Artificial Inteligence Artificial Intelligence Training 
CIO
NOVEMBER 1, 2024
The world has known the term artificial intelligence for decades. Developing AI When most people think about artificial intelligence, they likely imagine a coder hunched over their workstation developing AI models. In some cases, the data ingestion comes from cameras or recording devices connected to the model.
CIO
MARCH 11, 2025
But how do companies decide which large language model (LLM) is right for them? LLM benchmarks could be the answer. They provide a yardstick that helps user companies better evaluate and classify the major language models. LLM benchmarks are the measuring instrument of the AI world.
CIO
OCTOBER 24, 2024
Take for instance large language models (LLMs) for GenAI. While LLMs are trained on large amounts of information, they have expanded the attack surface for businesses. Artificial Intelligence: A turning point in cybersecurity The cyber risks introduced by AI, however, are more than just GenAI-based.
CIO
JANUARY 9, 2025
Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. These autoregressive models can ultimately process anything that can be easily broken down into tokens: image, video, sound and even proteins.
CIO
MARCH 11, 2025
To capitalize on the enormous potential of artificial intelligence (AI) enterprises need systems purpose-built for industry-specific workflows. The Insurance LLM is trained on 12 years worth of casualty insurance claims and medical records and is powered by EXLs domain expertise.
CIO
JANUARY 30, 2025
In particular, it is essential to map the artificial intelligence systems that are being used to see if they fall into those that are unacceptable or risky under the AI Act and to do training for staff on the ethical and safe use of AI, a requirement that will go into effect as early as February 2025.
AWS Machine Learning - AI
APRIL 9, 2025
Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements.
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