Search Results for "llm"
Here's Why GPT-4 Becomes 'Stupid': Unpacking Performance Degradation
The performance degradation of GPT-4, often labeled as 'stupidity', is a pressing issue in AI, highlighting the model's inability to adapt to new data and the necessity for continuous learning in AI development.
Enhancing LLM Application Safety with LangChain Templates and NVIDIA NeMo Guardrails
Learn how LangChain Templates and NVIDIA NeMo Guardrails enhance LLM application safety.
IBM Introduces Efficient LLM Benchmarking Method, Cutting Compute Costs by 99%
IBM's new benchmarking method drastically reduces costs and time for evaluating LLMs.
NVIDIA Launches Nemotron-4 340B for Synthetic Data Generation in AI Training
NVIDIA unveils Nemotron-4 340B, an open synthetic data generation pipeline optimized for large language models.
Character.AI Enhances AI Inference Efficiency, Reduces Costs by 33X
Character.AI announces significant breakthroughs in AI inference technology, reducing serving costs by 33 times since launch, making LLMs more scalable and cost-effective.
IBM Research Unveils Cost-Effective AI Inferencing with Speculative Decoding
IBM Research has developed a speculative decoding technique combined with paged attention to significantly enhance the cost performance of large language model (LLM) inferencing.
LangChain Introduces Self-Improving Evaluators for LLM-as-a-Judge
LangChain's new self-improving evaluators for LLM-as-a-Judge aim to align AI outputs with human preferences, leveraging few-shot learning and user feedback.
Ensuring Integrity: Secure LLM Tokenizers Against Potential Threats
NVIDIA's AI Red Team highlights the risks and mitigation strategies for securing LLM tokenizers to maintain application integrity and prevent exploitation.
Understanding the Role and Capabilities of AI Agents
Explore the concept of AI agents, their varying degrees of autonomy, and the importance of agentic behavior in LLM applications, according to LangChain Blog.
WordSmith Enhances Legal AI Operations with LangSmith Integration
WordSmith leverages LangSmith for prototyping, debugging, and evaluating LLM performance, enhancing operations for in-house legal teams.
NVIDIA NeMo Curator Enhances Non-English Dataset Preparation for LLM Training
NVIDIA NeMo Curator simplifies the curation of high-quality non-English datasets for LLM training, ensuring better model accuracy and reliability.
NVIDIA NeMo Enhances LLM Capabilities with Hybrid State Space Model Integration
NVIDIA NeMo introduces support for hybrid state space models, significantly enhancing the efficiency and capabilities of large language models.
