AI Foundations
AI Hallucination: Comparison of the Popular LLMs in 2025
AI models sometimes generate data that seems plausible but is incorrect or misleading; known as AI hallucinations. According to Deloitte, 77% of businesses who joined the study are concerned about AI hallucinations. We benchmarked 16 LLMs with 60 questions to each one to measure their hallucination rates: Hallucination rates Our benchmark revealed that OpenAI GPT-4.
Top 4 AI Search Engine Comparison in 2025
Searching with LLMs has become a major alternative to Google search. We benchmarked the following AI search engines to see which one provides the most correct results: Benchmark results Deepseek is the leader of this benchmark, by correctly providing 57% of the data in our ground truth dataset.
Deepseek: Features, Pricing & Accessibility in 2025
DeepSeek is a Chinese AI startup that has made significant strides in artificial intelligence, particularly with its R1 model, which has outperformed OpenAI’s O1 on multiple reasoning benchmarks. We analyzed DeepSeek’s technical advancements, benchmark performance, and strategic positioning in the AI landscape to evaluate its impact.
World Foundation Models: 10 Use Cases & Examples [2025]
Training robots and autonomous vehicles (AVs) in the physical world can be costly, time-consuming, and risky. World Foundation Models offer a scalable alternative by enabling realistic simulations of real-world environments. These models accelerate development and deployment in robotics, AVs, and other domains by reducing reliance on physical testing.
AGI Benchmark: Can AI Generate Economic Value in 2025
AI will have its greatest impact when AI systems start to create economic value autonomously. We benchmarked whether frontier models can generate economic value. We prompted them to build a new digital application (e.g. website or mobile app) that can be monetized with a SaaS or advertising-based model.
Lazarus AI: Extractive & On-Prem AI for Regulated Industries
Generating insights from unstructured data has long been a strategic aim among organizations that Lazarus AI builds foundation models (e.g. RikAI) to solve complex and urgent problems involving large amounts of unstructured private data. Lazarus is active in these industries: Government (e.g. defense), insurance (e.g. damage assessment of catastrophic events), healthcare, and banking.
10 Steps to Developing AI Systems in 2025
IBM identifies the top AI adoption challenges as concerns over data bias (45%), lack of proprietary data (42%), insufficient generative AI expertise (42%), unclear business value (42%), and data privacy risks (40%).These obstacles can hinder AI implementation, slow innovation, and reduce the return on investment for organizations adopting AI technologies.
Specialized AI Models: Vertical AI & Horizontal AI in 2025
Foundation models like ChatGPT with many capabilities (e.g. translation, text generation) trained on public data have launched the generative AI wave.
Image Recognition vs Classification: Applications with Examples
Businesses increasingly leverage AI-powered visual data solutions, but confusion between image recognition and classification leads to inefficiencies. Understanding the key differences helps businesses optimize AI deployment in the security, healthcare, and retail fields. Explore image recognition vs classification, their key differences, and applications with real-life examples.
Top 10 Strategies for AI Improvement with Real Life Examples
AI systems achieved remarkable milestones (e.g., exceeding human performance in image and speech recognition); however, AI progress is slowing down as scaling yields fewer benefits. Additionally, AI and ML models degrade over time unless they are regularly updated or retrained.This makes it critical to utilize all levers to improve AI models continually.