Auto-complete BERT Chatbots 
Unite.AI
AUGUST 28, 2023
These AI agents, transcending chatbots and voice assistants, are shaping a new paradigm for both industries and our daily lives. Chatbots & Early Voice Assistants : As technology evolved, so did our interfaces. Tools like Siri, Cortana, and early chatbots simplified user-AI interaction but had limited comprehension and capability.
Marktechpost
APRIL 16, 2024
The framework is widely used in building chatbots, retrieval-augmented generation, and document summarization apps. The book covers the inner workings of LLMs and provides sample codes for working with models like GPT-4, BERT, T5, LLaMA, etc. The book covers topics like Auto-SQL, NER, RAG, Autonomous AI agents, and others.
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AssemblyAI
SEPTEMBER 18, 2023
From chatbots that provide human-like interactions to tools that can draft articles or assist in creative writing, LLMs have expanded the horizons of what's possible with AI-driven language tasks. BERT BERT stands for Bidirectional Encoder Representations from Transformers, and it's a large language model by Google.
Unite.AI
AUGUST 1, 2023
GPT-4: Prompt Engineering ChatGPT has transformed the chatbot landscape, offering human-like responses to user inputs and expanding its applications across domains – from software development and testing to business communication, and even the creation of poetry.
John Snow Labs
JUNE 27, 2023
Instead of navigating complex menus or waiting on hold, they can engage in a conversation with a chatbot powered by an LLM. In this section, we will provide an overview of two widely recognized LLMs, BERT and GPT, and introduce other notable models like T5, Pythia, Dolly, Bloom, Falcon, StarCoder, Orca, LLAMA, and Vicuna.
Unite.AI
SEPTEMBER 13, 2024
This is a crucial advancement in real-time applications such as chatbots, recommendation systems, and autonomous systems that require quick responses. Kernel Auto-tuning : TensorRT automatically selects the best kernel for each operation, optimizing inference for a given GPU. build/tensorrt_llm*.whl
AWS Machine Learning Blog
JANUARY 9, 2023
The models can be completely heterogenous, with their own independent serving stack. After these business logic steps are complete, the inputs are passed through to ML models. For example, a chatbot service or an application to process forms or analyze data from documents. ML inference options.
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