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 13 GoAnywhere Alternatives
We compared the top 13 alternatives to GoAnywhere MFT, highlighting their secure file-transfer capabilities, including supported protocols, deployment options, and free trial availability. Note: Ratings are based on Capterra and G2. Vendors are listed based on rating. We list our subscribers at the top with their links. The alternatives are designed for a broad range…
20 Strategies for AI Improvement & Examples
AI models require continuous improvement as data, user behavior, and real-world conditions evolve. Even well-performing models can drift when the patterns they learned no longer match current inputs, leading to reduced accuracy and unreliable predictions. Changes in regulations, product requirements, or customer expectations can also introduce new constraints that existing models were not designed to…
Large Multimodal Models (LMMs) vs LLMs
Evaluate LLMs and LMMs by comparing their benchmark scores and real-world latency by clicking the model’s name in the table below. You can also weigh their input and output pricing to judge overall efficiency and value. *Audio is native on the E2B, E4B and 12B models only. Available in five sizes: E2B, E4B, 12B, 26B…
AIM Agentic Marketing Benchmark
We are introducing the AIM Agentic Marketing Benchmark, which measures agent performance on three marketing workflows: competitive gap analysis, ABM target list preparation, and a personalized sales deck. We also ran a separate website reputation audit in which agents examined AIMultiple’s English-language content and reported verifiable issues with factual accuracy, citations, consistency, freshness, functionality, grammar,…
Top 5 AI Guardrails: W&B Weave and Xnode Cortx
AI security failures are expensive and increasingly common. Many incidents stem from weak governance, particularly gaps in access control, data permissions, and oversight of model usage. AI guardrails reduce this risk by setting enforceable boundaries for how AI systems access data, generate outputs, and interact with users or business workflows. Explore how AI guardrails operate,…
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 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: W&B Weave HallucinationFree Scorer (part of CoreWeave Forge, formerly Weights & Biases), 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…
Top 25 Generative AI Finance Use Cases
I spent a decade consulting for financial services firms. Every AI implementation I saw followed the same pattern: pilot projects that looked impressive in presentations but stalled in production. That’s changing. Banks are now deploying generative AI at scale, and the results are measurable. Here’s what’s actually working, based on implementations you can verify. Specialized…
17 Generative AI Healthcare Use Cases
Healthcare systems are facing increased data volumes, staff shortages, and rising expectations for personalized care. Generative AI is emerging as a key solution by synthesizing unstructured medical data, such as clinical notes, imaging reports, and patient histories, into insights for clinicians and administrators. Explore how generative AI is applied across healthcare delivery, administration, and population…
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