Towards AI

MARCH 12, 2025

Normalization Trade-off: GPT models preserve formatting & nuance (more token complexity); BERT aggressively cleans text simpler tokens, reduced nuance, ideal for structured tasks. Contraction handling (dont do not or kept intact based on model requirements). Tokenization directly impacts model quality & efficiency.

LLM 54

LLM BERT Neural Network Metadata 54

Unite.AI

DECEMBER 9, 2024

Models that once struggled with basic tasks now excel at solving math problems, generating code, and answering complex questions. Central to this progress is the concept of scaling laws rules that explain how AI models improve as they grow, are trained on more data, or are powered by greater computational resources.

AI Modeling 144

AI Modeling Neural Network AI AI 144

Unite.AI

AUGUST 1, 2023

OpenAI has been instrumental in developing revolutionary tools like the OpenAI Gym, designed for training reinforcement algorithms, and GPT-n models. The spotlight is also on DALL-E, an AI model that crafts images from textual inputs. Generative models like GPT-4 can produce new data based on existing inputs.

Prompt Engineering 246

Prompt Engineering Prompt Engineer ChatGPT Convolutional Neural Networks 246

AssemblyAI

JUNE 27, 2023

Deep Neural Networks (DNNs) have proven to be exceptionally adept at processing highly complicated modalities like these, so it is unsurprising that they have revolutionized the way we approach audio data modeling. Can we train an AI model to tokenize any type of audio data? The EnCodec architecture ( source ).

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Generative AI BERT Neural Network Deep Learning 298

Unite.AI

OCTOBER 22, 2024

From recommending products online to diagnosing medical conditions, AI is everywhere. As AI models become more complex, they demand more computational power, putting a strain on hardware and driving up costs. For example, as model parameters increase, computational demands can increase by a factor of 100 or more.

Neural Network 144

Neural Network Convolutional Neural Networks Deep Learning Natural Language Processing 144

Marktechpost

MAY 30, 2024

Google plays a crucial role in advancing AI by developing cutting-edge technologies and tools like TensorFlow, Vertex AI, and BERT. Its AI courses provide valuable knowledge and hands-on experience, helping learners build and optimize AI models, understand advanced AI concepts, and apply AI solutions to real-world problems.

Artificial Intelligence 130

Artificial Intelligence Artificial Intelligence BERT Computer Vision 130

Unite.AI

DECEMBER 4, 2023

In the ever-evolving domain of Artificial Intelligence (AI), where models like GPT-3 have been dominant for a long time, a silent but groundbreaking shift is taking place. Small Language Models (SLM) are emerging and challenging the prevailing narrative of their larger counterparts.

Large Language Models 215

Large Language Models BERT Neural Network Natural Language Processing 215

NVIDIA

FEBRUARY 11, 2025

Like the prolific jazz trumpeter and composer, researchers have been generating AI models at a feverish pace, exploring new architectures and use cases. No Labels, Lots of Opportunity Foundation models generally learn from unlabeled datasets, saving the time and expense of manually describing each item in massive collections.

Neural Network 55

Neural Network Large Language Models Robotics BERT 55

Unite.AI

JULY 25, 2024

According to MarketsandMarkets , the AI market is projected to grow from USD 214.6 One new advancement in this field is multilingual AI models. Integrated with Google Cloud's Vertex AI , Llama 3.1 IBM's Model 1 and Model 2 laid the groundwork for advanced systems. billion in 2024 to USD 1339.1

Neural Network 200

Neural Network AI AI Machine Learning 200

IBM Journey to AI blog

AUGUST 1, 2023

True to their name, generative AI models generate text, images, code , or other responses based on a user’s prompt. But what makes the generative functionality of these models—and, ultimately, their benefits to the organization—possible? An open-source model, Google created BERT in 2018.

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Generative AI Data Scientist Machine Learning BERT 176

Unite.AI

SEPTEMBER 18, 2023

NLP in particular has been a subfield that has been focussed heavily in the past few years that has resulted in the development of some top-notch LLMs like GPT and BERT. The neural network consists of three types of layers including the hidden layer, the input payer, and the output layer.

Deep Learning 318

Deep Learning Artificial Intelligence Artificial Intelligence AI 318

Unite.AI

AUGUST 2, 2023

These limitations are a major issue why an average human mind is able to learn from a single type of data much more effectively when compared to an AI model that relies on separate models & training data to distinguish between an image, text, and speech. They require a high amount of computational power.

