The ever-growing presence of technology in our daily lives has sparked discussions among many about how it affects the environment. Being able to measure, control, and ultimately reduce the carbon footprint of your product or service is not only a responsible stance to take, it can actually bring tangible benefits to the business. Quantifying ML […]
The Environmental Impact of ML Inference Read More »
A fundamental barrier the Healthcare industry faces in adoption of Machine Learning is a lack of trust and compliance for artificial intelligence solutions (AI). Increased calls for regulation, demonstrated by the FDA’s most recent guidance, pose a moral dilemma for healthcare providers trying to serve their patients. Explainable AI (XAI) in healthcare can help build
Using Explainable AI (XAI) for Compliance and Trust in the Healthcare Industry Read More »
Multi-model serving (MMS) is cutting-edge functionality with massive potential to enable a team to scale the deployment of models on a small infrastructure footprint by intelligently scheduling models to shared servers. This is made even more effective by activating “Overcommit” allowing servers to handle more models than can fit in memory. This is done by keeping
What is Multi-Model Serving and How Does it Transform your ML Infrastructure? Read More »
Production machine learning deployment is increasingly multi-faceted. Mission-critical systems often demand redundancy, high throughput or low latency, all of which can mean deploying a model multiple times across many pieces of hardware. A traditional machine learning container-based usage count does not map well to the number of inference services being run. It also creates a
How Seldon Helps You Understand Your Deployed Model Usage Read More »
How can financial services teams scale AI/ML in a manner that promotes confidence, increased automation and financial returns? And what does AI in finance look like? The level of maturity and the speed of adoption varies across different territories globally. This is largely due to different talent pools, operating models and regulation that Financial Services organizations
How Can the Financial Services Industry Trust AI? Read More »
The oil, gas, and energy sector is a crucial part of the global economy, representing 3.2% of the world’s GDP as of 2021. With the industry coming under ever-greater scrutiny over its environmental and emissions footprint, companies throughout the space are increasingly committing themselves to improving their productivity and cutting down on waste. To help
MLOps in Oil, Gas, and Energy Read More »
Only 22% of AI professionals are women. Artificial intelligence (AI) and machine learning (ML) are fields that have traditionally been male-dominated, but that’s starting to change. Today, there are many talented and successful women leaders in AI and ML who are making a significant impact on the industry and are inspiring others to follow in
7 Women Leaders in AI/ML to Follow Read More »
The year in review As we reach the end of 2022 I’d like to take the time to reflect on what has been a momentous 12 months for Seldon and the ML and AI world. It is fantastic to mark the end of the year with a whole range of new product releases, notably Seldon
A Product-Centric Year in Review at Seldon Read More »
Continuous research is something that we strongly believe in at Seldon. There has been a huge increase in the publication of new research in the field of machine learning and MLOps. Seldon’s research partnership with the University of Cambridge has played a significant role in shaping our vision for the future of MLOps and in
Seldon presents research at NeurIPS @ Cambridge Read More »
MLOps is an exciting and relatively new concept in the world of AI. MLOps, or Machine Learning Operations, is a methodology that details how to effectively develop, deploy, and monitor models in a structured and segmented manner. In real-world ML applications, the emphasis is on the smooth development of models, and on their scalability. Having
What is MLOps going to do for you? Read More »
