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5x more spending on ML
There are two biggest trends in the MLops community and the Mlops industry that is going on right now and it’s going to keep going on in 2024. 1st, it’s MLops is taken off. And according to Deloitte survey and State of AI, almost 50% of responders are spending 4X more than last year on machine learning initiatives, and they plan to even integrate more to all enterprises in the next three years. And we can break down much learning in three basic categories. It’s computer vision, it’s natural language processing and the rest of applications. This is like where you’re it oversimplified categorization of Ml, but nevertheless it can guide you overall structure of the market. And another trend is all these machine learning companies and players have cloud machine learning solution, and all this cloud machine learning solution has sub optimal usage and configuration.
Furthermore, there’s a noticeable trend towards democratizing ML, with tools and platforms becoming more user-friendly for non-experts. This is leading to a wider adoption across various departments within organizations, not just IT or data science teams. The focus is also shifting towards more sustainable ML practices, considering the environmental impact of data centers and computing resources.
Scarcity of ML expertise
The scarcity of ML expertise has led to a reliance on external consultants and managed services, further increasing expenses. Companies are investing in training and upskilling their existing workforce to bridge this gap. Moreover, there’s a trend towards adopting MLaaS (Machine Learning as a Service) platforms which offer more cost-effective and scalable solutions compared to building in-house capabilities.
Seven figure monthly GCP/AWS billing is the new normal
So in other research, almost 25% of machine learning companies spend more than half a million dollars per month on the…