Snorkel AI

MAY 25, 2023

BERT, the first breakout large language model In 2019, a team of researchers at Goole introduced BERT (which stands for bidirectional encoder representations from transformers). By making BERT bidirectional, it allowed the inputs and outputs to take each others’ context into account. BERT), or consist of both (e.g.,

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

Topbots

OCTOBER 4, 2023

Here are a few examples across various domains: Natural Language Processing (NLP) : Predictive NLP models can categorize text into predefined classes (e.g., Masking in BERT architecture ( illustration by Misha Laskin ) Another common type of generative AI model are diffusion models for image and video generation and editing.

Generative AI 119

Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 119

NVIDIA Developer

JUNE 2, 2021

And when designed correctly, developers can use these techniques to build powerful NLP applications that provide natural and seamless human-computer interactions within chatbots, AI voice agents, and more.

Natural Language Processing 40

Natural Language Processing Neural Network Deep Learning BERT 40

Viso.ai

JULY 9, 2024

But, there are open source models like German-BERT that are already trained on huge data corpora, with many parameters. Through transfer learning, representation learning of German-BERT is utilized and additional subtitle data is provided. Some common free-to-use pre-trained models include BERT, ResNet , YOLO etc.

Neural Network 52

Neural Network BERT Deep Learning Computer Vision 52

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Bank agents may also struggle to track the status of complaints and ensure that they are resolved in a timely manner. Assigning complaints to staff.

Large Language Models 52

Large Language Models Natural Language Processing LLM AI 52

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Bank agents may also struggle to track the status of complaints and ensure that they are resolved in a timely manner. Assigning complaints to staff.

Large Language Models 52

Large Language Models Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Bank agents may also struggle to track the status of complaints and ensure that they are resolved in a timely manner. Assigning complaints to staff.

Large Language Models 52

Large Language Models Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Snorkel AI

AUGUST 24, 2023

AI is accelerating complaint resolution for banks AI can help banks automate many of the tasks involved in complaint handling, such as: Identifying, categorizing, and prioritizing complaints. Bank agents may also struggle to track the status of complaints and ensure that they are resolved in a timely manner. Assigning complaints to staff.

Large Language Models 52

Large Language Models Natural Language Processing Artificial Intelligence Artificial Intelligence 52

NVIDIA Developer

MAY 20, 2021

And when designed correctly, developers can use these techniques to build powerful NLP applications that provide natural and seamless human-computer interactions within chatbots, AI voice agents, and more.

Natural Language Processing 40

Natural Language Processing Deep Learning Neural Network NLP 40

Topbots

JULY 6, 2023

Like other large language models, including BERT and GPT-3, LaMDA is trained on terabytes of text data to learn how words relate to one another and then predict what words are likely to come next. GPT-4 lists the following: Natural language understanding and generation for chatbots and virtual assistants. How is the problem approached?

LLM 52

LLM Large Language Models Natural Language Processing NLP 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Parallel computing Parallel computing refers to carrying out multiple processes simultaneously, and can be categorized according to the granularity at which parallelism is supported by the hardware. For this post, we remain focused on PBA applicability and look at two of these topics: chatbots and time series prediction.

ML 96

ML Deep Learning Algorithm Large Language Models 96

Dlabs.ai

NOVEMBER 2, 2023

It’s fine-tuned specifically for generating conversational responses, making it ideal for tasks like creating chatbots or virtual assistants. BERT), GPT is a generative model. ChatGPT, on the other hand, is a specialized app built using the GPT model for conversational interactions. But why settle on GPT? Step 5: LLM customization 5.1.

ChatGPT 52

ChatGPT LLM Artificial Intelligence Artificial Intelligence 52

Unite.AI

SEPTEMBER 20, 2023

To install and import the library, use the following commands: pip install -q transformers from transformers import pipeline Having done that, you can execute NLP tasks starting with sentiment analysis, which categorizes text into positive or negative sentiments. We choose a BERT model fine-tuned on the SQuAD dataset.

LLM 342

LLM NLP BERT Python 342

Unite.AI

AUGUST 8, 2023

These advances have fueled applications in document creation, chatbot dialogue systems, and even synthetic music composition. Information Retrieval: Using LLMs, such as BERT or GPT, as part of larger architectures to develop systems that can fetch and categorize information. Recent Big-Tech decisions underscore its significance.

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243

AWS Machine Learning Blog

NOVEMBER 1, 2023

Key strengths of VLP include the effective utilization of pre-trained VLMs and LLMs, enabling zero-shot or few-shot predictions without necessitating task-specific modifications, and categorizing images from a broad spectrum through casual multi-round dialogues. This model achieves a 91.3%

Auto-classification 115

Auto-classification LLM Auto-complete Generative AI 115

Marktechpost

JANUARY 11, 2025

Some well-known examples include OpenAIs GPT (Generative Pre-trained Transformer) and Googles BERT (Bidirectional Encoder Representations from Transformers). Types of Large Language Models Large Language Models can be categorized based on their architecture, training objectives, and use cases.

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Large Language Models BERT Neural Network Artificial Intelligence 94