Unleashing the Potential of Large Language Models: A Blueprint for Real-Time, Enterprise-Ready Deployments

arXiv:2608.00419 · cs.LG, cs.AI, cs.CL, cs.IR · Submitted 2026-08-01 · Read on arXiv

Muhammad Faizan Raza, Shuo, Yang, Satish Mahadevan Srinivasan, Joanna F. DeFranco

Luna · Luna

cs.LG, cs.AI, cs.CL, cs.IR

Submitted: 2026-08-01

Comments: 6 pages, 1 figure. Authors' accepted version of an article published in IEEE Computer. The version of record is available at the DOI below

Journal ref: Computer, vol. 59, no. 4, pp. 195-199, April 2026

DOI: 10.1109/MC.2026.3664470

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Hallucination — 9× in this paper · explained in 4 episodes
• Continual Learning — 8× in this paper · explained in 3 episodes
• Catastrophic Forgetting — 6× in this paper · explained in 9 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• RAG — 5× in this paper · explained in 3 episodes
• Feedback Loop — 4× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Command Query Responsibility Segregation — 2× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Feedback Mechanisms — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 14 episodes
• Human-in-the-loop — 2× in this paper · explained in 4 episodes
• Transformers — 2× in this paper · explained in 2 episodes
• Accountability — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Evaluation Framework — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 8 episodes
• Generative Pretrained Transformer — 1× in this paper
• Grounding — 1× in this paper · explained in 3 episodes
• Hallucination Mitigation — 1× in this paper · explained in 2 episodes
• Harness — 1× in this paper · explained in 2 episodes
• Health Insurance Portability and Accountability Act — 1× in this paper
• In-Context Learning — 1× in this paper · explained in 7 episodes
• Incremental Updates — 1× in this paper · explained in 2 episodes
• Language Models (LLMs) — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 9 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 17 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 21 episodes
• SLO-aware Adaptive Grounding Engine — 1× in this paper
• Structured Reasoning — 1× in this paper · explained in 3 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• On the Opportunities and Risks of Foundation Models
• GPT-4 Technical Report
• PaLM: Scaling Language Modeling with Pathways
• Is Your LLM Outdated? A Deep Look at Temporal Generalization

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