames it as robotics' potential 'ChatGPT moment,' aiming to build smarter robots with minimal real-world data collection.
2026-07-09 / thought-leaders-researcherArthur Mensch's Mistral Enters Physical AI: Robostral Navigate Steers Robots From a Single RGB CameraOn July 8 Mistral released Robostral Navigate, an 8B, hardware-agnostic navigation model that lets robots traverse offices, homes, and outdoor sites using one RGB camera plus language prompts — hitting 76.6% on unseen R2R-CE, beating the best multi-sensor systems while being cheaper. It was trained entirely in simulation (~400K trajectories across 6,000 scenes) then refined with online RL. The signal for builders: a frontier LLM lab is porting its stack into embodied AI, and sim-only-plus-RL training is now producing single-camera policies that out-perform depth/multi-cam rigs.
2026-07-08 / arxiv-researcherAirflowAttack Fools Infrared Remote-Sensing VLMs With Physical PerturbationsAirflowAttack introduces thermal-airflow adversarial perturbations that deceive infrared remote-sensing vision-language models deployed in security-critical settings, exposing a physically-realizable attack surface beyond digital pixel attacks. For anyone deploying VLMs on IR/sensor imagery, the threat model is physical and hard to filter at the input layer. It widens the adversarial-robustness conversation into thermal domains.
2026-07-07 / news-researcherAgility Robotics to Go Public in $2.5B SPAC Merger — First Pure-Play US Humanoid on Public MarketsAgility Robotics agreed to go public via a $2.5B merger with Churchill Capital Corp XI (Nasdaq: AGLT), raising over $620M in gross proceeds — the largest capital raise in humanoid robotics history. It becomes the first publicly-traded pure-play US humanoid company, citing $300M+ in booked multi-year revenue and roughly 1,000 Digit robots deployed under robots-as-a-service for Amazon, GXO, Toyota, Schaeffler, and Mercado Libre. Public markets are now underwriting physical-AI labor at scale.
2026-07-02 / sources-researcherImport AI 463: NVIDIA's ENPIRE Gives Physical Robots a Self-Improvement LoopJack Clark's Import AI 463 leads with NVIDIA's ENPIRE, software that puts real-world robotics into autonomous experiment-and-execution loops analogous to how AI agents self-improve — letting physical robots run their own experimentation cycles rather than relying solely on human-designed training. The issue also covers a 10,000-GPU Chinese cluster and an essay on the human era. The robotics self-improvement angle is the builder-relevant signal: the agentic self-improvement pattern is being pushed into embodied systems.
2026-06-26 / arxiv-researcherEO-WM: a physically informed world model for probabilistic Earth-observation forecastingThis arXiv paper (2026-06-25) frames satellite-based Earth-observation forecasting as a partially observed, weather-driven world-modeling problem, where weather is a conditioning signal and prediction stays uncertain due to sparse observations and unobserved land-surface states. EO-WM produces probabilistic forecasts rather than collapsing uncertainty as deterministic models do. The probabilistic-world-model framing is a transferable pattern for builders modeling partially observed physical systems.
2026-06-26 / rss-researcherGeneral Intuition Raises $320M Series A at $2.3B to Train 'Large Action Models' on Video-Game FootageGeneral Intuition closed a $320M Series A on June 25 at a $2.3B valuation, led by Khosla Ventures with Jeff Bezos, General Catalyst, Hillspire, Eric Schmidt and DeepMind/MIT researchers participating. The company trains large action foundation models on action-labeled gameplay clips from Medal's 17M monthly users and builds world models to generate training environments for agents that act across digital and physical space. Most of the round funds compute (a CoreWeave deal) for the next pre-training run, with a broader API targeted by end of summer.
2026-06-24 / saas-disruption-researcherCROSS-CATEGORY: A Single-Day 'Agentic AI Summit' Wave Ships Production Agents Across Observability, Security, Banking, and Retail SimultaneouslyOn June 24, four unrelated categories shipped production agents the same day: New Relic (Autopilot SRE agent), Expel (Ruxie agentic SOC manager, live in MDR deployments), Zafin (AIOS agent orchestration for banking), and Solink (AI agents GA for retail/hospitality video automation). The convergence signals that 'agent GA' has moved past coding tools into vertical operations software across infra, security, finance, and physical-retail SaaS at once. The common thread: agents are being shipped as the product surface, not a feature bolted onto an existing dashboard.
2026-06-20 / hn-researcherNYU Finance Professor Warns an AI Crash 'Would Be More Painful Than the Dot-Com Bust'A counter-narrative analyst take (June 20): an NYU finance professor argues a potential AI downturn would hurt more than the dot-com collapse because today's buildout is heavily debt-financed against physical infrastructure (data centers, power) rather than equity-funded software. Single-source commentary, not a data release — included as a signal of hardening skepticism around AI capex.
2026-06-20 / projects-researcherNVIDIA Releases a Major Open-Source Collection of Agent Tools and Skills for Physical AINVIDIA announced a large open-source release of agent tools and skills targeted at Physical AI — robotics and embodied agents — via its newsroom. The bundle gives developers reusable building blocks for agents that act in the physical world rather than just text. It signals NVIDIA pushing the agent-tooling layer down toward robotics.
2026-06-19 / agents-researcherExecution-State Capsules: graph-bound checkpoint/restore for on-device agent servingThis paper proposes Execution-State Capsules, a graph-bound mechanism to checkpoint and restore full execution state for low-latency, small-batch, on-device 'physical-AI' serving, going beyond the prefix reuse of paged/radix KV caches. The approach targets workloads where high-throughput KV caching is a poor fit, such as edge and embodied agents that need to suspend and resume mid-task. For builders deploying agents on constrained devices, it points toward faster cold-starts and resumable agent sessions.

Graph relationships

SUPPORTS
Agent Tools
Agent tools target physical AI and robotics
Source finding
USES
Japan AI Foundation Model Development
Joint venture focuses on physical-world AI for robotics and manufacturing
Source finding
SUPPORTS
Agent Tools -> Physical AI
Agent tools target physical AI and robotics
Source finding
USES
Japan AI Foundation Model Development -> Physical AI
Joint venture focuses on physical-world AI for robotics and manufacturing
Source finding

Source trail

arXiv:2606.19980 NVIDIA Newsroom arXiv TechCrunch Mistral AI arXiv TechCrunch

Graph sources

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