One Simple Graphic: companies that offer deep neural network accelerators

In 2018, I sat down and listed companies (mainly based in the US and China) that were offering specialized hardware for deep learning. There were plenty of startups in the hardware space at that time but things have changed and that particular list is a bit outdated. Many companies have pivoted, or gone bust, orContinue reading “One Simple Graphic: companies that offer deep neural network accelerators”

Gradient Flow #17: RL for Recommenders, AI Assurance, Traffic Prediction

Subscribe • Previous Issues This edition has 880 words which will take you about 5 minutes to read. “Juggling is sometimes called the art of controlling patterns, controlling patterns in time and space.”  – Ron Graham Data Exchange podcast What is AI Assurance?  Ofer Razon and Superwise are part of a community in the early stages ofContinue reading “Gradient Flow #17: RL for Recommenders, AI Assurance, Traffic Prediction”

One Simple Chart: what technologies are most important to large banks

As someone who speaks with many technology startups in the software space, I know how important the financial services sector can be to software companies. Companies in this sector have significant technology budgets and increasing competition from fintech startups has accelerated their adoption of new technologies. More financial companies are using cloud platforms and machineContinue reading “One Simple Chart: what technologies are most important to large banks”

One Simple Chart: how open source projects interact with users

Core members of an open source projects make an effort to interact with users through a variety of means. They give talks at local events (now moved online), they answer questions online, and they resolve issues identified by users (using tools like GitHub). As far as answering questions from users, over the past couple ofContinue reading “One Simple Chart: how open source projects interact with users”

Issue #16: Conversational Assistants, Model Compression, Cloud Native

Subscribe • Previous Issues This edition has 800 words which will take you about 4 minutes to read. “You may not get rich by using all the available information, but you surely will become poor if you don’t.”  – Jack Treynor Data Exchange podcast Best practices for building conversational AI applications   Alan Nichol is co-founder andContinue reading “Issue #16: Conversational Assistants, Model Compression, Cloud Native”

One Simple Chart: the number of cloud native developers worldwide

I recently came across a developer survey (The State of Cloud Native Development) from the Cloud Native Computing Foundation (CNCF) and /Data, focused on estimating the number of cloud native developers worldwide. CNCF defines cloud native technologies as follows: Cloud native technologies empower organizations to build and run scalable applications in modern, dynamic environments such as public,Continue reading “One Simple Chart: the number of cloud native developers worldwide”

One Simple Chart: where do consumers prefer AI data be processed

With machine learning and AI being embedded in a growing number of products and systems, privacy and security become central for users and companies. Every company now has a Privacy Policy to comply with regulations like GDPR and CCPA. And in the not-so-distant future, companies will have teams focused on managing risks stemming from dataContinue reading “One Simple Chart: where do consumers prefer AI data be processed”

Issue #15: Technology Adoption, Bias in Speech, Fizz Buzz

Subscribe • Previous Issues This edition has 710 words which will take you about 4 minutes to read. “Most people who have the data are in power. And most people who are powerless do not have data.” – Cathy O’Neil Data Exchange podcast From Python beginner to seasoned software engineer   Renowned programmer and author, Joel Grus,Continue reading “Issue #15: Technology Adoption, Bias in Speech, Fizz Buzz”

One Simple Chart: which sectors are using reinforcement learning

Interest in reinforcement learning has grown steadily over the last decade. In a recent post, I described emerging applications of RL in recommendation and personalization systems, and in business simulation and optimization. In this post, I wanted to examine which industry sectors have been mentioning reinforcement learning in their job postings. Let’s place demand forContinue reading “One Simple Chart: which sectors are using reinforcement learning”