AI News That You Probably Missed 

The tech landscape looks more and more like a strategic game of RISK.

We’re seeing inevitable price dips, cost-effective models and a marathon to see who can achieve global domination the quickest.

Let’s take a look at some of the big moves and AI news in this ever-expanding world.

Nvidia Expands AI Management with Run:ai Acquisition

In a significant move to enhance AI computing resource management, Nvidia has announced its plan to acquire the startup Run:ai. 

This company, known for its Kubernetes-based orchestration software, will enable Nvidia to optimise AI workload management across diverse environments – from cloud to hybrid systems. 

This acquisition reflects Nvidia’s commitment to addressing the growing complexity of AI deployments and takes support from their collaboration with Amazon Web Services to push forward in generative AI technology. Nvidia’s strategy also includes investments in smaller AI firms, strengthening its influence across the AI landscape.

Omri Geller, co-founder and CEO of Run:ai, mentions that “Run:ai has been a close collaborator with Nvidia since 2020 and we share a passion for helping our customers make the most of their infrastructure. We’re thrilled to join Nvidia and look forward to continuing our journey together.”

Generative AI Costs on the Downward Slope

The cost trajectory of generative AI services looks to mirror the historical trend of falling ICT prices

Thanks to advancements in semiconductor manufacturing and economies of scale, the future promises more affordable AI solutions. 

“Because microchips are an important cost component of AI models, we expect the replacement cost of the existing infrastructure needed to run AI models to come down over time as well,” says Jan Frederik Slijkerman, Sector Strategist at ING.

OpenAI’s GPT-4 Turbo, for instance, has already debuted at significantly reduced prices, hinting at cheaper AI services on the horizon. 

Despite the continuous development of new and more complex models, the industry expects a general downtrend in prices. Which makes AI more accessible across various sectors.

Microsoft Advocates for Smaller, More Affordable Systems

In response to the escalating costs and scale of generative AI systems, Microsoft is pivoting towards smaller, cost-effective AI models with its new Phi-3 technology family. 

According to the NYTimes, “Tech companies are starting to embrace smaller A.I. technologies that are not as powerful but cost a lot less. And for many customers, that may be a good trade-off.”

These models promise nearly the same capabilities as the larger systems. But at a fraction of the cost and computational needs. This strategic shift aims to make AI technologies accessible to a broader range of applications, balancing performance with affordability. 

With Microsoft recently introducing three smaller A.I. models that are part of the Phi-3 family, they revealed that the smallest of the three already performed almost as well as GPT-3.5.

Microsoft’s initiative could redefine AI deployment, focusing on practical, economical solutions for everyday tasks.

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