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
Bias in AI: Examples and 6 Ways to Fix it
The questions span gender, race/ethnicity, age, appearance, religion, socioeconomic status, sexual orientation, and disability, and each one is designed so that “cannot be determined” is the only defensible answer. Every question was run 5 times per model, for over 43,000 responses in total. Average resistance is 89.3% in multiple choice and drops to 85.5% open-ended…
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 Dilemmas with Real Life Examples
Though artificial intelligence is changing how businesses work, there are concerns about how it may influence our lives. This is both an academic/societal problem and a reputational risk for companies; no company wants to be undermined by data or AI ethics scandals that damage its reputation. Explore insights into ethical issues that arise with the…
Top 20+ Predictions from Experts on AI Job Loss
As a McKinsey consultant, I helped enterprises adopt new technologies for a decade. My quick answers: Note: The size of the plots is correlated with the size of the job loss prediction. The percentages referenced in our analysis are derived from assumptions about overall job displacement. In specific scenarios, these assumptions included potential job gains…
Generative AI Ethics: How to Manage Them
Generative AI raises important concerns about how knowledge is shared and trusted. Britannica, for instance, filed a lawsuit against Perplexity, alleging that the company illegally and knowingly copied Britannica’s human-verified content and misused its trademarks without permission.98 Explore what generative AI ethics concerns are and best practices for managing them. AI models learn patterns from…
10+ Large Language Model Examples
We have gathered open-source benchmarks to compare leading proprietary and open-source large language models. Choose your use case to find the right model. You can evaluate large language models by examining their benchmark performance and real-world latency (available by clicking each model’s name in the table), and by reviewing their pricing to assess overall efficiency…
50+ ChatGPT Use Cases with Real Life Examples
ChatGPT reached approximately 1 billion weekly active users in early 2026 roughly 10% of the world’s population.152 OpenAI surpassed $20 billion in annual revenue for 2025, confirmed by CFO Sarah Friar.153 The Anthropic Economic Index distinguishes two modes of use: augmentation, in which a human interacts with AI, and automation, in which AI completes tasks…
Large Language Models in Cybersecurity
We evaluated 7 large language models across 9 cybersecurity domains using SecBench, a large-scale and multi-format benchmark for security tasks. We tested each model on 44,823 multiple-choice questions (MCQs) and 3,087 short-answer questions (SAQs), covering data security, identity & access management, network security, vulnerability management, and cloud security. MCQs (Multiple-Choice Questions) benchmarking: SAQs (Short Answer…
Best 10 Serverless GPU Clouds & 14 Cost-Effective GPUs
Serverless GPU can provide easy-to-scale computing services for AI workloads. However, their costs can be substantial for large-scale projects. Navigate to sections based on your needs: Serverless GPU providers offer different performance levels and pricing for AI workloads. Compare the most cost-effective GPU configurations for your fine-tuning and inference needs across leading serverless platforms: You…
Benchmark of 80+ LLMs in Finance: Claude Opus 5.5 & GPT-6 Astra
The test set is the hard subset of the FinanceReasoning benchmark (Tang et al.), with 238 questions.181 Accuracy is the percentage of questions answered correctly. Numerical answers receive a 0.2% relative tolerance. Output tokens are the tokens generated across the 238 answers. Input tokens are counted separately in the cost calculation. Cost is the calculated…