Sıla Ermut
Research interests
Sıla's research areas include email marketing, eCommerce marketing campaigns and marketing automation.She is also part of AIMultiple's email deliverability benchmark. She is designing and running email deliverability benchmarks while collaborating with the AIMultiple technology team.
Professional experience
Sıla previously worked as a recruiter and worked in project management and consulting firms.Education
She holds:- Bachelor of Arts degree in International Relations from Bilkent University.
- Master of Science degree in Social Psychology from Başkent University.
Her Master's thesis was focused on ethical and psychological concerns about AI. Her thesis examined the relationship between AI exposure, attitudes towards AI, and existential anxieties across different levels of AI usage.
Latest Articles from Sıla
10 Steps to Developing AI Systems
IBM identifies the top AI adoption challenges as concerns over data bias (45%), lack of proprietary data (42%), insufficient generative AI expertise (42%), unclear business value (42%), and data privacy risks (40%).These obstacles can hinder AI implementation, slow innovation, and reduce the return on investment for organizations adopting AI technologies.
Control-M for Enterprise Workload Automation
Control-M is BMC Software’s workload automation solution that orchestrates application and data workflows across mainframe, cloud, and hybrid environments through a centralized interface. The platform manages complex workflow dependencies, provides end-to-end visibility into production processes, and integrates with major cloud services, data platforms, and DevOps tools.
Customer Engagement Automation: 5 Tools & Examples
Businesses face rising customer expectations and limited resources, especially as 80% of customers now value their experience as much as the product itself.Meeting these expectations requires clever use of customer engagement automation tools, which we divided into two categories: individual and comprehensive tools.
Generative AI in Manufacturing: Use Cases & Benefits
Generative AI is becoming a strategic tool for manufacturers facing challenges such as supply chain disruptions, labor shortages, and rising cost pressures. It helps automate design, predict maintenance needs, and optimize supply chains, while driving efficiency, reducing costs, and speeding up innovation.
Applying RLHF: Techniques, use cases, and challenges
Training AI systems to align with human values can be a challenge in machine learning. To mitigate this, developers are advancing AI through reinforcement learning (RL), allowing systems to learn from their actions. A notable trend in RL is Reinforcement Learning from Human Feedback (RLHF), which combines human insights with algorithms for efficient AI training.
eCommerce Data Collection: Best Practices & Examples
As online shopping grows and customer expectations shift, eCommerce businesses face increasing pressure to stay competitive. Real-world data is key to making faster, smarter decisions. Failing to collect and utilize data properly can result in missed sales, inefficient operations, and poor customer retention.
Top 5 Price Monitoring Tools
A key challenge for businesses is maintaining competitive pricing while adapting to market fluctuations. Price monitoring tools help solve this challenge by tracking competitors’ prices and providing insights for more dynamic pricing decisions.
Generative AI for Sales Use Cases
Unlike traditional AI in sales applications, which typically focuses on data analysis and pattern recognition, generative AI actively contributes to the sales process by creating content, drafting communications, and improving customer engagement. Explore the future of generative AI for sales, including use cases with examples that align with the steps of a typical selling process.
Image Recognition vs Classification: Applications with Examples
Businesses increasingly leverage AI-powered visual data solutions, but confusion between image recognition and classification leads to inefficiencies. Understanding the key differences helps businesses optimize AI deployment in the security, healthcare, and retail fields. Explore image recognition vs classification, their key differences, and applications with real-life examples.
How to Create Ordinal Inscriptions: Step by Step Guide
Creating NFTs on the Bitcoin blockchain can be complex due to limited wallet support, technical steps, and high transaction fees. As ordinal inscriptions, also known as Bitcoin NFTs, gain popularity, understanding how to create and manage them has become essential.
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