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.
Top 15 Open Source AI Platforms & Libraries
Deploying your own AI model or, in some cases, fine-tuning pre-existing models comes with several challenges: Open-source platforms that offer unified APIs help address these challenges by enabling multi-cloud deployment and optimizing GPU resource management.
7 Useful AI Transformation Strategies in 2026
AI transformation is the next phase of digital transformation. Businesses are willing to invest in AI technologies to stay ahead of competitors. Digital transformation is a prerequisite for companies to initiate their AI transformation, as digital data is essential for AI training, and digital processes are typically required to deploy AI solutions.
Vision Language Models Compared to Image Recognition
Can advanced Vision Language Models (VLMs) replace traditional image recognition models? To find out, we benchmarked 16 leading models across three paradigms: traditional CNNs (ResNet, EfficientNet), VLMs ( such as GPT-4.1, Gemini 2.5), and Cloud APIs (AWS, Google, Azure).
LLM Inference Engines: vLLM vs LMDeploy vs SGLang
We benchmarked 3 leading LLM inference engines on NVIDIA H100: vLLM, LMDeploy, and SGLang. Each engine processed identical workloads: 1,000 ShareGPT prompts using Llama 3.1 8B-Instruct to isolate the true performance impact of their architectural choices and optimization strategies.
AI Adoption in Manufacturing: Insights from 100 Companies
Our analysis of the top 100 manufacturing companies by revenue from the Forbes Global 2000, spanning automotive, industrial equipment, chemicals, consumer electronics, and more across 15 countries, reveals two clear patterns in how manufacturers approach artificial intelligence. We evaluated three key metrics across all 100 companies: AI partnerships, open-source contributions, and AI initiative outputs.
Enterprise AI Company Landscape Breakdown in 2026
Artificial intelligence is revolutionizing every industry with various use cases. Demand for AI products grows as more companies shift their legacy systems with digital products to survive in the competitive business landscape. However, the AI vendor landscape is crowded, and most executives or decision-makers have limited knowledge of the AI landscape.