AI News

FEBRUARY 17, 2025

Reduce false positives: Unlike traditional rule-based systems that flag legitimate transactions as fraud, AI continuously learns and improves accuracy over time. AI-powered fraud detection helps prevent these tactics by: Verifying receipts: AI scans submitted receipts and detects forgeries, duplicates, and altered information.

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Unite.AI

MARCH 2, 2025

Meta AI is addressing this challenge head-on with Scalable Memory Layers (SMLs), a deep learning approach designed to overcome dense layer inefficiencies. Instead of embedding all learned information within fixed-weight parameters, SMLs introduce an external memory system, retrieving information only when needed.

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Unite.AI

MARCH 12, 2025

Adaptive algorithms update themselves with new fraud patterns, feature engineering improves predictive accuracy, and federated learning enables collaboration between financial institutions without compromising sensitive customer data. One of the primary concerns is data privacy and ethical considerations.

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Marktechpost

JULY 9, 2024

One new paradigm that has emerged to meet these problems is continuous learning or CL. This is the capacity to learn from new situations constantly without losing any of the information that has already been discovered. This algorithm has proven to reach state-of-the-art classification accuracy on CNNs.

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Marktechpost

MARCH 28, 2024

Continual Learning (CL) is a method that focuses on gaining knowledge from dynamically changing data distributions. This technique mimics real-world scenarios and helps improve the performance of a model as it encounters new data while retaining previous information. have been developed.

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Unite.AI

NOVEMBER 26, 2024

While they are excellent at recognizing patterns and synthesizing written knowledge, they struggle to mimic the way humans learn and behave. As AI continues to evolve, we are seeing a shift from models that simply process information to ones that learn, adapt, and behave like humans. But there are challenges.

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Unite.AI

OCTOBER 23, 2024

LLMs are trained on large datasets that contain personal and sensitive information. One emerging solution to address these concerns is LLM unlearning —a process that allows models to forget specific pieces of information without compromising their overall performance. They can reproduce this data if prompted in the right way.

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Marktechpost

MARCH 15, 2024

The key challenge in this domain is introducing new information to a model without erasing its existing knowledge, a problem known as catastrophic forgetting. The study focuses on a sophisticated strategy involving learning rate adjustments and replaying a subset of the previously learned data.

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Unite.AI

DECEMBER 26, 2024

One big problem is AI hallucinations , where the system produces false or made-up information. By incorporating advanced memory systems, MoME improves how AI processes information, enhancing accuracy, reliability, and efficiency. These models may invent information to fill the gaps when dealing with ambiguous or incomplete inputs.

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AI News

JUNE 3, 2024

delivers accurate and relevant information, making it an indispensable tool for professionals in these fields. Harnessing the Power of Machine Learning and Deep Learning At TickLab, our innovative approach is deeply rooted in the advanced capabilities of machine learning (ML) and deep learning (DL).

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Unite.AI

FEBRUARY 21, 2025

Akeneo is the product experience (PX) company and global leader in Product Information Management (PIM). How is AI transforming product information management (PIM) beyond just centralizing data? Akeneo is described as the “worlds first intelligent product cloud”what sets it apart from traditional PIM solutions?

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Unite.AI

JANUARY 30, 2025

Driving Continuous Learning and AI Literacy For AI to succeed, employees need the skills and confidence to work in tandem with intelligent systems. AI orchestrators can create a skills development framework to build employee proficiency and embed continuous learning into everyday workflows.

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Unite.AI

DECEMBER 26, 2024

Utilizing computer vision algorithms that process a steady stream of captured images, the radar-based technology continuously analyzes various room layouts, outdoor and indoor situations, circumstances with pets, and people of varying shapes, sizes, and ages to accurately classify and detect falls.

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AWS Machine Learning Blog

MARCH 18, 2025

In the rapidly evolving healthcare landscape, patients often find themselves navigating a maze of complex medical information, seeking answers to their questions and concerns. However, accessing accurate and comprehensible information can be a daunting task, leading to confusion and frustration.

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Unite.AI

FEBRUARY 21, 2025

It uses advanced machine learning algorithms to match conference attendees, exhibitors, and sponsors based on their interests and goals. Key features of Grip: AI-driven matchmaking algorithm Uses machine learning algorithms on billions of data points to recommend the most relevant people to meet.

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Unite.AI

FEBRUARY 5, 2025

More than 5,400 companies, including Zoom, UiPath, JCDecaux, and Microsoft, use the platform to gather customer insights and inform development decisions. Since then, Ive learned that theres more value in taking your time with onboarding. Embrace Continuous Learning : AI is a dynamic field, so stay curious and keep learning.

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Flipboard

JANUARY 28, 2025

Picture your enterprise as a living ecosystem, where surging market demand instantly informs staffing decisions, where a new vendor’s onboarding optimizes your emissions metrics, where rising customer engagement reveals product opportunities. Next, leaders should deploy agents in clusters that can learn and evolve together.

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Unite.AI

DECEMBER 10, 2024

An AI knowledge base might allow continuous access to training materials, thereby allowing the reinforcement of learning and building the skills over time within the employees. The resources will help employees independently access information and integrate AI at their comfort and pace.

