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CIOs are rethinking how they use public cloud services. Here’s why.

CIO

Increasingly, however, CIOs are reviewing and rationalizing those investments. The reasons include higher than expected costs, but also performance and latency issues; security, data privacy, and compliance concerns; and regional digital sovereignty regulations that affect where data can be located, transported, and processed.

Cloud 209
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When is data too clean to be useful for enterprise AI?

CIO

But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects. For many organizations, preparing their data for AI is the first time they’ve looked at data in a cross-cutting way that shows the discrepancies between systems, says Eren Yahav, co-founder and CTO of AI coding assistant Tabnine.

Data 211
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IBM and AWS Create a Path to Modernization Via Industry-Specific Solutions

CIO

The financial services industry must adhere to a different set of security requirements, from protecting Personal Identifiable Information (PII) to safeguards that meet Payment Card Industry (PCI) compliance, meant to protect credit card holder’s information. Consider the critical area of security controls, for example.

AWS 172
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Interpreting predictive models with Skater: Unboxing model opacity

O'Reilly Media - Data

There is often a need to verify the reasoning of such ML systems to hold algorithms accountable for the decisions predicted. There is also a trade off in balancing a model’s interpretability and its performance. A deep dive into model interpretation as a theoretical concept and a high-level overview of Skater.

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Getting specific with GenAI: How to fine-tune large language models for highly specialized functions

CIO

The challenge, as many businesses are now learning the hard way, is that simply applying black box, off-the-shelf LLMs, like a GPT-4, for example, will not deliver the accuracy and consistency needed for professional-grade solutions. The key to this approach is developing a solid data foundation to support the GenAI model.

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Lilly revolutionizes clinical trials with intelligent sensor cloud

CIO

Turning data into intelligence MagnolAI ingests raw and processed data from all connected devices leveraged in clinical studies — whether those are off-the-shelf wearable devices to measure heart rate, or a Lilly innovation such as its sensor used to measure defecation for inflammatory bowel disease (IBD).

Cloud 148
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The Cost of AI in Healthcare: Crucial Factors to Evaluate

Openxcell

Within seconds, an advanced system flags a critical condition, guiding the medical team toward the right treatment, saving precious time and, ultimately, a life. Beyond software development, costs stem from data infrastructure, regulatory compliance, training, and ongoing advancements. billion in 2022 and is projected to reach $187.95