Low-code Development Platforms

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”

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”

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”

Revisiting the unicorn concept

Subscribe • Previous Issues The AI $100 Million Revenue Club Everyday there’s a new unicorn. It used to be a status that meant that a startup has graduated from being a startup and into a mature company worth being listed on the public stock market backed by revenue. In today’s climate becoming a unicorn is increasingly aContinue reading “Revisiting the unicorn concept”

Supercharging Your Data and AI Platforms

Subscribe • Previous Issues Data Management Trends You Need to Know Intel Capital’s Assaf Araki and I both focus on data, analytics, and machine learning, thus we regularly hear pitches from startups building new data management solutions. Data management is a broad area that includes solutions for different workloads, data types, and use cases.  Our post listsContinue reading “Supercharging Your Data and AI Platforms”

Practical Reinforcement Learning and Differential Privacy

Subscribe • Previous Issues Ratio of Data Scientists to Data Engineers A fun topic of discussion among leaders of data teams is the ratio between the number of data scientists and data engineers. There is no ideal answer. It really depends on the tools and infrastructure you have in place, the maturity and availability of use casesContinue reading “Practical Reinforcement Learning and Differential Privacy”

Locating Machine Learning Engineers

Subscribe • Previous Issues Where Do Machine Learning Engineers Work? About five years ago we published a post that highlighted the emergence of a role focused on making data science work in production. At the time we noticed job postings (mainly in the SF Bay Area) that used the title “machine learning engineer” to describe individuals skilledContinue reading “Locating Machine Learning Engineers”

2022 Trends in Data and AI

Subscribe • Previous Issues FREE Report: Trends in Data, Machine Learning, and AI This short guide identifies trends that will be relevant to organizations across all industries and sectors over the next 12-18 months. Download What is Graph Intelligence? In a new post with Leo Meyerovich of Graphistry, we highlight the current state of Graph Intelligence, aContinue reading “2022 Trends in Data and AI”