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Step 1: Describe
Just tell NBot what
you're looking for.
Forget complex boolean search strings or RSS management. Simply tell NBot what you’re interested in and it will build the perfect tracker for you.
- Understands niche technical terminology
- Automatically identifies top sources
- Suggests related topics to expand coverage
New Tracker Setup
I need to track the latest advancements in solid-state battery manufacturing, specifically focusing on dry-coating processes.
I can help with that. I've found key sources in academic journals (Nature Energy, Joule) and industry news covering companies like Tesla and Volkswagen.
Would you like me to include patent filings as well?
Yes, and also track...
ML Research Tracker2h ago
Sparse MoE models like Mixtral 8x7B are outperforming dense models in reasoning tasks while maintaining 40% lower inference costs.
Key breakthrough involves dynamic routing algorithms that minimize expert collapse.
The Rise of Mixture-of-Experts Models: A comprehensive survey
Step 2: Discover
Cut through the noise
to uncover real insights.
Your tracker monitors news outlets, newsletters, RSS feeds, niche blogs, and social media discussions – extracting core arguments, highlighting new data and key data points, and providing citations so you can verify instantly.
AI Summaries
Context-aware summaries that explain *why* it matters.
Direct Sources
One click to the original source material.
Step 3: Refine
Chat with your feed
to make it perfect.
Your tracker isn't static – it's an active agent. Use the built-in chat to ask questions or adjust your tracker in real-time.
"Can you summarize the main arguments against this approach?"
Instant Q&A on any topic in your feed.
"Stop showing me financial reports. Focus on engineering blogs."
Dynamic re-prompting of your tracker.
Feed Assistant
Change focus: prioritize engineering blogs over financial news.
Understood. I've updated your content filters.
Financial Reports Engineering Blogs
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Fee calculators can give you a quick first comparison when choosing where to sell. This one ranks platforms by estimated payout, with Vinted at the...
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The discussion mixes firsthand reports with untested hypotheses, so the evidence is thinner than the arguments.
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Two new papers take different routes to grounding robot manipulation in space:
- WICL keeps the model frozen and writes simulated rehearsal feedback...
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dNaViT Tests Discrete Visual Codes as a Shared Currency
The paper asks how far a finite discrete vocabulary can go in representing the visual world. The authors' answer rests on four points:
-...
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Ground-based LiDAR captures forest structure in precise 3D detail, but extracting usable meaning from the dense point clouds has been hard, partly...
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Measurement is the first gap IAB wants to close. 67% of surveyed leaders named it the top problem, and the most-requested fix is a common definition...
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The paper frames depth-wise information dilution in Pre-LN models as the core problem. Its proposed remedy, DepthGraft, rebuilds deep-layer KV from...
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Editing weights directly, without gradient training, can reportedly repair reasoning failures.
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Experimental screening samples only a small fraction of sequence space, so the authors frame the core challenge as traversing mutation combinations...
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PSI claims a proof of the Aaronson-Ambainis conjecture using an Anthropic model. Co-author Scott Aaronson says he doesn't fully understand the proof...
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Measurement is the first gap IAB wants to close. 67% of surveyed leaders named it the top problem, and the most-requested fix is a common definition...
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The paper frames depth-wise information dilution in Pre-LN models as the core problem. Its proposed remedy, DepthGraft, rebuilds deep-layer KV from...
Repairing Language Models by Editing Weight Bits
Editing weights directly, without gradient training, can reportedly repair reasoning failures.
- Agent starting point: A frontier LLM agent read the...
ProTEUS: A Mutation-Level World Model for Protein Evolution
Experimental screening samples only a small fraction of sequence space, so the authors frame the core challenge as traversing mutation combinations...
An AI Proof Claim Still Awaiting Verification
PSI claims a proof of the Aaronson-Ambainis conjecture using an Anthropic model. Co-author Scott Aaronson says he doesn't fully understand the proof...
Use Fee Calculators as a Starting Point
Fee calculators can give you a quick first comparison when choosing where to sell. This one ranks platforms by estimated payout, with Vinted at the...
Benchmarking Deep Learning for Forest LiDAR Segmentation
Ground-based LiDAR captures forest structure in precise 3D detail, but extracting usable meaning from the dense point clouds has been hard, partly...
Reader Debate Over Anthropic-Found Vulnerabilities: Evidence vs. Speculation
The discussion mixes firsthand reports with untested hypotheses, so the evidence is thinner than the arguments.
- Project-specific evidence: A Fil-C...
Creator Marketing's Measurement Gap Meets IAB's Standards Push
Measurement is the first gap IAB wants to close. 67% of surveyed leaders named it the top problem, and the most-requested fix is a common definition...
In-Context Rehearsal Versus Implicit Foresight in Robot Manipulation
Two new papers take different routes to grounding robot manipulation in space:
- WICL keeps the model frozen and writes simulated rehearsal feedback...
DepthGraft Proposes Cross-Layer KV Reuse for Deep Models
The paper frames depth-wise information dilution in Pre-LN models as the core problem. Its proposed remedy, DepthGraft, rebuilds deep-layer KV from...
