Marktechpost

OCTOBER 25, 2023

However, despite their remarkable zero-shot capabilities, these agents have faced limitations in continually refining their performance over time, especially across varied environments and tasks. If you like our work, you will love our newsletter. We are also on WhatsApp. Join our AI Channel on Whatsapp.

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AI News

JUNE 3, 2024

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). Deep learning, a subset of ML, plays a crucial role in our data analysis and decision-making processes.

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AWS Machine Learning Blog

MAY 9, 2024

The rapid advancements in artificial intelligence and machine learning (AI/ML) have made these technologies a transformative force across industries. An effective approach that addresses a wide range of observed issues is the establishment of an AI/ML center of excellence (CoE). What is an AI/ML CoE?

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AI News

FEBRUARY 17, 2025

It uses machine learning (ML), natural language processing (NLP), and optical character recognition (OCR) to read and analyse structured and unstructured documents, with abilities far beyond traditional rule-based systems. What is intelligent document processing? AI can compare submissions and flag inconsistencies.

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Marktechpost

MARCH 15, 2024

This research advances in continual learning, presenting a viable and cost-effective method for updating LLMs. Don’t Forget to join our 38k+ ML SubReddit The post Can Continual Learning Strategies Outperform Traditional Re-Training in Large Language Models? Also, don’t forget to follow us on Twitter.

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Towards AI

JANUARY 29, 2025

d) Continuous Learning and Innovation The field of Generative AI is constantly evolving, offering endless opportunities to learn and innovate. Programming Languages: Python (most widely used in AI/ML) R, Java, or C++ (optional but useful) 2. Adaptability and Continuous Learning 4.

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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. These problems keep many ML practitioners awake at night.

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Unite.AI

APRIL 6, 2025

Wendys AI-Powered Drive-Thru System (FreshAI) FreshAI uses advanced natural language processing (NLP) , machine learning (ML) , and generative AI to optimize the fast-food ordering experience. The AI can process multiple customer requests in parallel, reducing bottlenecks during peak hours.

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Unite.AI

OCTOBER 30, 2023

Model development Efficient development and deployment is one of the important yet dicey aspects of AI/ML development. AI and ML projects require frequent incremental iterations and seamless integration into production, following a CI/CD approach. Continuous learning is vital in DevOps for ongoing improvement.

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Unite.AI

JUNE 19, 2024

In world of Artificial Intelligence (AI) and Machine Learning (ML), a new professionals has emerged, bridging the gap between cutting-edge algorithms and real-world deployment. As businesses across industries increasingly embrace AI and ML to gain a competitive edge, the demand for MLOps Engineers has skyrocketed.

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Towards AI

MARCH 21, 2023

When I was younger, I was sure that ML could, if not overperform, at least match the pre-ML-era solutions almost everywhere. I’ve looked at rule constraints in deployment and wondered why not replace them with tree-based ml models. ML algorithms can improve their performance as more data is used for training.

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AWS Machine Learning Blog

MARCH 18, 2025

The rise of generative AI has significantly increased the complexity of building, training, and deploying machine learning (ML) models. Customers also face the challenges of writing specialized code for distributed training, continuously optimizing models, addressing hardware issues, and keeping projects on track and within budget.

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NYU Center for Data Science

SEPTEMBER 28, 2023

Building on this momentum is a dynamic research group at the heart of CDS called the Machine Learning and Language (ML²) group. By 2020, ML² was a thriving community, primarily known for its recurring speaker series where researchers presented their work to peers. What does it mean to work in NLP in the age of LLMs?

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Marktechpost

MARCH 22, 2025

In R&D, two primary challenges must be addressed: enabling continuous learning and acquiring specialized knowledge. To overcome this, RD-Agent employs a dynamic learning framework that integrates real-world feedback, allowing it to refine hypotheses and accumulate domain knowledge over time.

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Unite.AI

SEPTEMBER 4, 2024

ML-driven Creative Targeting™: For each cohort, we use machine learning in collaboration with our creative team to devise optimal creative strategies. Can you explain the concept of ML-driven Creative Targeting™ and how it integrates with your creative strategy? The result is a synergy between data science and creativity.

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AI News

SEPTEMBER 27, 2024

” He notes it’s powered by “a compound AI system that continuously learns from usage across an organisation’s entire data stack, including ETL pipelines, lineage, and other queries.”

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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. The core issue is that these methods are not evaluated under the constraints of continual learning.

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AWS Machine Learning Blog

MARCH 1, 2023

This post demonstrates how you can build a custom text classifier (no prior ML knowledge needed) that can assign a specific label to a given text. Admin:~/environment $ aws s3 cp s3://aws-blogs-artifacts-public/artifacts/ML-13607/custom-classifier-complete-dataset.csv. Happy learning and experimentation!

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Flipboard

SEPTEMBER 10, 2023

AI Apps are domain-infused, AI/ML-powered applications that continuously learn and adapt with minimal human intervention in helping non-technical users manage data and analytics-intensive operations to deliver well-defined operational outcomes.

