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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

Best Design to Code Tools Compared: Detailed Analysis

AI Coding
Benchmark
Aug 21

Design-to-code tools have changed more in the past 18 months than in the decade before that. The category used to mean “export some CSS from Figma.” Now it spans full-stack app builders, bidirectional MCP integrations that write back to the canvas, and agentic platforms shipping production branches from Slack messages. The tools on this list…

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AI Ethics
Insight
Aug 20

Responsible AI: 4 Principles & Best Practices

65% of leaders feel unprepared to manage AI-related risks effectively. 7 Developing and scaling AI applications with responsibility, trustworthiness, and ethical practices in mind is essential to build AI that works for everyone. Explore four principles for responsible AI (RAI) design and recommend best practices to achieve them: AI tools are increasingly being used in…

AI
Insight
Aug 20

7 Useful AI Transformation Strategies

Before choosing how to transform AI, leaders need to know where to start. We analyzed the Anthropic Economic Index (March 2026 release)34, mapping over 1 million real-world Claude interactions across 3,260 occupational tasks to the standard APQC Process Classification Framework (PCF).35 Check out high, mid, and granular-level processes by real-world AI exposure and human verification…

Document Automation
Insight
Aug 20

State of OCR technology: Is it dead or a solved problem?

Optical Character Recognition (OCR) is one of the earliest areas of artificial intelligence research. Today, OCR technology is relatively mature and no longer called AI, which is a good example of Pulitzer Prize winner Douglas Hofstadter’s quote: AI is whatever hasn’t been done yet.43 In our OCR benchmark, DeltOCR, a large language model, correctly reads…

Chatbots
Open World Evaluation
Aug 20

Banking Chatbots: 7 Tools & Use Cases

Industries that prioritize customer service face rising costs as demand for excellent service grows. Banking chatbots let customers complete transactions by voice or text, reducing operational costs and improving customer satisfaction. We compiled the top 7 chatbots with financial literacy, including their features, comparisons, and best practices for deployment to address cost and service concerns.…

Chatbots
Insight
Aug 20

Top 10 Mortgage Chatbots: Use Cases & Examples

Banks that keep customers happy grow deposits 85% faster than competitors. Loan processing directly affects client satisfaction. 56. Chatbots can handle mortgage-related tasks around the clock, simulating what mortgage brokers typically do. We examine 10 vendors, their practical applications, and United Wholesale Mortgage’s implementation. *The table is sorted by rating score. Mortgage chatbots handle loan-related…

LLM
Insight
Aug 19

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.63 OpenAI surpassed $20 billion in annual revenue for 2025, confirmed by CFO Sarah Friar.64 The Anthropic Economic Index distinguishes two modes of use: augmentation, in which a human interacts with AI, and automation, in which AI completes tasks…

LLM
Insight
Aug 19

ChatGPT for Customer Service: Top 10 Use Cases

ChatGPT has moved from novelty to infrastructure in customer service. Companies are using it to cut response times, handle volume their teams can’t absorb, and reduce the cost of routine interactions. But results vary sharply depending on how it’s implemented. OpenAI launched GPT-5.6, a materially more capable model that is better at instruction-following, reasoning across…

LLM
Insight
Aug 18

The Future of Large Language Models

See the future of large language models by delving into promising approaches, such as self-training, fact-checking, and sparse expertise that could address LLM limitations. Success rate comparison of LLM’s Claude Sonnet 4.6 led the benchmark with an overall score of 0.748, with base and thinking variants tied to three decimal places. Claude Opus 4.8 (0.702),…

GenAI Applications
Insight
Aug 17

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…

Healthcare AI
Insight
Aug 17

25 Healthcare AI Use Cases with Examples

A recent study shows that hybrid teams of human clinicians and AI systems make more accurate medical diagnoses, largely because they tend to make different and complementary errors that help correct one another. These findings indicate strong potential of AI to enhance patient safety and promote more equitable healthcare.124 How do healthcare AI systems perform?…