Subscribe • Previous Issues Experiment Tracking and Experiment Management Tools There are a variety of open-source and commercial tools available to support machine learning teams during the modeling phase. Experiment tracking and experiment management tools log all relevant metadata and results, and most of these tools include collaboration and visualization features to make ML experiments easier toContinue reading “Low-code Development Platforms”
Author Archives: Ben Lorica
Experiment Tracking and Experiment Management Tools
Gauging the popularity of a new class of tools for machine learning. Individuals and teams who build machine learning models need tools to keep track of and analyze experiments they run. It can be very challenging to organize all the information needed to evaluate, identify, and reproduce specific experiments. In the course of building aContinue reading “Experiment Tracking and Experiment Management Tools”
Ranking Low-code Development Platforms
Measuring the popularity of low-code development tools and databases. Although the global economy is slowing, software developers and technical talent remain in high demand. What can companies do to broaden their technical talent pool and make their current developers productive so that they can accelerate time to market? The most common approach to upskilling is investingContinue reading “Ranking Low-code Development Platforms”
2022 Workflow Orchestration Survey Report
By Gradient Flow. The State of Orchestration Survey ran online from February 6 to April 4, 2022. A total of 581 respondents from a variety of industries participated. This survey was conducted in collaboration1 with Prefect. Modernizing an organization’s data infrastructure is increasingly difficult without an orchestrator. At a high-level, these are tools that enableContinue reading “2022 Workflow Orchestration Survey Report”
2022 Identity Management Survey Report
By Gradient Flow. The Identity Management Survey ran online in February/March 2022. Over 500 respondents from a variety of industries participated.. This survey was conducted in collaboration1 with Clear Skye. The proliferation of software services and platforms comes at a time when security threats and data breaches continue to grow. In addition, regulatory pressure andContinue reading “2022 Identity Management Survey Report”
Secure Machine Learning
Subscribe • Previous Issues Data Pegacorns With Kenn So of Shasta Ventures, we identify data startups with real market traction. We chose companies founded 2006 or after as it coincides with the initial release of Hadoop, the open-source technology platform that started the big data era. This is the second in a series of posts on pegacorns,Continue reading “Secure Machine Learning”
The Business Intelligence Index
Measuring the popularity of BI tools In a recent post on trends in machine learning, we predicted that there will be more no-code/low-code ML tools available to non-programmers. The potential market for such tools is immense given that the number of analysts dwarf the number of data scientists and data engineers. Due to improvements inContinue reading “The Business Intelligence Index”
The Data Pegacorns
Introducing the Data $100M Revenue Club By Kenn So and Ben Lorica. The global economy has deteriorated since our last post on AI pegacorns (startups that have at least $100M in annual revenue). Rather than focusing solely on valuation, there has been a rapid revalidation of the importance of revenue scale. As a continuation ofContinue reading “The Data Pegacorns”
AI Observability, Orchestration, Consolidation
Subscribe • Previous Issues Machine Learning Trends You Need to Know In a new post with Assaf Araki of Intel Capital, we collect resources and insights to help you navigate the AI landscape. We believe machine learning is a platform play and companies will use at most two platforms to manage the entire pipeline: one platform toContinue reading “AI Observability, Orchestration, Consolidation”
Large Image Datasets Today Are a Mess
Introducing a new free tool for curating image datasets at scale. By Amir Alush, Danny Bickson, Ben Lorica. TL;DR Visual data management systems are lacking in all aspects: storage, quality (deduplication, anomaly detection), search, analytics and visualization. As a consequence, companies and researchers are losing product reliability, working hours, wasted storage, compute and most importantly,Continue reading “Large Image Datasets Today Are a Mess”