ML
It’s Time To Set Industry Standards for AI
The AI hype cycle has shifted from real promise to real life. The intense complexities that accompany enterprise AI – like the data issues, sustainability and scalability, and of ...Full Article
AI Chip Makers Must Meet Customer Needs to Gain Design Wins for Success
AI Hardware Summit – With more than 80 AI accelerator chip companies battling for elusive market share around the world, it’s no longer enough for upstart AI chip makers ...Full Article
VMware, Nvidia Partner to Bring AI Capabilities to More Enterprises
VMworld 2020 -- In a move designed to make it easier for any enterprise to use and integrate deep AI capabilities in their business operations, VMware and Nvidia are ...Full Article
AI/ML in Broadband Networks: the Role of Standards
Earlier this year a new initiative to create standards for artificial intelligence (AI) and machine learning (ML) in the cable telecommunications industry was launched. The working group, which draws ...Full Article
How AI and ML Applications Will Benefit from Vector Processing
As expected, artificial intelligence (AI) and machine learning (ML) applications are already having an impact on society. Many industries that we tap into daily—such as banking, financial services and ...Full Article
Breaking Down Dark Data Barriers in Asset-Intensive Industries
The phrase “Dark Data” – referring to data that is unknown or untapped – has been bantered around technology conferences for years. Many industries are well on their way ...Full Article
Cash Prizes for COVID-19 AI Contest Testing Data Scientists’ NLP Smarts
Ten thousand dollars in prize money is available to data scientists with natural language processing expertise competing in a contest designed to help rid the world of coronavirus. Kaggle, ...Full Article
AI Is Changing Web Development
According to Accenture, 77 percent of smart devices include at least one AI feature. It is anticipated that by 2025 the global AI market will reach $60 billion. The ...Full Article
What to Ask When Implementing Machine Learning
Successfully operationalizing machine learning models in production environments can be incredibly difficult, as the industry has already seen. In fact, Gartner has predicted 85 percent of AI projects in ...Full Article
