CIO
NOVEMBER 16, 2023
A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities. That question isn’t set to the LLM right away. And it’s more effective than using simple documents to provide context for LLM queries, she says.
TechCrunch
DECEMBER 14, 2023
I’ve spent much of the past year discussing generative AI and large language models with robotics experts. It’s become increasingly clear that these sorts of technologies are primed to revolutionize the way robots communicate, learn, look and are programmed.
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CIO
MARCH 18, 2024
For successful AI deployments, IT leaders not only need the latest GPU/CPU silicon, they also need artificial intelligence (AI) servers that establish a foundation. The software enables any business to accelerate AI development on large language model (LLM) pre-training, fine-tuning and inference with lower risk and faster catch-up.
CIO
APRIL 10, 2024
Inferencing has emerged as among the most exciting aspects of generative AI large language models (LLMs). A quick explainer: In AI inferencing , organizations take a LLM that is pretrained to recognize relationships in large datasets and generate new content based on input, such as text or images.
Apiumhub
MAY 15, 2024
Artificial Intelligence 101 has become a transformative force in many areas of our society, redefining our lives, jobs, and perception of the world. AI involves the use of systems or machines designed to emulate human cognitive ability, including problem-solving and learning from previous experiences.
CIO
JANUARY 24, 2024
Generative AI and large language models (LLMs) like ChatGPT are only one aspect of AI. Downsides: Not generative; model behavior can be a black box; results can be challenging to explain. Fortunately, most organizations can build on publicly available proprietary or open-source models.
CIO
APRIL 10, 2024
The company needs massive computing power with CPUs and GPUs that are optimized for AI development, says Clark, adding that Seekr looked at the infrastructure it would need to build and train its huge AI models and quickly determined that buying and maintaining the hardware would be prohibitively expensive. Clark says.
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