Confidential Computing and Machine Learning

Measuring the popularity and exploring the readiness of Confidential Computing tools. In order to have a comprehensive data protection and privacy policy, organizations must ensure the confidentiality and integrity of your data in these states: at rest, in use, and in transit. We previously reviewed the ecosystem of tools for protecting data while in use.Continue reading “Confidential Computing and Machine Learning”

Tech companies are gearing up for the Metaverse

Major technology companies are investing in the Metaverse. Enterprises should take early action to stay ahead of the curve. In the aughts, I was a user and proponent of earlier versions of virtual worlds (specifically of Second Life). Unfortunately, the technology was clunky and the user base never really grew beyond a few hundred thousandContinue reading “Tech companies are gearing up for the Metaverse”

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”

Distributed Computing for AI: A Status Report

An update on the central role of distributed computing in modern AI. By Ben Lorica and Kenn So. In our previous post we introduced a class of AI startups (“pegacorns”) that have at least $100 million in annual revenue. Many of the AI pegacorns sell applications rather than infrastructure, and many of their founders citedContinue reading “Distributed Computing for AI: A Status Report”

Most State-Of-The-Art AI Systems Are Trained With Extra Data

According to the 2022 AI Index Report, nine state-of-the-art AI systems out of the ten benchmarks they tested against are trained with extra data. By Ben Lorica. Stanford’s AI Index Report has just come out – one of my favorite annual reads. This report tracks several metrics including performance on machine learning benchmarks, volume ofContinue reading “Most State-Of-The-Art AI Systems Are Trained With Extra Data”

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”

Ratio of Data Scientists to Data Engineers

As companies get more proficient in using data and AI to drive decision making and operations, team members with disparate backgrounds – analysts, product mangers, decision makers – begin using data on a regular basis. But when they’re first starting out, the requisite data may not be in place, and data processing and analysis tendContinue reading “Ratio of Data Scientists to Data Engineers”

Data Remains the Key Challenge In Computer Vision Projects

Datagen recently surveyed about 300 professionals in computer vision about the value of data. The survey comes at a time of renewed focus on the importance of tools for helping ML teams address data related challenges. Data-centric AI represents a recent shift among researchers, away from focusing on models and toward the underlying data used inContinue reading “Data Remains the Key Challenge In Computer Vision Projects”