AI
Explore practical insights, research, and benchmarks on artificial intelligence, including generative AI, large language models, RAG, governance frameworks, MLOps practices, and AI hardware. Gain an understanding of key tools, implementation strategies, and enterprise use cases shaping the AI landscape.
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Test Automation Documentation with Best Practices
Test automation is vital for ensuring the quality and reliability of applications in software testing and development. Businesses and QA teams are transitioning from manual testing to automation testing as it can: automate repetitive tasks reduce human error shorten testing cycles,1 What often goes overlooked is the role of effective documentation in maximizing the benefits…
Compare 9 Large Language Models in Healthcare
We benchmarked 9 LLMs using the MedQA dataset, a graduate-level clinical exam benchmark derived from USMLE questions. Each model answered the same multiple-choice clinical scenarios using a standardized prompt, enabling direct comparison of accuracy. We also recorded latency per question by dividing total runtime by the number of MedQA items completed. Healthcare LLMs benchmark results…
OCR Benchmark: Text Extraction / Capture Accuracy
OCR accuracy is critical for many document processing tasks, and SOTA multi-modal LLMs are now offering an alternative to OCR. We benchmarked leading OCR services in DeltOCR Bench to identify their accuracy levels in different document types: Handwriting: GPT-5 (%95) stands out as the strongest performer, closely followed by olmOCR-2-7B (%94) and Gemini 2.5 Pro…
Reranker Benchmark: Top 8 Models Compared
We benchmarked 8 reranker models on ~145k English Amazon reviews to measure how much a reranking stage improves dense retrieval. We retrieved top-100 candidates with multilingual-e5-base, reranked them with each model, and evaluated the top-10 results against 300 queries, each referencing concrete details from its source review. The best reranker lifted Hit@1 from 62.67% to…
Cloud GPU Rental Price Index
On-demand rates for the newest-generation cloud GPUs (B200, B300, MI300X, RTX 5090) roughly doubled over the past year, while mainstream cards (H100, H200, A100) held a tight band. We compile the GPU index monthly from 63 providers and 17 GPU models, covering on-demand, spot, and 1-year reserved tiers. Price trends by GPU generation The chart…
10+ AI Procurement Use Cases & Case Studies
As the benefits of artificial intelligence (AI) are appreciated by a greater audience, the number of AI use cases in different industries expand daily. AI in the procurement sector is no different. See a comprehensive overview of the AI procurement process, detailing the reasons for its adoption, various use cases, the top 5 AI procurement…
LLM Parameters: GPT-5 High, Medium, Low and Minimal
Some 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. success: Key takeaways We used…
Generative AI ERP Systems: 10 Use Cases & Benefits
Enterprise resource planning (ERP) software helps businesses integrate workflows across finance and operations. Generative AI, alongside technologies like RPA, has the potential to enhance ERP processes. What are the use cases of generative AI ERP systems? 1- Financial planning & automation The financial use of Generative AI in ERP systems can cover the automation of…
10 Risks of Generative AI & How to Mitigate Them
With industries prioritizing generative AI for innovation and automation, its potential grows. However, risks of generative AI like accuracy and ethical concerns remain. Addressing these challenges is key to ensuring AI benefits humanity. Explore the top 10 risks of generative AI and steps to mitigate them: Model reliability & output integrity risks 1. Accuracy risks…
Generative AI in Retail: 7 Use Cases & Examples
Retail businesses strive to enhance customer experiences and loyalty. This requires producing attractive content in various formats, effective marketing efforts, and exceptional customer service. With generative AI, retailers can address most of these issues through automation, particularly by enhancing their ability to analyze customer data to deliver more personalized experiences. See the examples and benefits…