Cloud Computing
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The path to putting your ML model in production
Suppose you are a Data Scientist or Machine Learning Engineer (or another role name of this kind). You took your time to analyze your dataset, clean it, and prepare it to train your model. You then prepared many model candidates using the most recent techniques and took your time to fine-tune them. After all this extensive work, you finally created a model to be proud of. You finally finished your job. Well, unfortunately, not. If your model never goes live and is actively used, delivering value
Fernando Camargo
November 24, 2020
Is it a good idea to run data centers underwater?
There are major infrastructural challenges in running large scale data centers. One is providing sufficient electric power to keep the facility running. A datacenter running tens of thousands of servers consumes roughly 10 Megawatts of power. Servers not only consume vast amounts of energy, they also generate a lot of heat. The air inside a data center will become sweltering unless you cool it down. Servers cannot function reliably in high temperatures. The cooling solution needs to be both hi
Adriano Marques
November 24, 2020
AI Infrastructure Alternatives for your Business
With cloud offerings becoming more abundant and diverse, cloud infrastructure seems to offer a much cheaper and simpler alternative to an on-premises data center. Many organizations, that need Artificial Intelligence to help with decision-making, problem-solving, etc. face a complicated decision: what is the best infrastructure deployment for AI workloads? Generally speaking, there are three possible deployment options. You can run your AI on-premises in your own datacenter, rent some space at
Adriano Marques
October 13, 2020
What Kind of AI Infrastructure is Best for my Business?
In this week's Exponential Chats, some of the team members responsible for Amalgam's development will have a chat about the various infrastructure alternatives available when it comes to training and deployment of Artificial Intelligence models. Between Cloud, Colocation, and On-Premise which one would you say is the best infrastructure for your AI needs? Come join us and participate by asking questions or giving your opinion in the live chat. - Adriano Marques is the founder and CEO of Exponen
Adriano Marques
September 30, 2020
The Eight Challenges You'll Face With On-Premise Artificial Intelligence
As glamorous as it is to have your own Artificial Intelligence Optimized On-Premise Data Center, it doesn't come easy. It is absolutelly true that if done right it boasts much better performance and much lower costs than resorting to the cloud or even using co-location to perform your processing workload when creating AI driven solutions. However, most people are not aware of what really makes an AI Optimized Data Center and end up building an expensive half-baked solution that can't perform o
Adriano Marques
September 18, 2020
Is the cloud moving to the sea?
In this week's Exponential Chats, some of the team members responsible for Amalgam's development will have a chat about Microsoft's Project codenamed Natick which was an attempt of sustainably running a Data Center underwater. After 2 years of deployment, Microsoft is claiming that their servers were up to 8 times more reliable than their counterparts on land. Is that an indication that the cloud is actually moving to the sea? Come join us and participate by asking questions or giving your opini
Adriano Marques
September 16, 2020
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