Sifted reads the web.
You read what matters.
Sifted reads the web so you don't have to. AI-powered research synthesis that surfaces the signal from the noise.
How It Works
We don't aggregate.
We synthesize.
We read full documents across thousands of sources every day, not just previews or summaries of summaries. Then distil them into a high-signal feed tailored to whatever you care about most.
News
Breaking stories and long-form journalism from the publications that set the agenda, before the summary-of-summaries crowd gets to it.
- Reuters
- Bloomberg
- The Economist
- Financial Times
- POLITICO
Research
Primary studies, white papers, and think-tank reports. The original data behind the headlines, not the watered-down press release.
- PubMed
- arXiv
- McKinsey Global Institute
- Brookings
- RAND
Industry
Earnings calls, analyst notes, company blogs, and the practitioners who write what textbooks will say in five years.
- Stratechery
- CB Insights
- Substack newsletters
- Company blogs
- LinkedIn Pulse
Community
Real-time discourse from the people closest to the work. Unfiltered, opinionated, and often ahead of formal publishing.
- Hacker News
- Reddit communities
- X / Twitter threads
- GitHub Trending
The Pipeline
Any source.
Any topic.
Pure signal.
Full articles, papers, and reports retrieved from across the web. Complete text, not just headlines.
Ads, navigation, and boilerplate stripped. What remains is clean, structured substance.
AI scores relevance to your topics and extracts the signal, from 0 to 100.
Rate Cuts: The 3 Assets That Actually Benefit
Your feed, updated daily. Ranked by signal, not by recency or engagement bait.
Live Synthesis
Hours of noise in. Minutes of signal out.
Advances in LLM Architecture
A 100-Page Technical Review · IEEE 2024
Key Concept
Multi-head attention is the shift
Allows models to simultaneously attend to different representation subspaces — making LLMs fundamentally different from prior sequential models.
Transformers Explained: A Deep Dive
Stanford Lecture Series — CS324 · 2h 04m
Core Insight
Scale follows predictable power laws
Compute × data × parameters obey Chinchilla-optimal ratios. Plan around them and you get significantly more capability for the same budget.
Attention Is All You Need + 58 Follow-up Studies
Vaswani et al. + meta-analysis · NeurIPS
Actionable Takeaway
Use Flash Attention 2 + grouped-query.
58 studies later the original paper's core claims hold. The field refined, not replaced, the transformer. These two impl choices close most of the efficiency gap.
Advances in LLM Architecture
A 100-Page Technical Review · IEEE 2024
Transformers Explained: A Deep Dive
Stanford Lecture Series — CS324 · 2h 04m
Attention Is All You Need + 58 Follow-up Studies
Vaswani et al. + meta-analysis · NeurIPS
Lattice-based Cryptography
Post-quantum algorithms that resist attacks from both classical and quantum computers — the ones your future AI overlords will be running.
Swap RSA-2048 for ML-KEM.
NIST standardised ML-KEM (formerly CRYSTALS-Kyber) in 2024. Migration tooling exists. Your 'we'll deal with it later' deadline just moved up.
Pricing
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For the curious and the time-poor.
- 2 AI-curated private feeds
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Pro
MOST POPULARFor teams and serious readers.
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