Towards AI

JANUARY 29, 2025

Last Updated on January 29, 2025 by Editorial Team Author(s): Vishwajeet Originally published on Towards AI. How to Become a Generative AI Engineer in 2025? From creating art and music to generating human-like text and designing virtual worlds, Generative AI is reshaping industries and opening up new possibilities.

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Marktechpost

JANUARY 20, 2025

AI and ML are expanding at a remarkable rate, which is marked by the evolution of numerous specialized subdomains. Recently, two core branches that have become central in academic research and industrial applications are Generative AI and Predictive AI. Ian Goodfellow et al.

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Flipboard

DECEMBER 26, 2024

The ever-growing presence of artificial intelligence also made itself known in the computing world, by introducing an LLM-powered Internet search tool, finding ways around AIs voracious data appetite in scientific applications, and shifting from coding copilots to fully autonomous coderssomething thats still a work in progress. Perplexity.ai

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Unite.AI

JULY 23, 2024

However, recent advancements in artificial intelligence (AI) and neuroscience bring this fantasy closer to reality. Mind-reading AI, which interprets and decodes human thoughts by analyzing brain activity, is now an emerging field with significant implications. What is Mind-reading AI?

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AI Weekly

JULY 27, 2023

In the News 10 Thought-Provoking Novels About AI Although we’re probably still a long way off from the sentient forms of AI that are depicted in film and literature, we can turn to fiction to probe the questions raised by these technological advancements (and also to read great sci-fi stories!). to power those data centers.

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Marktechpost

AUGUST 4, 2024

Representational similarity measures are essential tools in machine learning, used to compare internal representations of neural networks. These measures help researchers understand learning dynamics, model behaviors, and performance by providing insights into how different neural network layers and architectures process information.

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Towards AI

JUNE 12, 2024

Last Updated on June 13, 2024 by Editorial Team Author(s): Thiongo John W Originally published on Towards AI. Photo by david clarke on Unsplash The most recent breakthroughs in language models have been the use of neural network architectures to represent text. Both BERT and GPT are based on the Transformer architecture.

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Unite.AI

MAY 29, 2024

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Source: A pipeline on Generative AI This figure of a generative AI pipeline illustrates the applicability of models such as BERT, GPT, and OPT in data extraction.

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Unite.AI

APRIL 30, 2024

Recently, Artificial Intelligence (AI) chatbots and virtual assistants have become indispensable, transforming our interactions with digital platforms and services. This self-awareness is not merely a theoretical concept but a practical necessity for AI to progress into more effective and ethical tools.

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Unite.AI

NOVEMBER 6, 2023

In recent years, Generative AI has shown promising results in solving complex AI tasks. Modern AI models like ChatGPT , Bard , LLaMA , DALL-E.3 Moreover, Multimodal AI techniques have emerged, capable of processing multiple data modalities, i.e., text, images, audio, and videos simultaneously. What are its Limitations?

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Unite.AI

AUGUST 8, 2023

That is Generative AI. Microsoft is already discontinuing its Cortana app this month to prioritize newer Generative AI innovations, like Bing Chat. billion R&D budget to generative AI, as indicated by CEO Tim Cook. Usually, they are built with deep neural networks, optimized to capture the multifaceted variations in data.

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Analytics Vidhya

JUNE 5, 2023

These gargantuan neural networks have revolutionized how machines learn and generate human language, propelling the boundaries of what was once thought possible.

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Unite.AI

DECEMBER 13, 2024

Artificial intelligence (AI) fundamentally transforms how we live, work, and communicate. Large language models (LLMs) , such as GPT-4 , BERT , Llama , etc., have introduced remarkable advancements in conversational AI , delivering rapid and human-like responses. Early AI systems were static, offering limited functionality.

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AssemblyAI

MAY 3, 2023

In the grand tapestry of modern artificial intelligence, how do we ensure that the threads we weave when designing powerful AI systems align with the intricate patterns of human values? This question lies at the heart of AI alignment , a field that seeks to harmonize the actions of AI systems with our own goals and interests.

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AssemblyAI

JUNE 27, 2023

Over the past decade, we've witnessed significant advancements in AI-powered audio generation techniques, including music and speech synthesis. This blog post is part of a series on generative AI. This shift has led to dramatic improvements in speech recognition and several other applications of discriminative AI.

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AWS Machine Learning Blog

JANUARY 19, 2024

In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. First, we use an Amazon SageMaker Studio notebook to fine-tune a pre-trained BERT model on a target task using a domain-specific dataset.

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Unite.AI

AUGUST 1, 2023

The spotlight is also on DALL-E, an AI model that crafts images from textual inputs. Such sophisticated and accessible AI models are poised to redefine the future of work, learning, and creativity. The Impact of Prompt Quality Using well-defined prompts is the key to engaging in useful and meaningful conversations with AI systems.

