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Cem Dilmegani

Cem Dilmegani

Principal Analyst
706 Articles
Stay up-to-date on B2B Tech

Cem has been the principal analyst at AIMultiple for almost a decade.

Cem's work at AIMultiple has been cited by leading global publications including Business Insider, Forbes, Morning Brew, Washington Post, global firms like HPE, NGOs like World Economic Forum and supranational organizations like European Commission. [1], [2], [3], [4], [5]

Professional experience & achievements

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider. [6], [7]

Research interests

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity (including network security, application security), data collection including web data collection and process intelligence.

Cem's hands-on enterprise software experience contributes to his work. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Education

He graduated as a computer engineer from Bogazici University in 2007. During his engineering degree, he studied machine learning at a time when it was commonly called "data mining" and most neural networks had a few hidden layers.

He holds an MBA degree from Columbia Business School in 2012.

Cem is fluent in English and Turkish. He is at an advanced level in German and beginner level in French.

External publications

Conference & other event presentations

Sources

  1. Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
  2. Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
  3. Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
  4. Science, Research and Innovation Performance of the EU, European Commission.
  5. EU’s €200 billion AI investment pushes cash into data centers, but chip market remains a challenge, IT Brew.
  6. Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
  7. We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

Latest Articles from Cem

AIJul 25

Meta's New Llama 3.1 AI Model: Use Cases & Benchmark

Meta published model weights for Llama 3.1 which is one of the most advanced language models. This access enables enterprises, researchers or individual developers to finetune and deploy their own Llama-based models.

AIJun 10

ChatGPT Code Interpreter Plugin: Use Cases & Limitations

Since the release of ChatGPT, programmers and more advanced users of the tool were curious whether OpenAI will allow plugins to the chatbot. OpenAI announced the first plugins in April, followed by many others since then. At the beginning of July 2023, they announced an official ChatGPT plugin, the Code Interpreter. Figure 1.

DataSep 3

Top 3 Prolific Alternatives

Prolific is a popular AI data collection service that offers a crowdsourcing platform for AI data seekers. Our research identified some drawbacks of working with Prolific from the perspectives of its customers and workers.

DataMay 28

Applying RLHF: Techniques, use cases, and challenges

Training AI systems to align with human values can be a challenge in machine learning. To mitigate this, developers are advancing AI through reinforcement learning (RL), allowing systems to learn from their actions. A notable trend in RL is Reinforcement Learning from Human Feedback (RLHF), which combines human insights with algorithms for efficient AI training.

AISep 8

Cloud GPUs for Deep Learning: Availability& Price / Performance

If you are flexible about the GPU model, identify the most cost-effective cloud GPU based on our benchmark of 10 GPU models in image and text generation & finetuning scenarios. If you prefer a specific model (e.g. A100), identify the lowest-cost GPU cloud provider offering it.

Enterprise SoftwareJun 19

eCommerce Data Collection: Best Practices & Examples

As online shopping grows and customer expectations shift, eCommerce businesses face increasing pressure to stay competitive. Real-world data is key to making faster, smarter decisions. Failing to collect and utilize data properly can result in missed sales, inefficient operations, and poor customer retention.

AIJul 1

Top 10 Tungsten Automation (Kofax) Alternatives

With the acceleration of artificial intelligence (AI), businesses are constantly looking for tools to: Intelligent document processing (IDP) tools can do all this, and more. For this reason, the global Intelligent Document Processing (IDC) market sizeis expected to grow from USD 1.1 billion in 2022 to USD 5.

AISep 2

RPA Generative AI: Top 15 Use Cases

RPA (robotic process automation) and generative AI are two popular tools in the digital transformation landscape: These two tools are widely used because of their wide-ranging capabilities. RPA’s handling of repetitive tasks & generative AI’s automation through the creation of original content creates an opportunity for businesses to reshape their companies’ operational efficiency.

AIJun 11

Chatbot in South Africa (RSA): Top 10 Vendors

Businesses in South Africa can benefit from conversational AI. WhatsApp boasts a 96% monthly usage rate among South African internet users, and AI-related searches in Africa grew by 270% in the past year. Therefore, you should capitalize on your audience’s comfort level with conversational AI tools.

DataSep 17

Data Transformation: Challenges & Real-life examples

Data is the cornerstone in many sectors, underpinning decision-making processes in business, government, health, and more. The advent of generative AI has heightened the importance of data and its various applications. Organizations must understand and proficiently implement data transformation processes to unlock the full potential of it.