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Training is expensive (Not)!

Allen Holub

I’m often contacted by someone who says: We could really use your training (or consulting services). The first answer is that I provide some of the highest quality training and consulting available, and there are plenty of examples of my work… The post Training is expensive (Not)! Do you have any tips?

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Know before you go: 6 lessons for enterprise GenAI adoption

CIO

Lesson 1: Don’t start from scratch to train your LLM model Massive amounts of data and computational resources are needed to train an LLM. That makes it impractical to train an LLM from scratch. Training GPT-3 was heralded as an engineering marvel. Here’s a quick read about how enterprises put generative AI to work).

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Seekr finds the AI computing power it needs in Intel’s cloud

CIO

Seekr’s main business is building and training AIs that are transparent to enterprise and other users. Training a large foundation model versus inferencing on a smaller, distilled model take different types of compute.” Workloads range from high-end training to fine-tuning and inferencing across a range of models,” he says.

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Selling the C-suite on preemptive IT investments

CIO

Others include preparation for zero-day attacks, almost anything having to do with data stewardship, as well as IT training and social engineering audits. Yet without training, both IT and end-users are ill-equipped to move forward with new technologies that the company needs. The average cost of a data breach is $4.64

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How 5G is driving big innovations in healthcare for veterans

CIO

The network will also be used to create immersive, lifelike training for surgical residents. Currently, hospitals use mannequins or live actors to simulate patients, but they are expensive and require intensive planning and scheduling. For that reason, most facilities use WiFi. But WiFi was designed to transmit data, not voice calls.

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Gen AI without the risks

CIO

Developing and deploying successful AI can be an expensive process with a high risk of failure. For the average enterprise, it’s prohibitively expensive. So, does every enterprise need to build a dedicated AI development team and a supercomputer to train their own AI models? Not at all. But do be careful.

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The AI continuum

CIO

Train a model from scratch Training your own LLM is out of reach for most organizations, and it still may not be a wise investment. Training a GPT4-scale, trillion-parameter model takes billions of dollars in supercomputing hardware, months of time, and valuable data science talent. Here is some guidance.