Small modular reactors top the board as hardware demand rises

SMR interest hits 1.36× the four-week pace, moving past Passkeys and AI agents while physical tech like humanoid robots climbs the ranks.

The numbers: Small modular reactors takes No. 1: Wikipedia readers at 1.36× the four-week pace. Small modular reactors: 1.36× momentum across 1 signal. 3 of 21 trends are climbing and 1 is cooling.

Backfilled on October 7, 2026 using only data published by September 29, 2026.

Small modular reactors, signal by signal

Each pedestal is one signal: its height is last week's typical day against the four weeks before, and the ring marks that normal. A lit pedestal is rising 1.15× or more.

Small modular reactors takes No. 1: Wikipedia readers at 1.36× the four-week pace.

Small modular reactors: 595 Wikipedia readers a day on a typical day last week, against 437 the four weeks before

Bars are single days, the line is the 7-day average, the shaded band is the last 7 days and the dashed line is the four-week typical day (median).

Data through npm 09/27, Wikipedia 09/28, HN 09/28. Source: Wikimedia pageviews API, user agents only.

Small modular reactors took the top spot with Wikipedia readers at 1.36× the four-week pace. This marks a change from yesterday when Passkeys led the board. The momentum for SMRs is now higher than the 1.33× seen in Passkeys and the 1.21× for AI agents. The focus is moving from digital authentication tools to physical energy generation systems.

The rise in SMRs aligns with other physical technologies gaining ground. Humanoid robots jumped from rank 21 to 14, and solid-state batteries moved from 17 to 11. Meanwhile, quantum computing dropped from 12 to 18. This pattern suggests builders are prioritizing tangible hardware components over abstract computational concepts. The board reflects a preference for systems that power and move physical objects.

AI agents remain steady with 653k daily installs, but they no longer hold the top growth position. The shift toward SMRs and batteries indicates a broader interest in the physical layer of technology. Builders are looking at how energy and robotics interact. The data shows attention is concentrating on the hardware that supports autonomous systems and sustainable power needs.

Watch next: Monitor if solid-state battery interest continues to climb alongside SMR adoption.

Column drafted by qwen/qwen3.8-27b from the numbers below; every figure checked against them.

The numbers

The Wikipedia article "Small modular reactor" drew 595 readers on a typical day last week, 1.36× its four-week norm of 437.

Next on the board: Passkeys at 1.33×, led by installs at 1.33× (887k on a typical day against 667k).

Quiet adoption: Bun runtime installs run at 1.18× their four-week pace while attention sits at 0.84×. Developers are adding it faster than people are reading about it.

Cooling fastest: Robotaxis at 0.81×, with Wikipedia readers down to 203 on a typical day from 251. Part of that is a spike on Sep 8 in the weeks before.

The long view: OpenAI Codex installs over the last four weeks are 116× the same four weeks a year earlier (3.4M a day against 29k).

Trend pages: Small modular reactors Passkeys AI agents Robotaxis

Quiet adoption

3 of 21 trends are climbing; Small modular reactors leads at 1.36×

Momentum is a typical day (median) of the last 7 divided by a typical day of the 28 before, averaged across every signal with enough data. 1× means no change. Rings mark each signal.

Data through npm 09/27, Wikipedia 09/28, HN 09/28. Source: npm downloads API, Wikimedia pageviews, Hacker News search.

4 of 7 developer tools are being installed faster than they are being read about

Across: attention momentum (Wikipedia readers and Hacker News stories). Up: install momentum (npm). Both on log scales; the 1× lines split the corners.

Data through npm 09/27, Wikipedia 09/28, HN 09/28. Source: npm downloads API, Wikimedia pageviews, Hacker News search.

Small modular reactors draws the most Wikipedia readers against its own normal: 1.36× over the last week

Each cell is one day's readers divided by that trend's four-week typical day. Brighter runs hot, darker runs cold.

Data through npm 09/27, Wikipedia 09/28, HN 09/28. Source: Wikimedia pageviews API, user agents only.

Every number on the board

All 22 trends, September 29, 2026. Per-day figures are a typical (median) day of the last week. * = base too small to count (under 1,000 installs, 100 readers or 1 story a day).

Small modular reactors	Energy	1.36×	Climbing	–	–	595	1.36×	0.0	0×*	0
Passkeys	Web platform	1.33×	Climbing	887k	1.33×	90	1.09×*	0.4	1×*	0
AI agents	AI agents	1.21×	Climbing	653k	1.19×	1,180	1.22×	13	1.21×	0
Smart glasses	Devices	1.14×	Steady	–	–	257	1.14×	1.1	2.5×*	0
AI API SDKs	AI agents	1.13×	Steady	18M	1.13×	–	–	–	–	0
WebGPU	Web platform	1.12×	Steady	1.5M	1.13×	135	1.11×	0.9	1.26×*	0
Vibe coding	AI coding	1.09×	Steady	–	–	1,687	1.22×	1.1	0.97×	0
SpaceX Starship	Space	1.08×	Steady	–	–	1,475	1.08×	1.6	6.3×*	0
Starlink	Space	1.07×	Steady	–	–	2,123	1.07×	0.9	2.2×*	0
Gemini CLI	AI coding	1.03×	Steady	64k	1.03×	–	–	0.0	n/a*	0
Solid-state batteries	Energy	1.03×	Steady	–	–	401	1.03×	0.0	0×*	0
Heat pumps	Energy	1.03×	Steady	–	–	489	1.03×	0.1	2×*	0
Model Context Protocol	AI agents	1.01×	Steady	10M	1.14×	1,538	1.08×	5.9	0.82×	0
Humanoid robots	Robots	1.01×	Steady	–	–	370	1×	0.6	0.61×*	0
Bun runtime	Web platform	1×	Steady	715k	1.18×	213	0.84×	0.6	0.59×*	0
OpenAI Codex	AI coding	0.98×	Steady	3.5M	1.06×	39	1.11×*	3.9	0.9×	0
Local LLMs	AI agents	0.97×	Steady	164k	0.91×	708	1.03×	0.6	0.84×*	0
Quantum computing	Devices	0.97×	Steady	–	–	1,879	1.07×	2.9	0.87×	1
Claude Code	AI coding	0.9×	Steady	2.0M	0.8×	–	–	6.9	1×	0
eVTOL air taxis	Space	0.9×	Steady	–	–	185	0.9×	0.0	0×*	0
Robotaxis	Robots	0.81×	Cooling	–	–	203	0.81×	0.0	0×*	0
Vehicle-to-grid	Energy	n/a	Not enough data	–	–	63	1.02×*	0.0	0×*	0

Method and sources

Every trend gets up to three free, daily signals. Installs: npm registry downloads for the packages named on each trend page (developer adoption; it counts CI and mirrors too, so it measures direction, not people). Attention: English Wikipedia readers per day, human agents only, and Hacker News stories with the term in the title. For each signal we divide a typical day (the median) of the last 7 complete days by a typical day of the 28 days before. Medians keep one launch-day spike from carrying a whole week; both windows are whole weeks, so weekend dips sit equally in both. Momentum is the geometric mean of the signals that clear a minimum base. npm reports some days as zero for every package at once; we treat those as missing.

The column is drafted by a free language model from the day's computed facts only, and is published only if every number in it matches those facts; otherwise the computed paragraphs stand alone. Theme labels come from Jev (or its Cloudflare Clef fallback, as noted) choosing from a fixed list of ten.

Stages: Breakout 1.5× and up, Climbing 1.15×, Steady 0.87× to 1.15×, Cooling below. Raw data: /api/trends/2026-09-29.json.