Şevval Alper
Şevval is an AI researcher at AIMultiple. She has previous research experience in pseudorandom number generation using chaotic systems.
Research interests
Şevval focuses on AI coding tools, AI agents, and quantum technologies.
She is part of the AIMultiple benchmark team, conducting assessments and providing insights to help readers understand various emerging technologies and their applications.
Professional experience
She contributed to organizing and guiding participants in three “CERN International Masterclasses - hands-on particle physics” events in Türkiye, working alongside faculty to facilitate learning.
Education
Şevval holds a Bachelor's degree in Physics from Middle East Technical University.
Latest Articles from Şevval
Top 10 Google Colab Alternatives
Google Colaboratory is a popular platform for data scientists and machine learning scientists, but its limitations and pricing may not meet your needs. Several alternatives offer unique features and capabilities that cater to different data science needs and scenarios.
LLM Parameters: GPT-5 High, Medium, Low and Minimal
New LLMs, such as OpenAI’s GPT-5 family, come in different versions (e.g., GPT-5, GPT-5-mini, and GPT-5-nano) and with various parameter settings, including high, medium, low, and minimal. Below, we explore the differences between these model versions by gathering their benchmark performance and the costs to run the benchmarks. Price vs.
AI Agents: Operator vs Browser Use vs Project Mariner
AI agents are increasingly marketed as end-to-end digital workers, but real-world performance can vary widely depending on the task, tools, and execution environment. To understand what these systems can genuinely deliver today, we conducted hands-on benchmarking across practical business scenarios.
Speech-to-Text Benchmark: Deepgram vs. Whisper
We benchmarked the leading speech-to-text (STT) providers, focusing specifically on healthcare applications. Our benchmark used real-world examples to assess transcription accuracy in medical contexts, where precision is crucial. Speech-to-text benchmark results Based on both word error rate (WER) and character error rate (CER) results, GPT-4o-transcribe demonstrates the highest transcription accuracy among all evaluated speech-to-text systems.
Vibe Coding: Great for MVP But Not Ready for Production
Vibe coding is a new term that has entered our lives with AI coding tools like Cursor. It means coding by only prompting. We made several benchmarks to test the vibe coding tools, and with our experience, we decided to prepare this detailed guide.
Screenshot to Code: Lovable vs v0 vs Bolt
During my 20 years as a software developer, I led many front-end teams in developing pages based on designs that were inspired by screenshots. Designs can be transferred to code using AI tools.
AI Code Review Tools Benchmark
With the increased use of AI coding tools, codebases have become more prone to vulnerabilities, which increased the need for effective code reviews.
AGI Benchmark: Can AI Generate Economic Value
AI will have its greatest impact when AI systems start to create economic value autonomously. We benchmarked whether frontier models can generate economic value. We prompted them to build a new digital application (e.g., website or mobile app) that can be monetized with a SaaS or advertising-based model.
Top 4 AI Search Engines Compared
Searching with LLMs has become a major alternative to Google search. We benchmarked the following AI search engines to see which one provides the most correct results: Benchmark results Deepseek is the leader of this benchmark, by correctly providing 57% of the data in our ground truth dataset.
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