Sıla Ermut
Sıla is an industry analyst at AIMultiple focused on email marketing and sales videos.
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
Top 10 Marketplace Optimization Tools in 2026
Brands selling on eCommerce marketplaces face challenges such as high competition, unpredictable demand, and limited product visibility. These issues often lead to reduced profitability and inefficient resource use. Marketplace optimization uses data, automation, and analytics to improve pricing, advertising, and content performance.
Top 15 Use Cases in AI for Neurology with Examples [2026]
Neurological disorders are among the most complex and costly to diagnose and manage, contributing billions in global healthcare expenditures each year.
E-Commerce AI Video Maker Benchmark: Veo 3 vs Sora 2
Product visualization plays a crucial role in e-commerce success, yet creating high-quality product videos remains a significant challenge. Recent advancements in AI video generation technology offer promising solutions.
25 Healthcare AI Use Cases with Examples in 2026
Healthcare systems are under growing pressure from rising patient data volumes and increasing demand for personalized care. Healthcare AI applications have emerged as a powerful solution to these problems by optimizing processes, enhancing diagnostic accuracy, and improving patient outcomes.
Compare Relational Foundation Models in 2026
We benchmarked SAP-RPT-1-OSS against gradient boosting (LightGBM, CatBoost) on 17 tabular datasets spanning the semantic-numeral spectrum, small/high-semantic tables, mixed business datasets, and large low-semantic numerical datasets. Our goal is to measure where a relational LLM’s pretrained semantic priors may provide advantages over traditional tree models and where they face challenges under scale or low-semantic structure.
AGI/Singularity: 9,300 Predictions Analyzed
Artificial general intelligence (AGI/singularity) occurs when an AI system matches or exceeds human-level cognitive abilities across a broad range of tasks, rather than excelling in a single domain. While many researchers and experts anticipate the near-term arrival of AGI, opinions differ on its speed and development pathway.
Large World Models: Use Cases & Examples in 2026
Despite advances in large language models, artificial intelligence remains limited in its ability to understand and interact with the physical world due to the constraints of text-based representations. Large world models address this gap by integrating multimodal data to reason about actions, model real-world dynamics, and predict environmental changes.
Top 5 AI Guardrails: Weights and Biases & NVIDIA NeMo
As AI becomes more integrated into business operations, the impact of security failures increases. Nearly all AI-related breaches occurred in environments without proper access controls, underscoring the risks of poorly governed AI deployments. AI guardrails address this gap by defining clear boundaries for AI use, supporting regulatory compliance and accountability, and enabling responsible long-term adoption.
Top 12 IT Service Management Tools in 2026
We evaluated the top 10 IT service management tools based on user experience, performance, and feature set. Explore our findings to see how these leading solutions differ in areas including AI features, communication integrations, DevOps, monitoring & security connections, and deployment options.
LLM Observability Tools: Weights & Biases, Langsmith ['26]
LLM-based applications are becoming more capable and increasingly complex, making their behavior harder to interpret. Each model output results from prompts, tool interactions, retrieval steps, and probabilistic reasoning that cannot be directly inspected. LLM observability addresses this challenge by providing continuous visibility into how models operate in real-world conditions.
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