Quantum computing is coming on fast, with potential use cases across industries. But nothing is happening at scale without a better cooling solution. One option on the table: synthetic diamonds.
Advances in supercomputing aren't just for the geeky - High Performance Computing has real world implications. Here's my take on some recent advancements, including HPC as a service, and cloud deployments.
Apple and Johnson & Johnson team up for Heartline Study app - a healthcare wearables breakthrough, or a questionable study?
Johnson & Johnson recently announced its Heartline Study app, which utilizes Apple Watches and iPhones, with the expected fanfare. But is this really an advancement in wearables? And, based on the official guidelines of clinical trials, does it qualify as a study?
Just about every vendor claims they have NLP capabilities of some kind. But not all apps tagged with the "Natural Language Processing" label are created equal.
When we talk about the limits of data science, we often revert to issues like scalability, or the lack of talent. But there's another burning question that data science projects overlook at their peril: just how important is causation?
The 2020 Precision Medicine Conference was loaded with practitioners solving real world problems with tech. Here's my review of the best sessions, and a couple low points where the tech hype overreached.
Explainability is not just a roadblock to AI adoption - it also has implications for public health and safety. This is how the tensions between transparency, accuracy and performance are coming to a head.
Are you really disrupting, or are you running in place? Weighing both sides of the disruption debate
The term "disruption" is widely used, along with "digital transformation." But are we using these terms accurately? And what does real disruption look like? A recent debate brought these issues to a head.
With the introduction of Google's Tensor Flow federated, the hype around federated machine learning is surging. But there are important questions about data privacy, performance and cost that need answering.
Digital twins are amongst the most hyped technologies in recent years. It's time for a critical look at the possibilities - and drawbacks - of digital twins for modern medicine.
AI-for-AI is gaining attention - but is the capacity for embedding AI for data productivity overlooked? Let's do a gut check on the views of industry experts.
One of AI's major stumbling blocks is explainability. But can we address AI's black box by evaluating outcomes? One example from the insurance industry pushes this debate forward.
Tech-for-good news from a data-for-good skeptic - how two Sisense customers use BI to save organs and lives
Even during the holiday season, the feel-good platitudes of the data-for-good movement can be hard to take. But real world stories of companies using BI tools to save lives? That's another matter entirely.