Artificial Intelligence
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.
Explore Artificial Intelligence
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…
LLM VRAM Calculator for Self-Hosting
Self-hosting an LLM means running inference on hardware the operator controls rather than via a third-party API, which changes the cost, data control, and privacy profile. Whether a model runs at all depends on memory. The calculator estimates the VRAM or unified memory a model needs to run locally, based on the model, its precision,…
Intelligence Density of 71 LLMs: Smarter and Denser Models
We tracked 71 LLMs released between February 2023 and May 2026 and collected 10 public benchmarks to measure intelligence density. We divided the capability score by the resource the model consumes (active parameters, training compute, and inference price). To calculate intelligence density, we executed the following steps: See methodology for the scoring approach, and per-resource…
Tabular Models Benchmark: Performance Across 19 Datasets 2026
We benchmarked 8 tabular learning models on 19 real-world datasets covering roughly 260,000 samples, with dataset sizes from 435 to 48,800 rows. Every model ran on the same machine with 5-fold cross-validation and identical splits. Each dataset is a round-robin of head-to-head matches between models, decided by the primary metric. Elo aggregates all 483 matches…
AI Web Browsers: Selection Guide in 2026
We tested 10 AI-powered browsers by running identical tasks across each platform: webpage summarization, multi-site research, form automation, and cross-tab workflows. We documented which features worked as advertised and which failed during actual use. A comparison of 10 browsers tested across 4 categories, updates on product launches, and concrete examples of what each browser can…
LLM Market Share: Compare Usage & Adoption
We analyzed LLM market share by combining usage-based data and web visit estimates to show how demand for large language models is distributed across AI labs and AI applications: Read the methodology to see how we measured and calculated these results. The United States dominated web visits across all four months, consistently accounting for 85.5–90.5%.…
Top 10 Voice Recognition Tool & Applications
If you’ve used virtual assistants like Alexa, Cortana, or Siri, you’re likely familiar with speech recognition and conversational AI. This technology enables users to interact with devices through verbal commands by converting spoken queries into machine-readable text. Explore the top 10 uses of voice recognition technology in voice search, customer service, healthcare, and other areas.…
No-Code AI: Benefits, Industries & Key Differences
No-code AI tools allow users to build, train, or deploy AI applications without writing code. These platforms typically rely on drag-and-drop interfaces, natural language prompts, guided setup wizards, or visual workflow builders. This approach lowers the barrier to entry and makes AI development accessible to users without a programming background. Recently, no-code AI has expanded…
RAG Evaluation Tools: Weights & Biases vs Ragas vs DeepEval
When a RAG pipeline retrieves the wrong context, the LLM confidently generates the wrong answer. Context relevance scorers are the primary defense. We benchmarked five tools across 1,460 questions and 14,600+ scored contexts under identical conditions: same judge model (GPT-4o), default configurations, and no custom prompts. Under standard conditions, WandB, TruLens, and Ragas emerged as…
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. 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. Deepgram Nova-v3 and…