Artificial Inteligence Systems Review Training 
CIO
JULY 24, 2024
Large language models (LLMs) are hard to beat when it comes to instantly parsing reams of publicly available data to generate responses to general knowledge queries. The key to this approach is developing a solid data foundation to support the GenAI model.
AWS Machine Learning - AI
NOVEMBER 20, 2024
Large language models (LLMs) are AI systems trained on vast amounts of text data, enabling them to understand, generate, and reason with natural language in highly capable and flexible ways. The FP8 data type has emerged as a game changer in LLM training. 8 38200 4.9751 6.156 41800 -3.98
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CIO
MARCH 5, 2024
India’s Ministry of Electronics and Information Technology (MeitY) has caused consternation with its stern reminder to makers and users of large language models (LLMs) of their obligations under the country’s IT Act, after Google’s Gemini model was prompted to make derogatory remarks about Indian Prime Minister Narendra Modi.
CIO
JANUARY 9, 2024
That quote aptly describes what Dell Technologies and Intel are doing to help our enterprise customers quickly, effectively, and securely deploy generative AI and large language models (LLMs).Many That makes it impractical to train an LLM from scratch. Training GPT-3 was heralded as an engineering marvel.
Palo Alto Networks
APRIL 2, 2024
Artificial intelligence (AI) plays a crucial role in both defending against and perpetrating cyberattacks, influencing the effectiveness of security measures and the evolving nature of threats in the digital landscape. A large language model (LLM) is a state-of-the-art AI system, capable of understanding and generating human-like text.
CIO
SEPTEMBER 25, 2024
Agentic systems An agent is an AI model or software program capable of autonomous decisions or actions. Gen AI-powered agentic systems are relatively new, however, and it can be difficult for an enterprise to build their own, and it’s even more difficult to ensure safety and security of these systems.
CIO
NOVEMBER 27, 2024
Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.
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