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.
Explore AI
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 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: The United States dominates global LLM usage in web visits and brand adoption, driven by ChatGPT and Gemini, while China operates largely behind the scenes. China…
AGI/Singularity: 9,800 Predictions Analyzed
Artificial general intelligence (AGI) is when an AI system matches human cognitive abilities across all tasks. We analyzed 9,800 AI researchers‘, leading entrepreneurs‘, and community predictions about the AGI timeline: Will AGI/singularity happen? AGI is inevitable according to most AI experts. When will we reach AGI? Between late 2020s and early 2030s. AGI timeline shortened…
7 Useful AI Transformation Strategies in 2026
Before choosing how to transform AI, leaders need to know where to start. We analyzed the Anthropic Economic Index (March 2026 release)76, mapping over 1 million real-world Claude interactions across 3,260 occupational tasks to the standard APQC Process Classification Framework (PCF).103 Check out high, mid, and granular-level processes by real-world AI exposure and human verification…
AI Rollups: Funding, Investors and Industry Trends
We analyzed 30 investments involving over 130 investors from the past 3 years to understand the current trend for AI rollups. Based on our analysis, we identified investor activity and trends, including the number of investors backing AI rollups, the total funding raised for AI rollups, and the leading industries. Funding trends in AI rollups…
Compare AI Revenues Across the Stack
The AI market expanded rapidly across all four layers (data, compute, models, and applications). For example, NVIDIA’s data center revenue jumped from $47.5B to $115.2B in a single year; OpenAI reached about $13B in annual revenue; and Anthropic approached $7B in ARR. We tracked revenue data from over 100 AI companies. Explore how revenues shifted…
Benchmark of 40+ LLMs in Finance: Claude Fable 5 & GPT-5
We evaluated 40+ LLMs in finance on 238 hard questions from the FinanceReasoning benchmark to identify which models excel at complex financial reasoning tasks like statement analysis, forecasting, and ratio calculations. LLM finance benchmark overview We evaluated LLMs on 238 hard questions from the FinanceReasoning benchmark (Tang et al.).120 This subset targets the most challenging…
Handwriting Recognition Benchmark: LLMs vs OCRs
OCR tools achieve over 99% accuracy on typed text in high-quality images. However, handwriting remains challenging due to variations in style, spacing, and irregularities. We introduce a cursive handwriting benchmark with 100 handwriting samples written by our team to prevent overfitting. Cursive handwriting benchmark results In this benchmark, GPT-5, Gemini 3 Pro Preview, and olmOCR-2-7B-1025-FP8…
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…