AI Flags Cavity Risk Through Social Factors
Researchers applied machine learning to Brazil's national oral health survey to predict cavity risk by age group. Rather than relying on individual...
Repairing Language Models by Editing Weight Bits
Editing weights directly, without gradient training, can reportedly repair reasoning failures.
- Agent starting point: A frontier LLM agent read the...
Bridging Inference Theory and Serving Decisions
The Modelplane maintainers' guide targets platform engineers new to inference, covering how models and GPUs work together and how to run production...
ProTEUS: A Mutation-Level World Model for Protein Evolution
Experimental screening samples only a small fraction of sequence space, so the authors frame the core challenge as traversing mutation combinations...
dNaViT Tests Discrete Visual Codes as a Shared Currency
The paper asks how far a finite discrete vocabulary can go in representing the visual world. The authors' answer rests on four points:
-...
An AI Proof Claim Still Awaiting Verification
PSI claims a proof of the Aaronson-Ambainis conjecture using an Anthropic model. Co-author Scott Aaronson says he doesn't fully understand the proof...
Use Fee Calculators as a Starting Point
Fee calculators can give you a quick first comparison when choosing where to sell. This one ranks platforms by estimated payout, with Vinted at the...
Benchmarking Deep Learning for Forest LiDAR Segmentation
Ground-based LiDAR captures forest structure in precise 3D detail, but extracting usable meaning from the dense point clouds has been hard, partly...
Reader Debate Over Anthropic-Found Vulnerabilities: Evidence vs. Speculation
The discussion mixes firsthand reports with untested hypotheses, so the evidence is thinner than the arguments.
- Project-specific evidence: A Fil-C...
Creator Marketing's Measurement Gap Meets IAB's Standards Push
Measurement is the first gap IAB wants to close. 67% of surveyed leaders named it the top problem, and the most-requested fix is a common definition...
In-Context Rehearsal Versus Implicit Foresight in Robot Manipulation
Two new papers take different routes to grounding robot manipulation in space:
- WICL keeps the model frozen and writes simulated rehearsal feedback...
DepthGraft Proposes Cross-Layer KV Reuse for Deep Models
The paper frames depth-wise information dilution in Pre-LN models as the core problem. Its proposed remedy, DepthGraft, rebuilds deep-layer KV from...
AI Flags Cavity Risk Through Social Factors
Researchers applied machine learning to Brazil's national oral health survey to predict cavity risk by age group. Rather than relying on individual...
Repairing Language Models by Editing Weight Bits
Editing weights directly, without gradient training, can reportedly repair reasoning failures.
- Agent starting point: A frontier LLM agent read the...
Bridging Inference Theory and Serving Decisions
The Modelplane maintainers' guide targets platform engineers new to inference, covering how models and GPUs work together and how to run production...
ProTEUS: A Mutation-Level World Model for Protein Evolution
Experimental screening samples only a small fraction of sequence space, so the authors frame the core challenge as traversing mutation combinations...
dNaViT Tests Discrete Visual Codes as a Shared Currency
The paper asks how far a finite discrete vocabulary can go in representing the visual world. The authors' answer rests on four points:
-...
An AI Proof Claim Still Awaiting Verification
PSI claims a proof of the Aaronson-Ambainis conjecture using an Anthropic model. Co-author Scott Aaronson says he doesn't fully understand the proof...
Frequently Asked Questions
Everything you need to know about your new AI research assistant.
What exactly is an AI Tracker?
An AI Tracker is your personal research assistant that monitors thousands of sources 24/7. Simply describe a topic you care about—like "Pre-seed AI startups in Southeast Asia" or "Rust memory safety debates"—and your tracker will continuously find, filter, and summarize the most relevant content for you.
How do I create my first Tracker?
Just tell NBot what you're interested in using natural language—no complex search syntax needed. Our AI understands niche terminology, automatically identifies top sources, and sets up your tracker in seconds. You can refine it anytime through conversation.
How does NBot find and filter content?
NBot uses advanced AI to scan news outlets, industry blogs, newsletters, and social media. Instead of just listing headlines, it reads and understands each piece, removes noise, and surfaces only what truly matters to your specific interests—complete with AI-generated summaries explaining why it's relevant.
What is Feed Chat?
Feed Chat lets you have a conversation with your tracker in real-time. Ask questions about any content in your feed, request deeper analysis, or dynamically adjust what your tracker focuses on—like saying "Focus more on technical deep-dives, less on industry news."
Can I listen to my tracked content?
Yes! NBot generates daily AI podcast summaries of your tracked feeds. Perfect for staying informed during your commute, workout, or any time you prefer audio over reading.
Can I share my Trackers with others?
Absolutely. You can make your trackers public so others can follow the intelligence streams you've built. You can also discover and follow trackers created by experts in the community—a great way to tap into tracked knowledge across different fields.
Is NBot free to use?
Yes! Our free tier lets you create up to 2 personal trackers and follow 5 community trackers—perfect for getting started. Upgrade to Plus for more trackers and Feed Chat, or go Pro for daily podcast summaries and priority support.
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