Sıla Ermut
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
Top 9 AI Providers Compared
The AI infrastructure ecosystem is growing rapidly, with providers offering diverse approaches to building, hosting, and accelerating models. While they all aim to power AI applications, each focuses on a different layer of the stack. We benchmarked the most widely used providers on OpenRouter: Cerebras, DeepInfra, Fireworks AI, Groq, Nebius, and SambaNova, using the GPT-OSS-120B…
AI Hallucination Detection Tools: W&B Weave & Comet
We benchmarked three hallucination detection tools: Weights & Biases (W&B) Weave HallucinationFree Scorer, Arize Phoenix HallucinationEvaluator, and Comet Opik Hallucination Metric, across 100 test cases. Each tool was evaluated on accuracy, precision, recall, and latency. We tested 100 responses (50 correct, 50 hallucinated) from factual Q&A scenarios against their source context. See the benchmark methodology.…
LLM Market Share: Compare Usage & Adoption
We analyzed LLM market share by combining usage-based data and web visit estimates to show how demand for large language models is distributed across AI labs and AI applications: Read the methodology to see how we measured and calculated these results. The United States dominated web visits across all four months, consistently accounting for 85–95%.…
Large World Models: Use Cases & Examples
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. Discover what large world models are,…
10+ Large Language Model Examples
We have gathered open-source benchmarks to compare leading proprietary and open-source large language models. Choose your use case to find the right model. You can evaluate large language models by examining their benchmark performance and real-world latency (available by clicking each model’s name in the table), and by reviewing their pricing to assess overall efficiency…
Top 13 GAN Use Cases
While GANs pioneered many early generative AI applications, particularly in image synthesis and style transfer, most consumer-facing generative AI tools today rely on diffusion-based architectures or related approaches such as flow matching and diffusion transformers (DiT). However, GANs remain important in specific domains, such as super-resolution, face restoration, the generation of synthetic tabular or healthcare…
AI Presentation Maker: Gamma vs Google Slides
We evaluated the top 5 AI presentation makers across 9 dimensions with 4 different prompts to assess their context and prompt understanding, visual AI integration, and voice and brand style adaptation capabilities: See the methodology and evaluation criteria to understand how we determined these results. The score variations across Gamma, Google Slides with Gemini, SketchBubble,…
Top 11 AI in ITSM Use Cases & Examples
Leveraging AI for IT service management (ITSM) tools supports organizations in terms of: See the top 11 use cases of AI in ITSM, examples, and benefits of leveraging AI in ITSM. AI-native ITSM refers to a new way of managing internal support and IT operations where artificial intelligence is not an added feature but part…
AI Image Detector Benchmark
As synthetic visuals grow more realistic and accessible, the ability to detect them has become a critical concern for upholding generative AI ethics, combating misinformation, and ensuring image authenticity. We compared the top 7 AI image detectors across 5 dimensions and found that most perform no better than a coin toss. See insights into their…
15 AI Agents in Marketing Tools & Examples
Research shows that 50% of organizations using generative AI plan to launch agentic AI pilot programs.63AI agents in marketing introduce systems that can reason, make decisions, and act with minimal human oversight. These intelligent agents analyze customer data, generate actionable insights, and coordinate campaigns across multiple platforms in real-time. We evaluated the top 15 AI…
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