Tracking what developers ship, investors fund, and enterprises adopt
From GitHub commits to SEC filings, scored by AI to separate real trends from noise.
Deep Learning
A subset of machine learning involving neural networks with many layers.
6/6
Sources with signal
Strong
Signal strength
1.2k
Evidence points
Hot
Signal strength
B2B
Market tracked
Signal breakdown by source
We track real-time data from developer platforms, startup ecosystems, academic research, and enterprise filings to identify trends backed by hard evidence.
Hacker News
Community awareness · Last 14 days
Upvotes from the tech community. More points = more attention.
Stories and discussion on Hacker News indicate tech community awareness. High HN activity often precedes mainstream adoption by 1-3 months.
-Tinybox – A powerful computer for deep learning
-François Chollet: ARC-AGI-3, Beyond Deep Learning and a New Approach to ML [vide…
-Deep learning-based morphological classification of ceramics
GitHub
Developer creation velocity · Last 30 days
Stars are bookmarks from developers. More stars = higher quality projects.
New repositories signal active developer investment. GitHub creation velocity is a 3-12 month leading indicator of market adoption.
-Genius-apple/RusTorch: RusTorch is a production-grade deep learning framework re…
-0324Lw/Deep-Reinforcement-Learning-Notes: 这是我的深度强化学习的学习笔记与总结
-fab2s/floDl: rust recursive deep learning framework
Y Combinator
Startup funding signal · Last 4 batches
YC runs batches twice a year. More batches = sustained investor interest over time.
YC-backed companies in this space represent the strongest conviction signal: venture capital betting on market potential.
-Ishiki Labs: Building the Future of Multimodal AI
-AxionOrbital Space: Foundation models for 24/7 Earth Observation
Stack Overflow
Developer adoption · Last 90 days
Stack Overflow questions indicate developers actively using the technology. A 3-6 month leading indicator of production adoption.
-Best architecture for integrating Python deep learning prototype into C++ produc…
-Is this Deep Learning → GenAI roadmap (project-based) sufficient for transitioni…
-ow do I break down a deep learning project into smaller steps as a beginner?
Academic Research
Research publication signal · Last 24 months
Citations count how often other researchers reference this work. More citations = higher influence.
Academic papers represent the earliest indicator. Researchers publishing findings that drive the next wave of applied innovation.
-Classifying Crop Leaf Diseases using Different Deep Learning Models with Transfe…
-Off-Policy Deep Reinforcement Learning without Exploration
-Deep learning-based structural health monitoring
SEC Corporate Filings
Enterprise adoption signal · Latest filings
Mentions in SEC 10-K/10-Q filings mean public companies are disclosing this technology as material to their business. This is the strongest enterprise validation signal.
-Spectral AI, Inc. (MDAI, MDAIW) (): ANNUAL REPORT
-Rank One Computing Corp (ROC) (): ANNUAL REPORT
-BLUSKY AI INC. (BSAI) (): 10-K
All data is sourced from public APIs: Hacker News (Algolia), GitHub (Search API), Stack Overflow (Stack Exchange API), Y Combinator (public batch data), OpenAlex (academic database), and SEC EDGAR (regulatory filings). Numbers reflect verified matches. Each item is checked by AI to confirm it's genuinely about the topic, not just a keyword overlap.
What the data tells us
6 independent sources show real activity around Deep Learning. Developers are building tools (GitHub), the tech community is talking about it (Hacker News), investors are backing startups in the space (Y Combinator), researchers are publishing papers, and enterprises are disclosing it in public filings. When this many unrelated sources agree, it's not speculation. It's market movement.
Why this data matters
We don't guess. We count what's actually happening.
Most trend reports are opinions. Inqvey Trends is different . We track what developers are building, what investors are funding, what researchers are publishing, and what enterprises are reporting to regulators. When multiple independent sources point to the same trend, it's not hype. It's a real market shift.
Hacker News
Community awareness (1-3 month lead)
GitHub
Developer creation velocity (3-12 month lead)
Y Combinator
Startup funding conviction signal
Stack Overflow
Technology adoption (3-6 month lead)
OpenAlex
Academic research (earliest indicator)
SEC EDGAR
Enterprise disclosure (strongest validation)
Each source is scored on a 0-100 scale based on activity volume. When a topic shows up across multiple unrelated sources (developers on GitHub, startups at Y Combinator, filings at the SEC) that agreement between independent signals is what separates real trends from noise. We use AI to verify that each result is genuinely about the topic, not just a keyword match.
Data freshness
Sources are scanned daily. Hacker News and GitHub reflect the last 14–30 days. Y Combinator covers the last 4 batches. Academic papers span the last 24 months. SEC filings cover the most recent quarterly and annual reports.
Go from trend to market intelligence
Knowing what's trending is step one. Knowing what the market actually wants is what drives product decisions.
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