Everything / Models and research / Deep learning
Deep learning Cooling
On TutorHero's Everything Index, Deep learning is cooling on GitHub: 2.78 of every 10,000 new public repos over the last three months (2.6k a month), +20% vs a year ago and 0.88x its level when ChatGPT launched. The 12-month forecast says holding (+6%). By the end of 2032, lines in the same state ended between 0.28x and 4.8x of where they started (median 0.82x).
Since 2019, and the range to 2032
New repos per 10,000 (3-month average, log scale)12-month forecastRange to 2032: middle half and 90% of past similar linesJev's 2032 call
The range is not a forecast of this line: it is what GitHub lines in the same state (grew its share 15% to 100% in a year) did 1 to 5 years later, 2019 to 2026, applied to today's level. Past 5 years it is stretched, not measured. Checked out of time (learned before 2022, scored after), 71% of outcomes landed inside the 90% range, so read it as wide. Open it in the Everything chart.
Week by week
Wikipedia views a day, last 8 weeks
New public repos with the deep-learning tag each week (Monday to Sunday, UTC). The outlined bars, last week included, are still filling in, as tags are often added days after a repo is created, so their height will grow a little. "Against the field" divides the change by what the typical tag did, so a wave that lifts every tag does not count. Hover for the numbers.
Built vs talked about
Each line is its own share (of all new GitHub repos, all Hacker News stories, all English Wikipedia views, all new stars on the repos we track), shown as a share of its own peak, so the timing and shape compare even though the units differ. Hover for the counts. Tap a name to hide or show a line.
What it means
- Learn the ideas more than the name: Deep learning is cooling, -52% below its Jul 2020 high.
- Start by reading rohitg00/ai-engineering-from-scratch (+10.9k stars in 3 months) and multimodal-art-projection/YuE (+4.4k stars in 3 months).
- People to follow: AUTOMATIC1111, pytorch, OpenCV.
- Jev for someone who wants to contribute or get hired: Test small (2.0 of 4).
- Getting crowded: new repos +20% but attention -45%, so each new project competes harder for stars.
- 4.90 new stars per new repo over 3 months, vs 8.50 for the typical trend: more supply than demand right now.
- The 12-month forecast for its share: +6% (Holding).
- Talk and building in step: Hacker News -53% vs new repos +20% in a year, close to the typical trend.
- Jev for a builder: Test small (1.8 of 4).
- History: of past GitHub lines that grew its share 15% to 100% in a year, 49% had a smaller share 3 to 5 years later and 13% at least doubled.
- Jev's 2032 call: better than most similar lines (unsure), which on the base rates means about 1.14x today's share by the end of 2032.
- Attention: 2.31% of new stars on the repos we track, -45% in a year.
- Hacker News: 5 stories a month, -53% share in a year; Wikipedia 24.6k views a month, -17%.
- Jev for an investor: Test small (1.6 of 4).
- Not investment advice: this measures what people build on GitHub, not any company.
- Most-starred tools here lately: rohitg00/ai-engineering-from-scratch (vouched), multimodal-art-projection/YuE.
- Check that a tool is still maintained before you adopt it: the field is shrinking.
- Jev for a developer picking tools: Test small (1.8 of 4).
Repos carrying it now
People building it
AUTOMATIC1111Creating the Stable Diffusion web UI and its extensions.Influence 70
pytorchOpen-source machine learning framework with GPU acceleration and AI tools.Influence 93
OpenCVOpen source computer vision library with extra modules and tools.Influence 51
UltralyticsDemocratizing Vision AI with YOLO object detection models.Influence 78
HumanSignalData labeling and exploration tools for machine learning.Influence 33
⚡️ Lightning AI Creating PyTorch Lightning and AI tools for scalable model development.Influence 57
coquiOpen speech technology for everyone.Influence 45
StreamlitBuilding and sharing data apps faster.Influence 32More in Models and research
Questions
Is Deep learning growing on GitHub?
Yes. Its share of all new public GitHub repos is +20% vs a year ago and -16% over the last three months (Sep 2026). Phase: Cooling.
How many new Deep learning repos are created each month?
About 2.6k new public repos a month carry the deep-learning tag (three-month average to Sep 2026), or 2.78 of every 10,000 new repos.
What will Deep learning look like in 2032?
Nobody knows, and we say how much. Of past GitHub lines that grew its share 15% to 100% in a year, the middle half had between 0.53x and 1.41x of their share 3 to 5 years later, and 49% ended smaller. Jev's call: Better than most similar lines.
Is Deep learning more talked about than built?
Talk and building in step. Over the year its share of Hacker News stories moved -53% while its share of new GitHub repos moved +20%. New repos grew faster than talk for most AI trends this year, so the label compares it with the typical trend: 1.4 times the talk per builder of the median trend.
Not investment advice. Measurements of what people build and star on GitHub, a statistical forecast, base rates and a model's reading of them. Nothing here is about any company's revenue, valuation or stock.