Category: Machine Learning

On this special episode of the Futurum Tech Podcast - Interview Series, host Daniel Newman is joined by Logan Wilt, AI data scientist and Applied AI Center of Excellence Garage Leader at DXC Technology to talk about using AI to approach problem solving and the human-machine relationship we are now encountering. addresses a growing enterprise need for AI model assurance. That said, there are both challenges and opportunities ahead for this AI startup. Model assurance is the ability to determine whether an AI application’s machine learning (ML) models remain predictively fit for their assigned tasks. This is a critical feature of any operational AI DevOps platform, which is one of the reasons caught my attention. I see both challenges and opportunities ahead for this AI startup.
Google’s latest announcement lands in a fast-moving, but still immature, quantum computing marketplace. By extending the most popular open-source ML development framework, Google will almost certainly catalyze use of TensorFlow Quantum in a wide range of ML-related initiatives. The Google-developed quantum ML framework will find its way into a wide range of other solution providers’ quantum computing environments. So what will Google’s likely next move be in the Quantum ML space? Read on to see what I think.
It is apparent that NVIDIA recognizes its current market-leading status in AI chipsets won’t necessary last forever. By focusing on the enterprise stack—the data center, enterprise computing, and all things related to the future of AI in the enterprise, the company plots a path forward that allows it to sustain its impressive growth record. The company’s acquisition of SwiftStack provides NVIDIA with a software-driven data storage and management platform for acceleration of deep learning, analytics, and high-performance computing applications across multiclouds.
Algorithmia integrates AI model governance with GitOps, integrating ML and code development into DevOps workflows that use Git as a source-code repository. With this announcement, Algorithmia has made it easier to use GitHub to break down the silos that traditionally have kept ML developers and application coders from integrating tightly within today’s continuous DevOps workflows.
Could data analytics be poised for a new change? Prescriptive analytics is here to shake up what we know about data and AI.
MarTech has changed the game for both B2B and B2C marketers. Read how marketers are using AI and machine learning to reach and engage customers.