Fast Track Your AI Projects: NVIDIA Reference Architectures
Building the infrastructure for AI in your company can be a true challenge. Juggling intricate models, massive amounts of data, and your entire research team can feel overwhelming.
MDCS AI Solutions
Building the infrastructure for AI in your company can be a true challenge. Juggling intricate models, massive amounts of data, and your entire research team can feel overwhelming.
AI requires a whole new level of networking capabilities. Below, we’ll explore where Traditional IT and AI networking differ. These are key shifts needed to embrace the AI era: speed, latency, and predictability.
If we don’t do it right, then infrastructure will hold us back. The data storage management world is undergoing a huge transformative shift. And AI (artificial intelligence) is the biggest reason. Every day, we see AI, and work with AI. The truth is, most of us have been working with AI and not ever realizing it’s there. All this demand for AI begs a paradigm shift in how we handle and utilize the vast amounts of data.
Expert Insights by Seyed-Ahmad Ahmadi – Senior Solution Architect for Deep Learning in Healthcare at NVIDIA. Get an exclusive walkthrough of cutting-edge Genomics, Drug Discovery, Biomedical Imaging, Medical Devices, and Natural Language Processing applications.
In the ever-evolving landscape of technology, IT and AI infrastructures are essential architectural foundations of our digital world. Together, they shape a unified and intelligent digital ecosystem, setting the stage for the transformative possibilities of the future.
Maybe you’ve heard the old African proverb, “it takes a village to raise a child.” The idea is that, raising a child is a group effort with the whole “village” contributing to raising the kid. We might say something similar can be said about AI (or DL or ML).
When the time is right, you’re there to make that solid decision capturing exactly what you need. No, you don’t know exactly when it will happen, but you wait and watch – ready. It starts from the idea and goes all the way down to the very core of the AI infrastructure.
Gartner predicts only 15% of AI solutions deployed in 2022 will be successful. 15%! That’s horrendous. And yet, you know that for your organization integrating artificial intelligence (AI) into your business operations has become imperative. Covid19, remote workplaces, and AI apps like ChatGPT have only further accelerated what was already in high demand. But, before you go jumping into the latest AI tech and software for your company you don’t want to end up like the 85% that could deploy their solutions successfully.
De opkomst van taal gerelateerde apps (zoals ChatGPT) heeft voor heel wat opschudding gezorgd in verschillende sectoren. Als je als organisatie een concurrentievoordeel wil behalen, dan zul je gebruik willen maken van dergelijke tools. Taalmodellen (LLM’s), zoals Grammarly, ChatGPT en Otter.ai, zijn zowel handig als intrigerend. Dergelijke tools zorgen voor gestroomlijnde activiteiten, stimuleren productiviteit en inspireren creativiteit. Het is echter belangrijk om deze modellen voorzichtig te benaderen.