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AWS Machine Learning Blog

MARCH 17, 2025

Case studies and real-world examples 3M Health Information Systems is collaborating with AWS to accelerate AI innovation in clinical documentation by using AWS machine learning (ML) services, compute power, and LLM capabilities. To learn more, see AWS for Healthcare & Life Sciences.

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Unite.AI

JANUARY 17, 2025

Businesses that leverage AI and machine learning (ML) to personalize ads see a 1.3 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. increase in incremental return on ad spend.

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Unite.AI

JUNE 13, 2024

Leveraging AI and Automation Deploying AI and machine learning (ML) models tailored to each of these attack classes is critical for proactive threat detection and prevention. However, this is rapidly changing as security vendors race to develop advanced AI/ML models capable of detecting and blocking these AI-powered threats.

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Chatbots Life

APRIL 27, 2024

For enterprise software, AI and ML are like special effects. By examining how AI and ML in enterprise software can drive business success, we aim to highlight these technologies’ transformational potential and underscore their importance in today’s competitive business environment.

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Unite.AI

FEBRUARY 21, 2025

Scalability is another challenge, as AI models must continuously learn and adapt to new product data, customer behaviors, and market trends while maintaining accuracy and relevance. AI relies on high-quality, structured data to generate meaningful insights, but many businesses struggle with fragmented or incomplete product information.

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Marktechpost

MAY 4, 2024

Researchers in this field aim to create systems capable of continuous learning and adaptation, ensuring they remain relevant in dynamic environments. A significant challenge in developing AI models lies in overcoming the issue of catastrophic forgetting, where models fail to retain previously acquired knowledge when learning new tasks.

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Aiiot Talk

JUNE 27, 2024

Recently, machine learning (ML) integration has revolutionized CRM because it brings a new level of sophistication to customer engagement. ML algorithms analyze vast amounts of data, uncover patterns and provide actionable insights, allowing you to predict consumer behaviour, personalize interactions, and automate routine tasks.

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Pickl AI

FEBRUARY 17, 2025

This scenario highlights a common reality in the Machine Learning landscape: despite the hype surrounding ML capabilities, many projects fail to deliver expected results due to various challenges. What is Machine Learning? This scalability is crucial for businesses looking to harness the full potential of their data assets.

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ODSC - Open Data Science

MARCH 26, 2025

The rapid rise of agentic AI systems and enterprise search solutions suggests that the demand for expertise in these areas will continue to grow in2025. Other high-priority skillsinclude: Advanced ML and deep learning (60%)reflecting interest in deepening technical expertise.

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Marktechpost

JANUARY 10, 2024

Automated Machine Learning (AutoML) has been introduced to address the pressing need for proactive and continual learning in content moderation defenses on the LinkedIn platform. It is a framework for automating the entire machine-learning process, specifically focusing on content moderation classifiers.

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Pickl AI

MARCH 24, 2025

Key Takeaways Adaptive Machine Learning continuously learns from incoming data without manual retraining. Compared to traditional models, adaptive ML enhances prediction accuracy significantly. Adaptive ML improves decision-making by utilizing the most relevant and current data available.

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IBM Journey to AI blog

AUGUST 14, 2023

The newly launched IBM Security QRadar Suite offers AI, machine learning (ML) and automation capabilities across its integrated threat detection and response portfolio , which includes EDR , log management and observability, SIEM and SOAR. The ML app helps your system to learn the expected behavior of the users in your network.

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IBM Journey to AI blog

JANUARY 10, 2024

Data: AI systems learn and make decisions based on data, and they require large quantities of data to train effectively, especially in the case of machine learning (ML) models. The category of AI algorithms includes ML algorithms, which learn and make predictions and decisions without explicit programming.

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Marktechpost

MAY 2, 2024

Learnable activations and symbolic regression methods are explored, highlighting the approach of continuously learned activation functions in KANs. In the study, KANs outperform MLPs in representing functions across various tasks such as regression, solving partial differential equations, and continual learning.

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PyImageSearch

DECEMBER 11, 2023

Kicking Off with a Keynote The second day of the Google Machine Learning Community Summit began with an inspiring keynote session by Soonson Kwon, the ML Community Lead at Google. The focus of his presentation was clear and forward-thinking: Accelerate AI/ML research and application.

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Marktechpost

JULY 23, 2024

Traditionally, academic benchmarks for tabular ML have not fully represented the complexities encountered in real-world industrial applications. Such limitations can lead to overly optimistic performance estimates when models evaluated on these benchmarks are deployed in real-world ML production scenarios.

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Marktechpost

SEPTEMBER 3, 2023

Our findings collectively present a novel brain-inspired algorithm for expectation-based global neuromodulation of synaptic plasticity, which enables neural network performance with high accuracy and low computing cost across a range of recognition and continuous learning tasks. Check out the Paper and Reference Article.

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AWS Machine Learning Blog

MARCH 18, 2025

Continuous learning and improvement As more data is processed, the LLM can continuously learn and refine its recommendations, improving its performance over time. Her work has been focused on in the areas of business intelligence, analytics, and AI/ML.

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