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13 IT resolutions for 2024

CIO Business Intelligence

CIOs are readying for another demanding year, anticipating that artificial intelligence, economic uncertainty, business demands, and expectations for ever-increasing levels of speed will all be in play for 2024. Here’s what they list as their 2024 resolutions. He sees 2024 as the year to have good answers.

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8 pressing needs for CIOs in 2024

CIO Business Intelligence

“The most pressing responsibilities for CIOs in 2024 will include security, cost containment, and cultivating a data-first mindset.” Here, we detail those and others that comprise eight of the top priorities for CIOs in 2024. Among the various strategies at our disposal, automation stands out as a pivotal solution,” she says. “In

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3 key digital transformation priorities for 2024

CIO Business Intelligence

Meanwhile, CIOs must still reduce technical debt, modernize applications, and get cloud costs under control. Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model.

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The path to socially responsible AI

CIO Business Intelligence

People across industries envisioned AI as being the fuel for thousands of hours of time saved, replacing jobs to reduce costs, and unlocking innovation at a scale we have never before seen. It is by combining data, human experience, and community that we are able to support developer needs.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

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Amazon OpenSearch Service search enhancements: 2023 roundup

AWS Big Data

Traditional lexical search, based on term frequency models like BM25, is widely used and effective for many search applications. Semantic search In semantic search, the search engine uses an ML model to encode text or other media (such as images and videos) from the source documents as a dense vector in a high-dimensional vector space.