Unite.AI

JULY 11, 2023

Covers Google tools for creating your own Generative AI apps. You’ll also learn about the Generative AI model types: unimodal or multimodal, in this course. Introduction to Large Language Models Image Source Course difficulty: Beginner-level Completion time: ~ 45 minutes Prerequisites: No What will AI enthusiasts learn?

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IBM Journey to AI blog

JANUARY 25, 2024

How might this insight affect evaluation of AI models? Model (in)accuracy To quote a common aphorism, all models are wrong. This holds true in the areas of statistics, science and AI. Models created with a lack of domain expertise can lead to erroneous outputs. How are you making your model explainable?

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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.

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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.

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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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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IBM Journey to AI blog

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” They are now capable of natural language processing ( NLP ), grasping context and exhibiting elements of creativity.

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AWS Machine Learning Blog

APRIL 4, 2025

These classified transactions then serve as critical inputs for downstream credit risk AI models, enabling more accurate assessments of a businesss creditworthiness. They fine-tuned this model using their proprietary dataset and in-house data science expertise.

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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.

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Unite.AI

DECEMBER 4, 2023

GPT 3 and similar Large Language Models (LLM) , such as BERT , famous for its bidirectional context understanding, T-5 with its text-to-text approach, and XLNet , which combines autoregressive and autoencoding models, have all played pivotal roles in transforming the Natural Language Processing (NLP) paradigm.

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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. Why Does the AI Industry Need the Data2Vec Algorithm?

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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.

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Marktechpost

DECEMBER 18, 2023

This article discusses a few AI models of 2023 that have the capability to transform the medical landscape. Although it shows promising capabilities, the researchers want to conduct more rigorous assessments to ensure that the model can be deployed in safety-critical domains.

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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. Using blockchain frameworks to deploy AI models to achieve decentralization services among models, and enhancing the scalability and stability of the system.

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Marktechpost

DECEMBER 5, 2023

What are Small Language Models? 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.

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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.

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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?

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Marktechpost

JULY 22, 2024

Authorship Verification (AV) is critical in natural language processing (NLP), determining whether two texts share the same authorship. With deep learning models like BERT and RoBERTa, the field has seen a paradigm shift. Existing methods for AV have advanced significantly with the use of deep learning models.

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Marktechpost

NOVEMBER 5, 2024

Previous attempts to address computational challenges in AI research include Compute surveys that explore resource access and environmental impacts but most focused narrowly on NLP communities. This work marks an important milestone in empowering academic researchers to engage more actively in large-scale AI model development.

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John Snow Labs

JUNE 27, 2023

Are you curious about the groundbreaking advancements in Natural Language Processing (NLP)? Prepare to be amazed as we delve into the world of Large Language Models (LLMs) – the driving force behind NLP’s remarkable progress. What are Large Language Models (LLMs)?

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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.

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Marktechpost

JUNE 24, 2024

Impact of ChatGPT on Human Skills: The rapid emergence of ChatGPT, a highly advanced conversational AI model developed by OpenAI, has generated significant interest and debate across both scientific and business communities.

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Artificial Corner

JULY 30, 2023

Natural Language Processing (NLP) is a subfield of artificial intelligence. In order to get precise and intended replies from AI models, prompts are used to direct and fine-tune the desired behavior from the AI system. What are large language models used for?

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AssemblyAI

MAY 3, 2023

The problem of how to mitigate the risks and misuse of these AI models has therefore become a primary concern for all companies offering access to large language models as online services. Virtually all current LMs are based on a particularly successful choice of architecture: the so-called Transformer model , invented in 2017.

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Marktechpost

JANUARY 4, 2024

The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. Training these models, however, is challenging. Unicron paves the way for more efficient and reliable AI model development by addressing the critical need for resilient training systems.

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John Snow Labs

MAY 15, 2023

The underlying principles behind the NLP Test library: Enabling data scientists to deliver reliable, safe and effective language models. Responsible AI: Getting from Goals to Daily Practices How is it possible to develop AI models that are transparent, safe, and equitable? Finally, [ van Aken et. Open Source.

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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. Google released BERT as open-source software , spawning a family of follow-ons and setting off a race to build ever larger, more powerful LLMs.

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Bugra Akyildiz

DECEMBER 28, 2024

Libraries DRAGON is a new foundation model (improvement of BERT) that is pre-trained jointly from text and knowledge graphs for improved language, knowledge and reasoning capabilities. DRAGON can be used as a drop-in replacement for BERT. GPUStack is an open-source GPU cluster manager for running large language models(LLMs).

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Marktechpost

OCTOBER 29, 2024

PII Masker is an advanced open-source tool designed to protect sensitive data by leveraging state-of-the-art artificial intelligence (AI) models. PII Masker utilizes cutting-edge AI models, particularly Natural Language Processing (NLP), to accurately detect and classify sensitive information.

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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. a social media post or product description).

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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.

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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.

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ODSC - Open Data Science

JANUARY 17, 2025

Implicit Learning of Intent : LLMs like GPT, BERT, or other transformer-based models learn to predict the next word or fill in missing text based on surrounding context. Exposure to different ways of expressing intents allows models to generalize better to new, unseenqueries. Will it rain tomorrow?,

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Towards AI

JANUARY 30, 2024

To alleviate this… abhinavkimothi.gumroad.com Types of Models Foundation Models Large AI models that have millions/billions of parameters and are trained on terabytes of generalized and unlabelled data. Designed to be general-purpose, providing a foundation for various AI applications. Examples: GPT 3.5,

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AWS Machine Learning Blog

JUNE 25, 2024

Unlike traditional natural language processing (NLP) approaches, such as classification methods, LLMs offer greater flexibility in adapting to dynamically changing categories and improved accuracy by using pre-trained knowledge embedded within the model.

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John Snow Labs

OCTOBER 19, 2023

Natural language processing (NLP) is a critical branch of artificial intelligence devoted to understanding and generating natural language. However, NLP systems are susceptible to biases, often mirroring the prejudices found in their training data. How to use the LangTest library to evaluate LLM for bias using CrowS-Pairs dataset?

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ODSC - Open Data Science

JUNE 9, 2023

In the 90’s we got grunge, statistical models, recurrent neural networks and long short-term memory models (LSTM). 2000–2015 The new millennium gave us low-rise jeans, trucker hats, and bigger advancements in language modeling, word embeddings, and Google Translate. BERT was designed to understand the meanings of sentences.

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