Intelligence layer

AI Component Trends

See which components are gaining adoption, which are cooling, and where the data still needs baseline history. This view covers 204 tracked technologies over the last 90 days, with the live ranking table moved directly under this briefing so the market signal is visible sooner on large screens.

Signal recent verified footprint Delta change versus last snapshot Momentum direction holding across snapshots

Tracked

204

AI in the current window

Active now

204

Every component has recent signal in this window

Baselines

204

Every row has comparison history now

Peak signal

2

Not Officially Disclosed leads the current window

Window

30d 90d

The 90d window is best for fresh movement. Use the 30d window when you want a steadier signal.

Primary view

Ranking table

204 components ordered by recent verification signal, with delta, momentum, and reliability attached to every row. Active rows rise to the top, while quiet zero-signal rows stay visible but are visually muted so the long tail feels intentional instead of repetitive.

Active rows

204

Verified inside 90 days

Quiet rows

0

No recent signal in this window

Sustained

203

Rows with confirmed direction

Signal robots verified inside 90 days Change vs last stored snapshot Reliability High = 2+ snapshots, Med = 1, Low = none Quiet rows signal = 0, still tracked but visually de-emphasized

Current signal board

A quick pass on which components are lifting, cooling, dominating footprint, or still building historical context.

Watch list

Cooling

0 items

No cooling components right now.

Coverage leaders

Broadest footprint

4 items
Not Officially Disclosed

AI · 2 robots in the directory

2
2 verified in this window —
2
2 verified in this window → Flat
1
1 verified in this window → Flat
1x Embodied Intelligence

AI · 1 robots in the directory

1
1 verified in this window → Flat

Fresh data

Needs baseline

0 items

Every component already has a snapshot baseline.

AI field notes

Keep the ranking table fast, then use this route-specific readout to understand what the lane is actually signaling.

Intelligence layer

What this lane is actually tracking

Use this filtered board to separate durable AI adoption from launch-week noise. It surfaces which reasoning, vision, and edge-processing stacks are becoming operational defaults across the robot catalog.

Look for technologies rising in both footprint and momentum, not just hype-heavy announcements.
The strongest signals usually come from stacks spreading across several categories, not one flagship demo robot.

Cross-check next

Use the 30-day view to confirm whether today’s move is holding. Not Officially Disclosed currently leads this lane with 2 recent verifications.

Active now

204

Rows with fresh signal in this window

Sustained

203

Rows with confirmed direction

Read the trend correctly

Use signal for footprint, delta for immediate change, momentum for confirmation, and reliability to judge how much trust to place in the pattern.

Signal

How many robots carrying the component were verified in the last 90 days. Treat it as current footprint, not install base.

Delta

Change against the last stored snapshot. Positive means more recent verification activity, negative means cooling, and a dash means the baseline is still forming.

Momentum

Two consecutive moves in the same direction. Use it to separate one-off spikes from signals that are holding their shape.

Reliability

High reliability means multiple historical checkpoints, medium means limited history, low means the component still needs another capture before comparison becomes meaningful.

The 90-day window smooths out one-off updates. When you want the earliest hint of movement, cross-check against the 30-day view.

About AI Components

204 AI components represent the intelligence layer of home robots — from navigation algorithms and computer vision to large language models and adaptive behavior systems. AI is the most transformative technology category in modern robotics, determining how autonomously a robot can operate, how naturally it interacts with humans, and how well it adapts to unique home environments. The 90-day trends track which AI technologies manufacturers are actually shipping in production robots.

Most used: Not Officially Disclosed (2 robots), Reactive AI Obstacle Avoidance (200+ object types); SmartPlan 3.0 (2 robots), 10 TOPS AI platform with LiDAR and vision fusion for automatic mapping, path planning, 300+ obstacle recognition, and smart cliff protection (1 robots), 1x Embodied Intelligence (1 robots), 2× Intel i7 (8th gen, 6-core) edge computing (1 robots).

Using This Trend Data

Components with high signal values and rising deltas are gaining manufacturer adoption — these represent technologies the industry is converging around. Components with declining signals may indicate either a technology being phased out or simply a gap in recent verification activity. Pay attention to momentum alongside the delta: a component with sustained upward momentum across multiple snapshots is a stronger signal of genuine growth than one with a single positive delta. Reliability indicators tell you how much confidence to place in the trend — high reliability means the pattern is confirmed by multiple data points, while low reliability means the trend is based on limited historical data. For purchasing decisions, combine trend data with the individual component detail pages linked from the table, which provide deeper technical context and robot compatibility information.

Large language models — LLMs are rapidly entering companion and assistant robots, enabling natural conversation instead of keyword commands. This is the fastest-growing AI category in terms of manufacturer interest.
Edge AI processors — On-device chips (NVIDIA Jetson, Qualcomm RB5, custom silicon) enable real-time processing without cloud dependency, improving response time and privacy. Growing adoption signals manufacturer investment in capable standalone operation.
Computer vision models — Object recognition, scene understanding, and visual navigation are becoming standard equipment. Robots with dedicated vision AI can identify specific objects (shoes, cables, pet waste) rather than treating all obstacles generically.
Simultaneous localization and mapping (SLAM) — Advanced SLAM algorithms process sensor data to build and update home maps in real-time. Improvements in SLAM AI directly translate to better cleaning coverage and fewer stuck situations.

Buying Context

The gap between robots with modern AI and those without is significant and growing. A robot with LLM-powered voice interaction, vision-based object recognition, and edge AI processing can operate far more autonomously than one relying on preset patterns and basic sensors. However, AI capability is hard to evaluate from specs alone — look at actual user reviews for real-world performance. The trend data above shows which AI technologies are gaining broad manufacturer adoption, indicating maturity and reliability.

Compare with the 30-day ai trends for a broader adoption picture.

Related
Components Directory Components Glossary Robot Categories Compare Robots

Frequently Asked Questions

How often is the 90-day trend data updated?
Recalculated on every page load from current robot verification dates. Signal = robots verified in the last 90 days. Snapshots for delta/momentum are stored periodically.
What does "No baseline" mean for a ai component?
First measurement in this window — no previous snapshot to compare. Once a second snapshot is taken, the component gets a delta and eventually momentum data.
What is the difference between 30-day and 90-day trends?
30-day is volatile and sensitive to individual product launches. 90-day smooths noise and reveals sustained adoption. A component rising in both views is showing genuine growth.
How is momentum different from the trend delta?
Delta compares against the single last snapshot. Momentum requires two snapshots and checks for sustained direction — two consecutive increases or decreases. Momentum is a stronger signal of real change.
Can trend data predict which ai components will be popular?
Trends show historical adoption patterns, not predictions. But sustained upward momentum in the 90-day view tends to continue as it reflects manufacturer consensus. Cross-reference with industry news and announcements.
What is the difference between cloud AI and edge AI in robots?
Cloud AI sends data to remote servers for processing, enabling more powerful analysis but requiring internet connectivity. Edge AI processes data locally on the robot's own chip, providing faster response times and better privacy. Many modern robots use a hybrid approach — edge AI for real-time decisions (obstacle avoidance) and cloud AI for heavier tasks (map analysis, conversation).
How do I know if a robot's AI is actually good?
AI quality is difficult to assess from spec sheets alone. Look for: (1) specific capabilities like object recognition (can it identify shoes, cables, pet waste?), (2) independent reviews testing navigation in cluttered environments, (3) user reviews mentioning whether the robot learns and improves over time. The trend data here shows which AI platforms have broad manufacturer adoption — a proxy for maturity.