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0.25 page – Beth Cohen will fill in when the paper is mostly complete.
2 Background
0.5 page
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2.1 Autonomous Network Beth Cohen
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2.2 LLM & GenAI Sandeep Panesar
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2.3 LFN & Previous AI WP
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3 Motivation
1 page
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Beth Cohen
2.4 LF Data (Thoth)- Sandeep Panesar Beth Cohen
3 Challenge Statement and Motivation Beth Cohen
1 page
Focus on Telco pain points only,
3.1 traditional CSP pain points
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- Beth Cohen
- Operational Efficiency – reduce costs and errors, potentially increase margins
- Network Automation - reduce expenditure
l Business Innovation - increase income
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3.2
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Emerging CSP Opportunities Sandeep Panesar
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- Converged Infrastructure for the era of AI
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- Converged Service for the era of AI
4 Problem Statement
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- Business Innovation - New revenue streams (data monetization?)
4.1 network AI explorations so far
1.5 page
- l Radio Access Network ChangJin Wang
- l Core Network Hui Deng ChangJin Wang
- l Bearer & DC Network - Cisco?
- l Cross domain network AI platform Lingli Deng
- l Telecom Cloud Hui Deng
4.2 challenges towards fully autonomy Lingli Deng Andrei Agapi
0.5 page
- l high quality structured data
- l AI trustworthiness
- l non-economic margin cost
- Contextual data sets
- l TBA
4.3 Network LLM: the game changer?
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4.3.1 issues solved/mitigated Andrei Agapi
- l high quality structured data
- l AI trustworthiness
- l non-economic margin cost
- l TBA
4.3.2 issues added/aggravated
- l high quality structured data
- l AI trustworthiness
- l non-economic margin cost
- l TBA
5 How could Open Source Help?
2-3 pages
5.1 Related Open Source Landscape Andrei Agapi
1-2 pages
- l Network communities
- l AI communities
- l Integration BPs
- l Verification programs
5.2 Common Vision: intelligence plane for
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XG
1 page
- l natural intent interaction
- l cognitive smart orchestration
- l real-time meta-network verification
- l built-in knowledge open
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- loops
5.2 Related Open Source Landscape
1-2 pages
l Network communities
l AI communities
l Integration BPs
l Verification programs
6 Call for Action Beth Cohen
0.25 page