Evaluate

Evaluate

Weigh the pros and cons of technologies, products and projects you are considering.

• Essential metrics for AI hardware management

  AI infrastructure requires monitoring compute, network, storage and business metrics to optimize performance, prevent bottlenecks and manage costs. Continue Reading

• AI breathes new life into IBM mainframes

  Often seen as the mammoths of IT shops well past their time, mainframes injected with AI are finding new opportunities for the massive data residing in the belly of the beast. Continue Reading

• Why multimodal AI is reshaping enterprise intelligence

  Multimodal AI can transform industries by combining text, images, video and audio to solve complex problems single-modality systems often can't address. Continue Reading

• How GenAI deployments are redefining everyday work routines

  GenAI deployments are making dramatic strides in boosting employee productivity, strategic analysis, software development cycles and customer service -- but not without risks. Continue Reading

• Is your business ready for an agentic AI team?

  The race is on to implement agentic AI teams. But can your business successfully deploy and manage them before taking this next step in enterprise automation? Continue Reading

• What Nvidia's $78B quarter tells you about enterprise AI

  Nvidia's latest earnings reveal more than impressive revenue figures. They highlight the accelerating adoption of enterprise AI and the growing pressure on infrastructure capacity.Continue Reading

• How businesses can close the AI engineering gap

  Amid growing concerns that AI is replacing jobs in several sectors, demand for AI engineers is surging as businesses employ several methods to overcome a severe skills shortage.Continue Reading

• Battle of the bots: Best GenAI chatbots for business

  Businesses are deploying multiple GenAI tools to support productivity. Success requires choosing the right tools for the right use case and keeping a close eye on the outcomes.Continue Reading

• 7 practical tips for agentic AI cost optimization

  Building an agentic AI cost-management framework requires unique considerations and details. These tips can help businesses get started.Continue Reading

• The ethics that make human-AI agent collaboration work

  Skepticism and distrust are common with new technology. Executives must develop a culture of trust with AI to ensure effective human-AI agent collaboration.Continue Reading

• The role of AI and humanics in training healthcare professionals

  The integration of AI and humanics in education is shaping the future of healthcare, with an emphasis on empathy, innovation and whole-person care.Continue Reading

• 35 AI content generators to explore in 2026

  Stay abreast of the growing selection of artificially generated media that businesses can use to produce text, images, music and code.Continue Reading

• Optimize AI models to generate more bang for your buck

  AI models must be fully optimized to align with business goals, provide valuable insights and produce positive ROI. Check out these proven, common sense model optimization methods.Continue Reading

• Global AI legislation and regulation tracker

  With AI, it's better to be proactive, not reactive. This tracker compiles the major AI legislation, laws and frameworks across the U.S., Europe, Asia and beyond.Continue Reading

• AI deployments gone wrong: The fallout and lessons learned

  AI's deployment landscape is littered with good intentions, crushed projects and unintended consequences due to misaligned business goals, mistrust in AI and weak management.Continue Reading

• How business leaders can prepare for quantum-AI integration

  AI completely changed the way we work, and quantum computing has the potential to upend our work completely. How can these technologies integrate to achieve further innovation?Continue Reading

• The operational reality of enterprise AI

  AI models are now commodities. It's enterprise challenges like security, scalability and integration are the real barriers to successful deployment.Continue Reading

• Claude vs. ChatGPT: How do they compare?

  Compare Anthropic's Claude vs. OpenAI's ChatGPT in terms of features, model options, costs, performance and privacy to decide which generative AI tool better suits your needs.Continue Reading

• How to use Perplexity AI: Tutorial, pros and cons

  AI-powered search engine Perplexity offers a conversational tone and much-needed source citations -- but it's not perfect. Learn how the tool works and how to start using it.Continue Reading

• ChatGPT vs. GPT: How are they different?

  Although the terms ChatGPT and GPT are both used to talk about generative pre-trained transformers, there are significant technical differences to consider.Continue Reading

• GANs vs. VAEs: What is the best generative AI approach?

  The use of generative AI is taking off across industries. Two popular approaches are GANs, which are used to generate multimedia, and VAEs, used more for signal analysis.Continue Reading

• Gemini vs. ChatGPT: What's the difference?

  ChatGPT took the early lead among AI-generated chatbots before Google answered with Gemini. While ChatGPT and Gemini perform similar tasks, there are differences.Continue Reading

• GPT-3.5 vs. GPT-4: Biggest differences to consider

  GPT-3.5 or GPT-4? With multiple OpenAI language models to choose from, picking the right option for your organization's needs comes down to the details.Continue Reading

• GPT-4o vs. GPT-4: How do they compare?

  OpenAI's GPT-4o promises improved multimodal capabilities and increased efficiency. Explore the differences between GPT-4o and its predecessor, GPT-4.Continue Reading

• Generative AI vs. predictive AI: Understanding the differences

  Generative AI and predictive AI vary in how they handle use cases and unstructured and structured data, respectively. Explore the benefits and limitations of each.Continue Reading

• Successful generative AI examples and tools worth noting

  Industries are using generative AI in various ways to generate new content. Learn about successful examples of this technology and notable tools in use.Continue Reading

• The future of generative AI: How will it impact the enterprise?

  Learn how generative AI will affect organizations in terms of capabilities, enterprise workflows and ethics, and how the technology will shape enterprise use cases.Continue Reading

• Generative AI landscape: Potential future trends

  Learn more about the growth of generative AI, its impact on other technologies, use cases and 10 trends that will contribute to the technology's development.Continue Reading

• Why banks need MLOps for digital transformation

  Financial institutions should look to MLOps to ease the development, deployment and management of machine learning models. MLOps is often ignored, yet banking will benefit from it.Continue Reading

• ML model optimization with ensemble learning, retraining

  Making ML models better post-deployment can be accomplished. Learn the ins and outs of two key techniques: ensemble learning and frequent model retraining.Continue Reading

• What is data science? The ultimate guide

  Data science is the process of using advanced analytics techniques and scientific principles to analyze data and extract valuable information for business decision-making, strategic planning and other uses.Continue Reading

• 3 ways to evaluate and improve machine learning models

  Training performance evaluation, prediction performance evaluation and baseline modeling can refine machine learning models. Learn how they work together to improve predictions.Continue Reading

• Wrangling data with feature discretization, standardization

  A variety of techniques help make data useful in machine learning algorithms. This article looks into two such data-wrangling techniques: discretization and standardization.Continue Reading

• Moving beyond NLP to make chatbots smarter

  Machine reasoning could help chatbots better understand context, which is crucial to understanding human emotions and formulating emotionally relevant responses.Continue Reading

• 7 popular AI use cases today

  AI use cases are cropping up in vertical markets ranging from healthcare to banking. Check out examples of how chatbots and other AI tools are changing the way business is done.Continue Reading