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Sıla Ermut

Sıla Ermut

Industry Analyst
87 Articles
Stay up-to-date on B2B Tech

Sıla is an industry analyst at AIMultiple covering AI models, AI infrastructure, AI governance, and enterprise applications of AI.

Research interests

Sıla’s research focuses on the use of AI in marketing, healthcare, supply chains, and sustainability. She also covers AI evaluation, governance, ethics, and adoption.

Her work includes researching and comparing AI technologies, analyzing their business applications, and contributing to AIMultiple’s technology benchmarks.

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

AI
Insight
Aug 6

Compare AI Revenues Across the Stack

The AI market expanded rapidly across all four layers (data, compute, models, and applications). For example, NVIDIA’s data center revenue increased from $47.5B to $115.2B in a single fiscal year (FY2024 to FY2025, ending January 2024 and January 2025). We tracked revenue data from over 80 AI companies. Explore how revenues shifted across compute, data,…

Enterprise Software
Feature Comparison
Aug 3

AutoSys: Key Features and User Insights

Interest in Broadcom’s AutoSys is declining (Source: Google Trends) and it has a lower average rating on review platforms compared to most other workload automation tools. This may be partially explained by: Dive into AutoSys’s capabilities, user evaluations, and outlook to learn more: AutoSys was originally developed by CA Technologies and acquired by Broadcom in…

Enterprise Software
Insight
Jul 23

eCommerce Technologies Use Cases & Examples

Increasing competition in the eCommerce sector requires businesses to understand how technology is changing customer expectations. Organizations must remain informed about emerging tools and market developments to respond effectively and sustain service quality. Discover the top 15 eCommerce technologies in personalization and customer engagement, operations and efficiency, and payment systems: Chatbots and intelligent virtual assistants…

AI
Insight
Jul 23

AI Rollups: Funding, Investors and Industry Trends

We analyzed 30 investments involving over 130 investors from the past 3 years to understand the current trend for AI rollups. Based on our analysis, we identified investor activity and trends, including the number of investors backing AI rollups, the total funding raised for AI rollups, and the leading industries. See the methodology to learn…

AI
Insight
Jun 25

Large Quantitative Models: Applications & Challenges

Modern systems are becoming too complex for traditional statistical analysis, as institutions now handle massive datasets, including patient, weather, and financial market data. Large quantitative models (LQMs) help by processing these datasets, integrating structured and unstructured data, and applying predictive modeling to uncover patterns and provide data-driven insights that traditional methods cannot deliver. Discover what…

Enterprise Software
Feature Comparison
Jun 16

Prices of Top 6 IT Service Management (ITSM) Software

IT Service Management (ITSM) tools that support incident, problem, change, and knowledge base management offer diverse pricing models. See IT service management pricing details of the top 6 providers and the feature guide for small businesses and enterprises. Note: Pricing information is obtained from vendor websites. Explore IT asset management pricing to discover additional vendors…

AI
Benchmark
Apr 15

LLM Quantization: BF16 vs FP8 vs INT4

We benchmarked Qwen3-32B at 4 precision levels (BF16, FP8, GPTQ-Int8, GPTQ-Int4) on a single NVIDIA H100 80GB GPU. Each configuration was evaluated on 2 benchmarks (~12.2K questions) covering knowledge and code generation, plus 2,000+ inference runs to measure throughput. Int4 is 2.7x faster than BF16 while losing less than 2 points on MMLU-Pro, but code…