Why the Math Around Adaptive AI is Painful

Artificial Intelligence (AI) is expensive.

more agile Driving companies to lower costs while investing in digital transformations to become leaner and more profitable; I got physics. I haven’t looked too deeply into it yet. Artificial intelligence strategies are not built as a cost-effective model.

Adaptive artificial intelligence and machine learning business models to act; It combines the promise of automation and responsiveness with crisp velocity. Many organizations use this capability as a cost-effective, They consider it a rational decision to make the best. ok i feel you really

S3 buckets in Databricks and Snowflake, as flexible AI business strategies allow organizations to make more sense of their data sitting in the cloud. This is a lot of data if you count the data sitting in the DR. Rationalizing data through AI and ML is old news. Many organizations have yet to realize a solid ROI on this important investment. As flexible AI business platforms require reasonable data sets to make rational and optimal decisions; Let’s think about the opportunities available.

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Many organizations, including financial institutions, rely on traditional information security solutions; Even with experienced SecOps resources and MSSPs with extensive adaptive controls, volume attacks are being achieved. The need for true automated remediation supported by Adaptive AI is a necessary use case to address growing cyber threats.

The cornerstone of current and future web 3.0 and blockchain strategies is based on innovative contract capabilities. Smart contracts and blockchain capabilities will enable taxis, It will benefit medical record and payment automation and passport processing. Adaptive AI and machine learning are critical to this task.

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Most agree that adaptive AI will only be effective if it processes enough data. Before organizations incorporated AI, data storage; Copy and capacity will be completely resolved.

In the Splunk example; This company will charge as they should for the amount of data they have to process. Still, Many organizations only selectively send specific log files to Splunk to keep costs down. now, In the new world of blockchain and adaptive AI; Organizations need to increase their budgets to support excessive data storage for AI to work as planned.

Some organizations consider adaptive AI as a replacement for human capital. AI is self-healing; You will need to plan for optimization and self-innovation skills.

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Organizations will need qualified data scientists and analytics resources until that day. mathematics storage, By adding to cybersecurity and development resources; How will adaptive AI become a cost-marginal thing for organizations?

Like I said at the beginning, stay tuned for the math. continuous monitoring; threat detection and incident response; Similar rules will be required to combat cyber security attacks with blockchain and adaptive AI. Until the promise of adaptive AI becomes a reality, organizations should consider their cost model as ongoing operating and development costs.

adaptability Balancing the cost of cybersecurity and risk Is adaptive AI more dangerous to an organization’s financial prospects?

That’s for another time 🙂

all the best,



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