Computer Vision 246

Computer Vision Algorithm Natural Language Processing Convolutional Neural Networks 246

Marktechpost

DECEMBER 5, 2023

As an alternative, Small Language Models (SLMs) have started stepping in and have become more potent and adaptable. Small Language Models, which are compact generative AI models, are distinguished by their small neural network size, number of parameters, and volume of training data.

BERT 132

BERT Large Language Models Neural Network Natural Language Processing 132

Unite.AI

FEBRUARY 23, 2024

Prompt engineering is the art and science of crafting inputs (or “prompts”) to effectively guide and interact with generative AI models, particularly large language models (LLMs) like ChatGPT. But what exactly is prompt engineering, and why has it become such a buzzword in the tech community?

Prompt Engineering 267

Prompt Engineering Prompt Engineer Large Language Models ChatGPT 267

Marktechpost

APRIL 25, 2024

This allows the model to perform better on tasks not covered extensively in the original training data. Parameter In the context of neural networks, including LLMs, a parameter is a variable part of the model’s architecture learned from the training data. These models typically involve an encoder and a decoder.

Large Language Models 128

Large Language Models LLM Neural Network Natural Language Processing 128

AssemblyAI

NOVEMBER 8, 2023

  Each stage leverages a deep neural network that operates as a sequence labeling problem but at different granularities: the first network operates at the token level and the second at the character level. We’ve used the DistilBertTokenizer , which inherits from the BERT WordPiece tokenization scheme.

Neural Network 147

Neural Network BERT Large Language Models Deep Learning 147

Mlearning.ai

APRIL 8, 2023

These included the Support vector machine (SVM) based models. Over the years, we evolved that to solving NLP use cases by adopting Neural Network-based algorithms loosely based on the structure and function of a human brain. Word embedding is a way to represent words as numbers in a neural network for language tasks.

NLP 98

NLP Neural Network Natural Language Processing Convolutional Neural Networks 98

ODSC - Open Data Science

MARCH 12, 2025

Takeaway: The industrys focus has shifted from building models to making them robust, scalable, and maintainable. The Boom of Generative AI and Large Language Models(LLMs) 20182020: NLP was gaining traction, with a focus on word embeddings, BERT, and sentiment analysis.

Data Science 52

Data Science ETL Machine Learning AI Engineer 52

Marktechpost

JANUARY 15, 2025

It employs artificial neural networks with multiple layershence the term deepto model intricate patterns in data. Unlike traditional machine learning, which relies heavily on manual feature extraction, deep learning models learn hierarchical representations on their own.

Deep Learning 85

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 85

Unite.AI

JULY 16, 2024

The ability to generate 3D digital assets from text prompts represents one of the most exciting recent developments in AI and computer graphics. billion by 2029 , text-to-3D AI models are poised to play a major role in revolutionizing content creation across industries like gaming, film, e-commerce, and more.

OpenAI 144

OpenAI BERT Neural Network AI 144

AWS Machine Learning Blog

FEBRUARY 6, 2024

We address this skew with generative AI models (Falcon-7B and Falcon-40B), which were prompted to generate event samples based on five examples from the training set to increase the semantic diversity and increase the sample size of labeled adverse events.

Large Language Models 113

Large Language Models BERT NLP Data Scientist 113

Unite.AI

DECEMBER 27, 2023

OpenAI's GPT-4 stands as a state-of-the-art generative language model, boasting an impressive over 1.7 trillion parameters, making it one of the largest language models ever created. Facebook's RoBERTa, built on the BERT architecture, utilizes deep learning algorithms to generate text based on given prompts.

Generative AI 215

Generative AI Chatbots Large Language Models OpenAI 215

Towards AI

SEPTEMBER 26, 2024

Building on that foundation, this week, in the High Learning Rate newsletter, we are sharing some exciting developments reshaping how AI models might learn to reason. These advancements center around self-taught reasoning, where AI models enhance their capabilities by learning from their own reasoning processes.

Neural Network 105

Neural Network BERT Explainability AI 105

AssemblyAI

SEPTEMBER 22, 2023

In August – Meta released a tool for AI-generated audio named AudioCraft and open-sourced all of its underlying models, including MusicGen. Last week – StabilityAI launched StableAudio , a subscription-based platform for creating music with AI models.

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Convolutional Neural Networks AI AI Data Scarcity 246

Artificial Corner

JULY 30, 2023

Large Language Models are hard and costly to train for general purposes which causes resource and cost restriction. Working of Large Language Models (LLMs) Deep neural networks are used in Large language models to produce results based on patterns discovered from training data.

