With the explosion of the machine learning tooling space, the barrier to entry has never been lower for companies looking to invest in AI initiatives. But enterprise AI in production is still immature. How are companies getting to production and scaling up with machine learning in 2021?
Trade promotions are becoming increasingly complex and harder to manage as CPG organizations struggle to respond to evolving digital channels of engagement, increasing demands from retailers, and ever-changing consumer behaviors. Here's how MLOps can help.
We are proud to announce that Iguazio has been named a sample vendor in five 2021 Gartner Hype Cycles, including the Hype Cycle for Data Science and Machine Learning, the Hype Cycle for Artificial intelligence, Analytics and Business Intelligence, Infrastructure Strategies and Hybrid Infrastructure Services, alongside industry leaders such as Google, IBM and Microsoft (who...
We just wrapped up the first-ever MLOps for Good hackathon, and we are so thrilled by the incredible response we’ve gotten from the ML community. 300 participants from all parts of the globe—From New Zealand, USA, Canada, Germany, Singapore, India, Portugal, Philippines, Malaysia, Australia, Morocco and Pakistan—joined our cause of bringing data science to production...
Six weeks ago we launched the first-ever “MLOps for Good” virtual hackathon, to foster projects with a positive social impact that bring data science to production. Read our roundup of some of these incredible projects.
The rapid progress in AI/ML has propelled the emergence of new mobility application scenarios that were unthinkable just a few years ago. What is the ideal way to process data efficiently and cost-effectively in a connected car world?
Enterprises struggle with data silos that slow innovation. By implementing analytics tools like Azure Synapse along with Iguazio's feature store, enterprises can build a single pipeline and rapidly run AI/ML.