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Unite.AI

SEPTEMBER 18, 2023

In this article, we will be talking about how the collaboration between AI and blockchain gives birth to numerous privacy protection techniques, and their application in different verticals including de-identification, data encryption, k-anonymity, and multi-tier distributed ledger methods.

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Unite.AI

JUNE 5, 2024

Artificial Intelligence (AI) has seen tremendous growth, transforming industries from healthcare to finance. AI models are expected to exceed 100 trillion parameters, pushing the limits of current hardware capabilities. These issues can hinder the widespread adoption of AI technologies.

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Unite.AI

FEBRUARY 7, 2024

This is why Machine Learning Operations (MLOps) has emerged as a paradigm to offer scalable and measurable values to Artificial Intelligence (AI) driven businesses. LLMs are deep neural networks that can generate natural language texts for various purposes, such as answering questions, summarizing documents, or writing code.

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Towards AI

MARCH 12, 2025

Last Updated on March 12, 2025 by Editorial Team Author(s): Ecem Karaman Originally published on Towards AI. Normalization Trade-off: GPT models preserve formatting & nuance (more token complexity); BERT aggressively cleans text simpler tokens, reduced nuance, ideal for structured tasks. 📌 Why Tokenization?

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Marktechpost

APRIL 21, 2024

The following six free AI courses offer a structured pathway for beginners to start their journey into the world of artificial intelligence. Introduction to Generative AI: This course provides an introductory overview of Generative AI, explaining what it is and how it differs from traditional machine learning methods.

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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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Marktechpost

MAY 5, 2024

By leveraging a new data-dependent convolution layer, Orchid dynamically adjusts its kernel based on the input data using a conditioning neural network, allowing it to handle sequence lengths up to 131K efficiently. Compared to the BERT-base, the Orchid-BERT-base has 30% fewer parameters yet achieves a 1.0-point

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Towards AI

JUNE 3, 2024

Last Updated on June 3, 2024 by Editorial Team Author(s): Greg Postalian-Yrausquin Originally published on Towards AI. BERT is a state-of-the-art algorithm designed by Google to process text data and convert it into vectors ([link]. apply(lambda x: preprepare(str(x))) There is an extensive list of pre-trained models for BERT.

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Unite.AI

OCTOBER 22, 2024

Artificial Intelligence (AI) is changing our world incredibly, influencing industries like healthcare, finance, and retail. 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.

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Pickl AI

AUGUST 14, 2024

Summary: Neural networks are a key technique in Machine Learning, inspired by the human brain. Different types of neural networks, such as feedforward, convolutional, and recurrent networks, are designed for specific tasks like image recognition, Natural Language Processing, and sequence modelling.

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Unite.AI

AUGUST 28, 2023

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. These AI agents, transcending chatbots and voice assistants, are shaping a new paradigm for both industries and our daily lives.

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Marktechpost

DECEMBER 12, 2024

A Deep Neural Network (DNN) is an artificial neural network that features multiple layers of interconnected nodes, also known as neurons. The deep aspect of DNNs comes from multiple hidden layers, which allow the network to learn and model complex patterns and relationships in data.

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Unite.AI

JULY 25, 2024

Artificial Intelligence (AI) transforms how we interact with technology, breaking language barriers and enabling seamless global communication. According to MarketsandMarkets , the AI market is projected to grow from USD 214.6 One new advancement in this field is multilingual AI models. billion in 2024 to USD 1339.1

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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. These models, characterized by their lightweight neural networks, fewer parameters, and streamlined training data, are questioning the conventional narrative.

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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. Foundation models: The driving force behind generative AI Also known as a transformer, a foundation model is an AI algorithm trained on vast amounts of broad data.

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Marktechpost

NOVEMBER 15, 2023

This model consists of two primary modules: A pre-trained BERT model is employed to extract pertinent information from the input text, and A diffusion UNet model processes the output from BERT. It is built upon a pre-trained BERT model. The BERT model takes subword input, and its output is processed by a 1D U-Net structure.

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Marktechpost

NOVEMBER 14, 2023

The research presents a study on simplifying transformer blocks in deep neural networks, specifically focusing on the standard transformer block. The study examines the simplification of transformer blocks in deep neural networks, focusing specifically on the standard transformer block.

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Pickl AI

NOVEMBER 26, 2024

Summary: Recurrent Neural Networks (RNNs) are specialised neural networks designed for processing sequential data by maintaining memory of previous inputs. Introduction Neural networks have revolutionised data processing by mimicking the human brain’s ability to recognise patterns.

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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. Earlier neural networks were narrowly tuned for specific tasks. A year after the group defined foundation models, other tech watchers coined a related term generative AI.

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Unite.AI

DECEMBER 9, 2024

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. For years, these laws served as a blueprint for developing better AI. The Basics of Scaling Laws Scaling laws are like a formula for AI improvement.

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