Large Language Models 98

Large Language Models LLM Natural Language Processing Deep Learning 98

Topbots

OCTOBER 4, 2023

Predictive AI is used to predict future events or outcomes based on historical data. For example, a predictive AI model can be trained on a dataset of customer purchase history data and then used to predict which customers are most likely to churn in the next month. virtual models for advertising campaigns).

Generative AI 119

Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 119

John Snow Labs

JUNE 27, 2023

Large language models (LLMs) are precisely that – advanced AI models designed to process, understand, and generate natural language in a way that mimics human cognitive capabilities. These models are trained on massive datasets, encompassing billions of sentences, to capture the intricate nuances of language.

Large Language Models 52

Large Language Models BERT Natural Language Processing NLP 52

Google Research AI blog

FEBRUARY 10, 2023

Robust algorithm design is the backbone of systems across Google, particularly for our ML and AI models. We also had a number of interesting results on graph neural networks (GNN) in 2022. We provided a model-based taxonomy that unified many graph learning methods. You can find other posts in the series here.)

Algorithm 110

Algorithm Neural Network Auto-classification ML 110

Topbots

APRIL 11, 2023

In this article, we will delve into the latest advancements in the world of large-scale language models, exploring enhancements introduced by each model, their capabilities, and potential applications. The Most Important Large Language Models (LLMs) in 2023 1. PyTorch implementation of BERT is also available on GitHub.

NLP 98

NLP BERT Large Language Models Natural Language Processing 98

Snorkel AI

MARCH 26, 2025

At its core, LLM-as-Judge refers to the use of large language models to evaluate, compare, and validate outputs generated by AI models, including other LLMs. It replaces or augments the use of human annotators, which frontier model companies have employed by the hundreds or thousands to rate or rank LLM outputs.

LLM 52

LLM Data Scientist Prompt Engineer Prompt Engineering 52

Snorkel AI

MARCH 1, 2023

Foundation Models (FMs), such as GPT-3 and Stable Diffusion, mark the beginning of a new era in machine learning and artificial intelligence. Table of contents What are foundation models? Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

Viso.ai

MARCH 20, 2024

Foundation models are recent developments in artificial intelligence (AI). Models like GPT 4, BERT, DALL-E 3, CLIP, Sora, etc., are at the forefront of the AI revolution. Use Cases for Foundation Models Applications in Pre-trained Language Models like GPT, BERT, Claude, etc.

AI Development 52

AI Development AI Developer Computer Vision BERT 52

ODSC - Open Data Science

JUNE 9, 2023

The 1970s introduced bell bottoms, case grammars, semantic networks, and conceptual dependency theory. In the 90’s we got grunge, statistical models, recurrent neural networks and long short-term memory models (LSTM). It uses a neural network to learn the vector representations of words from a large corpus of text.

Natural Language Processing 52

Natural Language Processing ChatGPT Generative AI BERT 52

Viso.ai

DECEMBER 18, 2023

TensorFlow is an open-source software library for AI and machine learning with deep neural networks. TensorFlow Lite Advantages Model Conversion: TensorFlow models can be efficiently transferred into TensorFlow Lite models for mobile-friendly deployment. What is TensorFlow? Learn more about Viso Suite here.

Computer Vision 98

Computer Vision Machine Learning Deep Learning Neural Network 98

Viso.ai

JULY 18, 2024

Emergence and History of LLMs Artificial Neural Networks (ANNs) and Rule-based Models The foundation of these Computational Linguistics models (CL) dates back to the 1940s when Warren McCulloch and Walter Pitts laid the groundwork for AI. Both contain self-attention mechanisms and feed-forward neural networks.

Large Language Models 52

Large Language Models Neural Network Natural Language Processing BERT 52

Mlearning.ai

JANUARY 17, 2024

If classic AI is the wise owl, generative AI is the wiser owl with a paintbrush and a knack for writing. Traditional AI can recognize, classify, and cluster, but not generate the data it is trained on. Classic AI models are usually focused on a single task. Deep learning neural network.

Generative AI 98

Generative AI Prompt Engineer Prompt Engineering Large Language Models 98

Unite.AI

SEPTEMBER 13, 2024

How It Works TensorRT-LLM speeds up inference by optimizing neural networks during deployment using techniques like: Quantization : Reduces the precision of weights and activations, shrinking model size and improving inference speed. It provides a flexible environment for managing AI models at scale.

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Large Language Models LLM Natural Language Processing Auto-complete 130