Adoption dailyEnergy transition
Today's story: Small modular reactors
Modular hardware wins as SMR interest spikes five ranks
Small modular reactors jump to No. 7 while solid-state batteries fall, signaling a preference for deployable energy systems over theoretical breakthroughs.
The numbers: Small modular reactors is today's biggest mover: up 5 places to No. 7, Wikipedia readers at 1.12× the four-week pace. Small modular reactors: 1.12× momentum across 1 signal. 4 of 21 trends are climbing and 4 are cooling. SpaceX Starship still leads the board at 1.57× (day 7).
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 is today's biggest mover: up 5 places to No. 7, Wikipedia readers at 1.12× the four-week pace.
Small modular reactors: 527 Wikipedia readers a day on a typical day last week, against 469 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 10/05, Wikipedia 10/06, HN 10/06. Source: Wikimedia pageviews API, user agents only.
Small modular reactors climbed five places to rank No. 7, with Wikipedia readers at 1.12× the four-week pace. This surge contrasts with solid-state batteries, which dropped from No. 8 to No. 12. The market is rewarding tangible, deployable units over long-term research concepts. Builders are prioritizing systems that can be manufactured and installed now, rather than waiting for theoretical efficiency gains.
Headlines reinforce this physical focus. A US microreactor reached criticality in 150 days, and the Navy adopted modular designs for faster missile production. Meanwhile, quantum computing cooled to 0.71× momentum, and smart glasses dropped to 0.68×. Attention is moving away from speculative tech toward hardware with clear deployment timelines and immediate industrial utility.
SpaceX Starship remains at No. 1 for the seventh day, holding 1.57× momentum. However, the SMR rise suggests a broader trend: builders are selecting technologies based on near-term integration. The gap between attention and installs for Claude Code, where installs sit at 0.99× while attention hits 1.3×, highlights that practical utility drives sustained adoption over viral curiosity.
Watch next: Monitor whether SMR interest translates into API or SDK growth for energy management tools.
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 527 readers on a typical day last week, 1.12× its four-week norm of 469.
Still No. 1 for day 7: SpaceX Starship at 1.57×, with Wikipedia readers at 1.57× (2,165 on a typical day against 1,378).
Talk ahead of installs: attention to Claude Code runs at 1.3× while installs sit at 0.99×. Watch whether usage follows.
Cooling fastest: Smart glasses at 0.68×, with Wikipedia readers down to 153 on a typical day from 224.
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: SpaceX StarshipPasskeysAI API SDKsSmart glasses
Talk ahead of installs4 of 21 trends are climbing; SpaceX Starship leads at 1.57×
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 10/05, Wikipedia 10/06, HN 10/06. Source: npm downloads API, Wikimedia pageviews, Hacker News search.
5 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 10/05, Wikipedia 10/06, HN 10/06. Source: npm downloads API, Wikimedia pageviews, Hacker News search.
SpaceX Starship draws the most Wikipedia readers against its own normal: 1.57× 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 10/05, Wikipedia 10/06, HN 10/06. Source: Wikimedia pageviews API, user agents only.
Every number on the board
| SpaceX Starship | Space | 1.57× | Breakout | – | – | 2,165 | 1.57× | 0.1 | 0.23×* | 0 |
|---|---|---|---|---|---|---|---|---|---|---|
| Passkeys | Web platform | 1.3× | Climbing | 1.1M | 1.3× | 92 | 1.04×* | 0.1 | 0.36×* | 0 |
| AI API SDKs | AI agents | 1.19× | Climbing | 21M | 1.19× | – | – | – | – | 0 |
| Model Context Protocol | AI agents | 1.17× | Climbing | 12M | 1.27× | 1,663 | 1.11× | 7.7 | 1.14× | 0 |
| Claude Code | AI coding | 1.14× | Steady | 2.2M | 0.99× | – | – | 8.4 | 1.3× | 0 |
| OpenAI Codex | AI coding | 1.13× | Steady | 3.9M | 1.11× | 99 | 2.5×* | 5.0 | 1.15× | 0 |
| Small modular reactors | Energy | 1.12× | Steady | – | – | 527 | 1.12× | 0.0 | n/a* | 0 |
| WebGPU | Web platform | 1.11× | Steady | 1.7M | 1.17× | 137 | 1.06× | 1.1 | 1.6×* | 0 |
| Starlink | Space | 1.1× | Steady | – | – | 2,195 | 1.1× | 0.7 | 1.43×* | 0 |
| AI agents | AI agents | 1.08× | Steady | 782k | 1.26× | 962 | 0.81× | 14 | 1.24× | 4 |
| Bun runtime | Web platform | 1.06× | Steady | 708k | 1.08× | 244 | 1.03× | 1.0 | 1.22×* | 0 |
| Solid-state batteries | Energy | 1.06× | Steady | – | – | 427 | 1.06× | 0.0 | 0×* | 1 |
| Heat pumps | Energy | 1.05× | Steady | – | – | 502 | 1.05× | 0.0 | 0×* | 1 |
| Gemini CLI | AI coding | 1.02× | Steady | 66k | 1.02× | – | – | 0.0 | n/a* | 0 |
| Local LLMs | AI agents | 1× | Steady | 192k | 1.13× | 634 | 0.9× | 0.7 | 1.11×* | 0 |
| Vibe coding | AI coding | 0.95× | Steady | – | – | 1,755 | 1.16× | 0.9 | 0.77× | 0 |
| eVTOL air taxis | Space | 0.91× | Steady | – | – | 181 | 0.91× | 0.0 | 0×* | 0 |
| Humanoid robots | Robots | 0.81× | Cooling | – | – | 301 | 0.81× | 0.9 | 1.04×* | 0 |
| Quantum computing | Devices | 0.71× | Cooling | – | – | 1,700 | 0.93× | 1.7 | 0.55× | 0 |
| Robotaxis | Robots | 0.7× | Cooling | – | – | 175 | 0.7× | 0.9 | 2.2×* | 1 |
| Smart glasses | Devices | 0.68× | Cooling | – | – | 153 | 0.68× | 0.7 | 1×* | 1 |
| Vehicle-to-grid | Energy | n/a | Not enough data | – | – | 54 | 0.87×* | 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/2026-10-07.json.