Welcome to Utilizing Tech, the podcast about emerging technology from Tech Field Day, part of The Futurum Group. Season 7 is presented by Solidigm and focuses on the question of AI Data Infrastructure and how that infrastructure is important for the future of artificial intelligence. Season 7: AI Data Infrastructure presented by Solidigm Season 6: Utilizing AI Season 5: Utilizing Edge Computing Season 4: Utilizing CXL Season 1-3: Utilizing AI
143 episodes transcribedAI is everywhere these days, powering applications from the enterprise to industrial, medical, education, and mobility. In this episode, David Klee jo...
MLOps is similar to DevOps but focused on ML, and focuses on improving quality of delivery for artificial intelligence applications. In this episode,...
Developers of AI applications face many obstacles, but the chief challenge is simply that these are different from traditional software development pr...
Microsoft plays a large role in enterprise IT applications, from the desktop to the datacenter to the Azure cloud, and the company is active in the wo...
You might think that 5G and AI are completely unrelated, but these new technologies support each other. Both are expressions of information theory, an...
Machine learning models have grown tremendously in recent years, with some having hundreds of billions of data points, and we wonder how big they can...
AI processing is appearing everywhere, running on just about any kind of infrastructure, from the cloud to the edge to end-user devices. Although we m...
Development of autonomous vehicles is an excellent example of machine learning applied to industrial IoT. In this episode, Alexander Noack of b-plus a...
We are on the cusp of a totally new architecture for enterprise IT, and this change toward composability is being driven by applications like AI. Inst...
Industrial cameras and sensors are generating more data than ever, and companies are increasingly moving machine learning to the edge to meet it. This...
AI applications typically require massive volumes of data and multiple devices within the datacenter. Nvidia acquired Mellanox to bring them industry-...
Training and optimizing a machine learning model takes a lot of compute resources, but what if we used ML to optimize ML? Luis Ceze created Apache Ten...
AI applications have large data volumes with lots of clients and conventional storage systems aren’t a good fit. In this episode, James Coomer from DD...
AI and analytics needs access to massive volumes of data, but we are constantly reminded of the importance of securing data. How can data be protected...
Most organizations have a vast amount of so-called unstructured data, and this poses a major risk for operations. But what if there was an AI-powered...
Big data really wasn't all that big until modern analytics and machine learning applications appeared, but now storage solutions have to scale capacit...
When it comes to AI, it's garbage in, garbage out: A model is only as good as the data used. In this episode of Utilizing AI, Ayodele Odubela joins Ch...
Biases can creep into any data set, and these can cause trouble when this data is used to train an AI model. Alf Rehn, Professor of Innovation, Design...
Productive use of AI requires the application of existing models to new applications through a process called transfer learning. In this episode, High...
BrainChip is developing a novel ultra low power “neuromorphic” AI processor that can be embedded in literally any electronic device, rather than centr...
