SLM vs LLM: When 2B parameters beat 1T
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The assumption that bigger models are always better isintuitive but wrong.
Banking and Finance
Cloud computing. AI-driven automation. Advanced data analytics. By embracing these innovations, financial institutions can enhance customer experiences, streamline operations, and secure a competitive edge in the evolving market.
AML solutions
Cloud for regulated entities
Hyper-personalization
Security & compliance
Banking as a Service (BaaS)
AI-first applications
Financial institutions became technological firms with massive risks and opportunities
The banking sector is undergoing rapid technological transformation, with substantial investments in artificial intelligence (AI) to enhance efficiency and customer experience. However, challenges such as data management and consumer trust persist, highlighting the need for strategic implementation of these technologies.
Current state of the financial market
21%
currently using AI banking tools, indicating a growing adoption of AI in personal finance
38%
of financial institutions identify data management as their biggest obstacle to AI adoption
$35B
is the estimated size of the global artificial intelligence in banking in 2025
26%
of customers refuse to use AI for financial purposes
What's hot in banking and finance
What is SLM and why size matters
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A clear explanation of SLMs: purpose-built AI models that deliver faster, more accurate results while keeping your data on-premise.
The AI Automation Field Guide: From Pilot to Production in 90 Days
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A pragmatic 90-day roadmap to take AI automation from pilot to secure production.
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