Unite.AI

SEPTEMBER 20, 2024

The emergence of machine learning and Natural Language Processing (NLP) in the 1990s led to a pivotal shift in AI. Its specialization makes it uniquely adept at powering AI workflows in an industry known for strict regulation and compliance standards.

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Unite.AI

JANUARY 12, 2024

The Evolution of AI Research As capabilities have grown, research trends and priorities have also shifted, often corresponding with technological milestones. The rise of deep learning reignited interest in neural networks, while natural language processing surged with ChatGPT-level models.

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How to Learn Machine Learning

APRIL 4, 2025

AI will help to strengthen defences, cybercriminal departments will utilize AI to work against phishing and deepfake attacks. Explainable AI (XAI): As AI is expanding rapidly, there is a high demand for transparency and trust in AI-driven decisions. Thus, explainable AI (XAI) comes into the picture.

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IBM Journey to AI blog

SEPTEMBER 20, 2023

Large language models (LLMs) are a class of foundational models (FM) that consist of layers of neural networks that have been trained on these massive amounts of unlabeled data. Large language models (LLMs) have taken the field of AI by storm.

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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. This is a critical limitation as the demand for explainable AI grows. BERT and RoBERTa, for example, have shown superior performance over traditional stylometric techniques.

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Mlearning.ai

FEBRUARY 6, 2023

With these statistics, a dispute process may be needed, but how would disputes be resolved if even the admissions officers don’t know why the model made a prediction ? This is why we need Explainable AI (XAI). The 2019 Conference on Empirical Methods in Natural Language Processing. [8] Weigreffe, Y.

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NVIDIA

DECEMBER 13, 2023

Financial Services Firms Embrace AI for Identity Verification The financial services industry is developing AI for identity verification. At the same time, NLP reads the documents to measure the veracity of the data on the documents as the AI analyzes them to look for fraudulent records.

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Pickl AI

SEPTEMBER 17, 2024

Transfer learning can significantly reduce the time and resources required to train a model from scratch and has applications in areas such as computer vision and natural language processing. What Is the Role of Explainable AI (XAI) In Machine Learning? What Is the Role of Ensemble Methods in Machine Learning?

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Pickl AI

AUGUST 14, 2024

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. They consist of interconnected nodes that learn complex patterns in data.

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Pickl AI

DECEMBER 10, 2024

Summary : Data Analytics trends like generative AI, edge computing, and Explainable AI redefine insights and decision-making. Key Takeaways Generative AI simplifies data insights, enabling actionable decision-making and enhancing data storytelling. Lets explore the key developments shaping this space.

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Pickl AI

NOVEMBER 5, 2024

AI encompasses various subfields, including Machine Learning (ML), Natural Language Processing (NLP), robotics, and computer vision. Together, Data Science and AI enable organisations to analyse vast amounts of data efficiently and make informed decisions based on predictive analytics.

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How to Learn Machine Learning

JANUARY 21, 2023

Advances in machine learning and deep learning techniques are making AI systems increasingly accurate and efficient. Moreover, advancements in Natural Language Processing (NLP) are allowing AI-powered systems to understand human speech and interact in more natural ways.

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Viso.ai

MARCH 26, 2024

Real-world applications range from automating loan approvals to processing insurance claims. Technologies such as Optical Character Recognition (OCR) and Natural Language Processing (NLP) are foundational to this. AI’s benefits extend to processing unstructured data from news feeds and social media.

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Viso.ai

JULY 9, 2024

For example, in Natural Language Processing (NLP), the model works by predicting the next word in a sequence. In NLP this process is used to predict the next word in a sentence. This architecture is widely used for language models bringing state-of-the-art performance and results.

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Pickl AI

NOVEMBER 18, 2024

Natural language processing ( NLP ) allows machines to understand, interpret, and generate human language, which powers applications like chatbots and voice assistants. Neural networks are powerful for complex tasks, such as image recognition or NLP, but may require more computational resources.

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Pickl AI

JANUARY 13, 2025

Key Features: Comprehensive coverage of AI fundamentals and advanced topics. Explains search algorithms and game theory. Includes statistical natural language processing techniques. Key Features: Explains AI algorithms like clustering and regression. Key Features: Covers basic AI concepts.

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Snorkel AI

MARCH 19, 2024

Google has established itself as a dominant force in the realm of AI, consistently pushing the boundaries of AI research and innovation. These breakthroughs have paved the way for transformative AI applications across various industries, empowering organizations to leverage AI’s potential while navigating ethical considerations.

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IBM Journey to AI blog

SEPTEMBER 3, 2024

One study estimates that training a single natural language processing model emits over 600,000 pounds of carbon dioxide; nearly 5 times the average emissions of a car over its lifetime. Many AI applications run on servers in data centers, which generate considerable heat and need large volumes of water for cooling. .

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The MLOps Blog

AUGUST 11, 2023

Embeddings are utilized in computer vision tasks, NLP tasks, and statistics. More specifically, embeddings enable neural networks to consume training data in formats that allow extracting features from the data, which is particularly important in tasks such as natural language processing (NLP) or image recognition.

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ODSC - Open Data Science

DECEMBER 27, 2024

From Developer Tools to AI Agents: A Journey Fueled byPassion Roberts journey into AI agents stems from a career dedicated to building tools that enhance developer productivity. His work in REST APIs and Kubernetes laid the foundation for OpenHands, combining his love for NLP and developer tools.

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Unite.AI

NOVEMBER 29, 2023

The adaptable nature of these algorithms enhances their proficiency in recognizing and mitigating emerging threats to the integrity of elections. NLP's sophisticated language comprehension empowers AI systems to interpret and contextualize information, significantly enhancing their ability to effectively detect and combat false information.

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Pickl AI

APRIL 2, 2024

Here are some cutting-edge applications that can give your business a competitive edge: Natural Language Processing (NLP): Extract insights from text data like customer reviews, social media conversations, and documents. Beyond the Basics: Advanced Applications of Data Science Data science goes beyond basic analytics.

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IBM Journey to AI blog

FEBRUARY 9, 2024

The incoming generation of interdisciplinary models, comprising proprietary models like OpenAI’s GPT-4V or Google’s Gemini, as well as open source models like LLaVa, Adept or Qwen-VL, can move freely between natural language processing (NLP) and computer vision tasks.

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