AI business strategies
Artificial intelligence software is changing how enterprises conduct business. Machine learning supports data-driven decisions, customer service chatbots follow up on leads, robots in manufacturing boost productivity -- the list goes on. Get advice for building and implementing AI business strategies.
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AI business strategies News
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August 19, 2022
19
Aug'22
Why you need to consider using small data to train AI models
A smaller data set makes sense for certain applications, such as intelligent document processing. It is not helpful in cases in which a large volume is needed to avoid mistakes.
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August 05, 2022
05
Aug'22
Abbyy aims intelligent document processing at business users
Since its birth three decades ago, Abbyy's trajectory has shifted from old-line OCR tech to the forefront of the fast-growing intelligent document processing sector.
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August 05, 2022
05
Aug'22
New AI ethics advisory board will deal with challenges
Created by the Institute for Experiential AI at Northeastern University, the board will help organizations without internal audit boards but will face some challenges.
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August 03, 2022
03
Aug'22
How the economic downturn is affecting the AI sector
Enterprise budget cutting is slowing AI projects. Vendors may not feel the impact now but likely won't be spared. Meanwhile, venture capitalists have cut back investments.
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The white-box model approach aims for interpretable AI
The white-box model approach to machine learning makes AI interpretable since algorithms are easy to understand. Ajay Thampi, author of 'Interpretable AI,' explains this approach. Continue Reading
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AI winter
AI winter is a quiet period for artificial intelligence research and development. Continue Reading
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How hybrid chatbots improve customer experience
Hybrid chatbots combine human intelligence with AI used in standard chatbots to improve customer experience. Learn how industries are using them to engage with customers. Continue Reading
Evaluate AI business strategies Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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How businesses can benefit from conversational AI applications
Conversational AI tools have traditionally been limited in scope, but as they become more humanlike, businesses have realized their potential and applied them to more use cases. Continue Reading
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Where does AI fit into a risk assessment strategy?
AI is a helpful way to take a different look at risk assessment and disaster recovery. AI sifts through massive amounts of risk data without the typical constraints of DR teams. Continue Reading
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GANs vs. VAEs: What is the best generative AI approach?
Generative AI is gaining steam in the tech sector. Two popular approaches are GANs, which are used more for multimedia, and VAEs, which are used more for signal analysis. Continue Reading
Manage AI business strategies
Learn to apply best practices and optimize your operations.
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AI chatbots don't need to be sentient, they just need to work
Chatbot users, vendors and ex-Google engineer Blake Lemoine discuss what is needed to make current chatbot tech more effective for customer service organizations. Continue Reading
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How AI governance and data privacy go hand in hand
Given instances where AI compromise data privacy and security, it's imperative that organizations understand both AI and data privacy can coexist in their AI governance frameworks. Continue Reading
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Real-world hyperautomation examples show AI's business value
Hyperautomation examples in the real world help businesses automate as many of their processes as possible and achieve their strategic goals. AI is instrumental in these efforts. Continue Reading
Problem Solve AI business strategies Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
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Expanding explainable AI examples key for the industry
Improving AI explainability and interpretability are keys to building consumer trust and furthering the technology's success. Continue Reading
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Combating racial bias in AI
By employing a diverse team to work on AI models, using large, diverse training sets, and keeping a sharp eye out, enterprises can root out bias in their AI models. Continue Reading
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Tackling the AI bias problem at the origin: Training data
Though data bias may seem like a back-end issue, the enterprise implications of an AI software using biased data can derail model implementation. Continue Reading