AI
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. However, businesses need to work with specialized AI systems trained on private data for increased effectiveness.
8 Vic.AI Alternatives to Automate Accounting in 2025
With the advancement of machine learning / AI and cloud SaaS, accountants have access to a range of tools that can automate finance processes.
Data Quality in AI: Challenges, Importance & Best Practices
Poor data quality hinders the successful deployment of AI and ML projects. Even the most advanced AI algorithms can yield flawed results if the underlying data is of low quality. We explain the importance of data quality in AI, the challenges organizations encounter, and the best practices for ensuring high-quality data.
Generative AI in Copywriting: Use Cases & Best Practices
97% of marketers believe that content writing is an essential marketing approach, and 60% of marketers report bringing in new consumers thanks to their content marketing efforts. Effective copywriting can assist a company in attracting potential customers, increasing brand awareness and driving sales. However, creating high-quality and engaging content can be time-consuming and challenging.
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.
AI in Software Testing in 2025: Benefits & Challenges
The number of software developers is expected to exceed 28 million by 2024. Additionally, just in 2021, more than 2 million mobile apps were released. To ensure that software releases perform adequately on their functionality, performance, and security, they must be tested rigorously.
Reproducible AI: Why it Matters & How to Improve it [2025]?
Reproducibility is a fundamental aspect of the scientific method, enabling researchers to replicate an experiment or study and achieve consistent results using the same methodology. This principle is equally vital in artificial intelligence (AI) and machine learning (ML) applications, where the ability to reproduce outcomes ensures the reliability and robustness of models and findings.
Top 6 Use Cases of AI in Fashion in 2025
According to McKinsey, generative AI could add up to $275 billion to operating profits in the fashion, apparel, and luxury sectors over the next 5 years.AI in fashion promises creativity and efficiency by transforming unstructured data like text, images, videos into innovative outputs like 3D designs and virtual models.
4 Techniques to Avoid AI Overfitting in 2025
AI revolutionizes every industry it hits. However, successfully developing and implementing it in a business is no walk in the park. Developing a high-performing AI model involves various challenges, which, if not managed properly, can lead to project failure.
5 AI Training Steps & Best Practices in 2025
AI enhances business efficiency, with leaders adopting pre-built solutions or developing their own. However, almost 80% of AI projects underdeliver or fail. One of the biggest challenges in developing AI systems is training the models.