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.

Image Recognition Software

We benchmarked the default API configurations of Amazon Rekognition, Google Cloud Vision, and Microsoft Azure AI Vision on 100 images across 5 object classes, and compared their pricing and feature coverage.

Image Recognition Software

Cloud GPU Providers

We track 71 cloud GPU providers and 14 curated GPU model families spanning more than 2,500 distinct instance configurations.

Cloud GPU Providers

Vector Database For RAG

The calculator below answers both, from our benchmark of seven self-hosted vector databases run at matched recall on identical embeddings.

Vector Database For RAG

AI Hallucination Detection

We benchmarked three hallucination detection tools: Weights & Biases (W&B) Weave HallucinationFree Scorer, Arize Phoenix HallucinationEvaluator, and Comet Opik Hallucination Metric, across 100 test cases.

AI Hallucination Detection

Explore Artificial Intelligence

Tabular Models Benchmark: Performance Across 19 Datasets 2026

AI Models

Benchmark

Jul 3

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 Productivity

Open World Evaluation

Jul 2

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

Benchmark

Jul 2

Compare Multimodal AI Models on Visual Reasoning

We benchmarked 15 leading multimodal AI models on visual reasoning using 200 visual-based questions. The evaluation consisted of two tracks: 100 chart understanding questions testing data visualization interpretation, and 100 visual logic questions assessing pattern recognition and spatial reasoning. Each question was run 5 times to ensure consistent and reliable results. See our benchmark methodology…

AI Ethics

Insight

Jul 2

Bias in AI: Examples and 6 Ways to Fix it in 2026

Interest in AI is increasing as businesses witness its benefits in AI use cases. However, there are valid concerns surrounding AI technology: To see if there would be any biases that could arise from the question format, we tested the same questions in both open-ended and multiple-choice formats. We found that when open-ended questions were…

AI Models

Benchmark

Jul 2

Compare Relational Foundation Models

We benchmarked SAP-RPT-1-OSS against gradient boosting (LightGBM, CatBoost) on 17 tabular datasets spanning the semantic-numeral spectrum, small/high-semantic tables, mixed business datasets, and large low-semantic numerical datasets. Our goal is to measure where a relational LLM’s pretrained semantic priors may provide advantages over traditional tree models and where they face challenges under scale or low-semantic structure.…

LLM

Insight

Jul 2

While GANs pioneered many early generative AI applications, particularly in image synthesis and style transfer, most consumer-facing generative AI tools today rely on diffusion-based architectures or related approaches such as flow matching and diffusion transformers (DiT). However, GANs remain important in specific domains, such as super-resolution, face restoration, the generation of synthetic tabular or healthcare…

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