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Unite.AI

DECEMBER 23, 2024

The system also synchronizes data across all modules in real-time, creating a unified environment where information flows smoothly between staff members, pet parents, and clinic systems. This enables seamless coordination between appointment scheduling, medical documentation, and inventory management through AI-powered automation.

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Towards AI

JANUARY 21, 2025

This persistence would enable the continuous development of contextual awareness through memory, and thus the accumulated experience which is its outcome can inform and refine ongoing interactions. Persistence and continuous learning are obviously not requirements or even desirable features for all use cases.

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The MLOps Blog

FEBRUARY 22, 2024

TL;DR: In many machine-learning projects, the model has to frequently be retrained to adapt to changing data or to personalize it. Continual learning is a set of approaches to train machine learning models incrementally, using data samples only once as they arrive. What is continual learning?

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AWS Machine Learning Blog

MARCH 17, 2025

Their knowledge is static and confined to the information they were trained on, which becomes problematic when dealing with dynamic and constantly evolving domains like healthcare. Furthermore, healthcare decisions often require integrating information from multiple sources, such as medical literature, clinical databases, and patient records.

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Unite.AI

FEBRUARY 7, 2025

I was trying to solve a personal frustration around making informed purchasing decisions without constantly having to rebuild context on Google or Amazon. Bee is leading this shift by focusing on continuous learning and adaptation rather than just adding more features.

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Unite.AI

MAY 31, 2023

A neural network (NN) is a machine learning algorithm that imitates the human brain's structure and operational capabilities to recognize patterns from training data. Since LLM neurons offer rich connections that can express more information, they are smaller in size compared to regular NNs.

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Unite.AI

NOVEMBER 11, 2023

” This prompt helps in creating comprehensive surveys that touch upon various facets of employee experience, ensuring that you have the data needed to make informed decisions to boost morale and productivity. Generating Training Module Outlines Continuous learning and development are key to keeping employees skilled and motivated.

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AWS Machine Learning Blog

MARCH 1, 2023

For information about creating IAM policies for Amazon Comprehend, see Permissions to perform Amazon Comprehend actions. Please refer to section 4, “Preparing data,” from the post Building a custom classifier using Amazon Comprehend for the script and detailed information on data preparation and structure.

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Marktechpost

OCTOBER 1, 2024

Continual learning is a rapidly evolving area of research that focuses on developing models capable of learning from sequentially arriving data streams, similar to human learning. It addresses the challenges of adapting to new information while retaining previously acquired knowledge.

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Unite.AI

APRIL 6, 2025

Cloud-connected AI for Continuous Learning and Optimization FreshAI operates on Google Clouds Vertex AI infrastructure, enabling scalable deployment, continuous model retraining, and centralized data management. Customers can verify their selections on-screen before proceeding to payment, reducing errors and disputes.

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Unite.AI

JANUARY 17, 2025

Continuous Learning and Optimization of In-Store By leveraging AI, retailers can continuously refine their strategies to create more effective advertising campaigns in physical stores. AI can also time-stamp the ads, providing additional validation and improving the accuracy of measurement.

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Unite.AI

JULY 25, 2023

An AI feedback loop is an iterative process where an AI model's decisions and outputs are continuously collected and used to enhance or retrain the same model, resulting in continuous learning, development, and model improvement. Typically, users give their feedback on the model outcome, which is then used for retraining.

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NYU Center for Data Science

JANUARY 22, 2025

Large language models forget how to interpret new information accurately, even when provided with the most up-to-date context. The researchers found that language models performance declined by approximately 20% when making predictions about recent events, compared to their accuracy on older information.

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Unite.AI

NOVEMBER 11, 2024

Our team maintains its technological edge through continuous learning and the participation in leading AI conferences. Our team continuously evolves how we leverage data, whether it is through more efficient mining of the data we have access to or augmenting the data with state-of-the-art generation technology.

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IBM Journey to AI blog

OCTOBER 17, 2024

Successful CFOs know that continuous learning is essential to innovation For CFOs looking to remain competitive in an ever-evolving business environment, understanding and applying generative AI is essential. AI can help identify potential risks earlier, allowing for more proactive management and better resource allocation.

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Pickl AI

MARCH 20, 2025

RAG improves AI responses by pulling in real-time information from external sources. Unlike traditional RAG, it uses intelligent agents to make decisions, learn from interactions, and provide more accurate answers. How Agentic RAG Works It is an advanced AI system that goes beyond simply retrieving information.

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Unite.AI

JUNE 2, 2023

In the age of information overload, managing emails can be a daunting task. EmailTree is also renowned for its ability to extract relevant information from complex emails and integrate them into your existing business workflow. The system continuously learns from user behavior, improving its performance over time.

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NVIDIA

MARCH 18, 2025

That massive, continuous flow of data generated by base stations, routers, switches and data centers including network traffic information, performance metrics, configuration and topology is unstructured and complex.

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Unite.AI

JANUARY 9, 2024

to ensure the technology is capable of continuously assessing risks in real-time and delivering to users the information needed to focus their actions and activities in ways that drive measurable outcomes. User input is critical to refinement and updates to ensure AI tools are meeting current and future needs.

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