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Given the enormous hype around generative AI over the last few months, there are whispers that we might have already experienced the zenith of people’s fascination for the technology – for the time being, at least.

We’ve seen replications of gen AI’s hype-cycle before. There was a time when data scientists wanted to implement machine learning as a solution to problems that could be solved with more traditional methods.

Businesses spent a fortune to not be last in the race to build sophisticated data science teams, with many learning the hard way that just because you can, doesn’t mean you should. Ignoring the proper foundations for your data (engineering, quality, management, governance), and diving in headfirst, proved to be a costly mistake.

Even though the value of finding simple solutions to simple problems has been realized, machine learning has proved to be a very popular and invaluable tool in the right circumstances.

In a recent post, Dom Conte, Chief Product Officer for Avail, shared his thoughts that “a cautious approach [to AI/LLM tools] doesn’t align with the rapid pace of development we’re seeing with these models.”

I agree with Dom. Just because the hype seems to dwindle slightly with gen AI, doesn’t mean it’s time to take your foot off the gas if you can do things the right way.

However, the hype is still very much alive for the big players as we’re seeing investment in technologies necessary for gen AI skyrocket.

Walmart is rolling out a new gen AI app to 50,000 non-store employees to help with everyday tasks. This is a great example of how big businesses are raising the demand for GPUs that are needed to train large language models (LLMs).

Nvidia is currently leading the charge when it comes to GPUs and Google are making sure that they’re first in line. By partnering with Nvidia, Google has ensured that Google Cloud customers have the best access to technology powered by Nvidia’s GPUs. As a result, Google are quickly shaping up to be the preferred to platform for working with generative AI models.

In recent weeks, Zoom has established itself as another household name gunning for gen AI. After announcing that they’re upgrading their AI assistant, Zoom faced backlash over fears of customer privacy if the AI would use customer video and audio – Zoom have said this isn’t the case. As is the case for most AI implementations, people begin to speculate around privacy issues as we’re in the very early stages of formulating any sort of regulation.

With large tech companies paving the way, the creation of gen AI specific regulations should be accelerated and general creases with the technology will be ironed out. Gen AI adoption is becoming a more realistic prospect for data and analytics teams globally.

Orbition are working closely with AI/LLM professionals on a daily basis – if you’re looking to invest in a team that can take your capabilities to the next level, reach me at

About the Author

Ethan Simpkin

Talent Consultant

Ethan is a highly skilled consultant with us here at Orbition, specializing in data and analytics.

With a passion for technology and a natural talent for identifying top talent, he has become a valuable asset to both clients and candidates in the industry.Read more.

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