AI Weekly

JUNE 1, 2023

[Apply now] 1west.com In The News Almost 60% of people want regulation of AI in UK workplaces, survey finds Almost 60% of people would like to see the UK government regulate the use of generative AI technologies such as ChatGPT in the workplace to help safeguard jobs, according to a survey. siliconangle.com Can AI improve cancer care?

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Marktechpost

OCTOBER 15, 2024

XAI, or Explainable AI, brings about a paradigm shift in neural networks that emphasizes the need to explain the decision-making processes of neural networks, which are well-known black boxes. Quanda differs from its contemporaries, like Captum, TransformerLens, Alibi Explain, etc.,

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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] Serrano, N.

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IBM Journey to AI blog

SEPTEMBER 24, 2024

Abhisesh Silwal, a systems scientist at Carnegie Mellon University whose research focuses on AI and robotics in agriculture, thinks so. Guerena’s project, called Artemis, uses AI and computer vision to speed up the phenotyping process. We get tired, lose our focus, or just physically can’t see all that we need to.

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ODSC - Open Data Science

APRIL 9, 2025

If you cant bring that context in, youre just very limited in what you can see and do, she explains. Graphs and the Future ofAI As AI systems become increasingly integral to business and society, theres growing recognition that they must operate with more contextual awareness.

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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. If you ask any company what theyd build with an infinite software engineering budget, youll get a long list of projects theyre not getting to, he explained.

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Unite.AI

APRIL 22, 2024

With more than 13 million global users, Ada Health exemplifies transparent, explainable AI in healthcare, providing clear insights into the diagnostic process. It features an AI-powered chatbot that offers round-the-clock support, handling inquiries about cancer care and post-treatment lifestyle practices.

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Marktechpost

JUNE 4, 2024

An emerging area of study called Explainable AI (XAI) has arisen to shed light on how DNNs make decisions in a way that humans can comprehend. Labeling neurons using notions humans can understand in prose is a common way to explain how a network’s latent representations work.

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Marktechpost

MAY 5, 2024

Consequently, there’s been a notable uptick in research within the natural language processing (NLP) community, specifically targeting interpretability in language models, yielding fresh insights into their internal operations. Recent approaches automate circuit discovery, enhancing interpretability.

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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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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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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. Emerging trends in AI, such as reinforcement learning and explainable AI , could further boost Palmyra-Fin's abilities.

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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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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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Heartbeat

SEPTEMBER 7, 2023

In the ever-evolving landscape of machine learning and artificial intelligence, understanding and explaining the decisions made by models have become paramount. Enter Comet , that streamlines the model development process and strongly emphasizes model interpretability and explainability. Why Does It Matter?

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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. Tackling Model Explainability and Bias GNNs also enable model explainability with a suite of tools.

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IBM Journey to AI blog

JULY 6, 2023

Machine learning engineers can specialize in natural language processing and computer vision, become software engineers focused on machine learning and more. to learn more) In other words, you get the ability to operationalize data science models on any cloud while instilling trust in AI outcomes.

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Unite.AI

MAY 24, 2024

In recent years, large language models (LLMs) have made remarkable strides in their ability to understand and generate human-like text. These models, such as OpenAI's GPT and Anthropic's Claude, have demonstrated impressive performance on a wide range of natural language processing tasks.

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IBM Journey to AI blog

AUGUST 11, 2023

Accountability—According to the IBM Global AI Adoption Index 2022 , a majority of organizations haven’t taken key steps to ensure their AI is trustworthy and responsible, such as reducing bias (74%), tracking performance variations and model drift (68%), and making sure they can explain AI-powered decisions (61%).

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Dlabs.ai

JULY 25, 2023

Read on to ensure your recruitment tools and hiring processes remain fair, transparent, and, above all, compliant. Let’s start by explaining what exactly Automated Employment Decision Tools (AEDTs) are. Pymetrics : Uses neuroscience games and AI to match candidates’ cognitive and emotional traits to job requirements.

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Pickl AI

SEPTEMBER 3, 2024

Here are some core responsibilities and applications of ANNs: Pattern Recognition ANNs excel in recognising patterns within data , making them ideal for tasks such as image recognition, speech recognition, and natural language processing. This process typically involves backpropagation and optimisation techniques.

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Pickl AI

SEPTEMBER 17, 2024

Explain The Concept of Supervised and Unsupervised Learning. Explain The Concept of Overfitting and Underfitting In Machine Learning Models. Explain The Concept of Reinforcement Learning and Its Applications. Explain The Concept of Transfer Learning and Its Advantages.

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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

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

JULY 24, 2024

The Golden Age of AI (1960s-1970s) Experts often refer to the 1960s and 1970s as the “Golden Age of AI.” ” During this time, researchers made remarkable strides in natural language processing, robotics, and expert systems. 2011: IBM Watson defeats Ken Jennings on the quiz show “Jeopardy!

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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. Using simple language, it explains how to perform data analysis and pattern recognition with Python and R.

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Pickl AI

SEPTEMBER 17, 2024

Summary : AI is transforming the cybersecurity landscape by enabling advanced threat detection, automating security processes, and adapting to new threats. It leverages Machine Learning, natural language processing, and predictive analytics to identify malicious activities, streamline incident response, and optimise security measures.

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Pickl AI

JANUARY 29, 2024

AI comprises Natural Language Processing, computer vision, and robotics. Skills Proficiency in programming languages (Python, R), statistical analysis, and domain expertise are crucial. ML focuses on enabling computers to learn from data and improve performance over time without explicit programming.

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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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The MLOps Blog

JUNE 27, 2023

For example, if your team works on recommender systems or natural language processing applications, you may want an MLOps tool that has built-in algorithms or templates for these use cases. This includes features for model explainability, fairness assessment, privacy preservation, and compliance tracking.

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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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Pickl AI

AUGUST 1, 2024

This capability allows Deep Learning models to excel in tasks such as image and speech recognition, natural language processing, and more. Multimodal Learning Multimodal learning involves integrating and processing data from multiple sources, such as text, images, and audio, to improve model performance and understanding.

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Heartbeat

FEBRUARY 2, 2024

Visual Question Answering (VQA) stands at the intersection of computer vision and natural language processing, posing a unique and complex challenge for artificial intelligence. is a significant benchmark dataset in computer vision and natural language processing. In xxAI — Beyond Explainable AI Chapter.

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Pickl AI

JULY 14, 2023

Moreover, Deep Learning models, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), achieved remarkable breakthroughs in image classification, natural language processing, and other domains.

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Ofemwire

MARCH 1, 2024

At its core, AI is designed to replicate or even surpass human cognitive functions, employing algorithms and machine learning to interpret complex data, make decisions, and execute tasks with unprecedented speed and accuracy. If you dont get that, let me explain what AI is, like I would do to a fifth grader.

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Pickl AI

APRIL 2, 2024

It explains key concepts, explores applications for business growth, and outlines steps to prepare your organization for data-driven success. Explainable AI (XAI): As AI models become more complex, there’s a growing need for interpretability. Summary This blog post demystifies data science for business leaders.

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ODSC - Open Data Science

OCTOBER 3, 2024

Beyond Interpretability: An Interdisciplinary Approach to Communicate Machine Learning Outcomes Merve Alanyali, PhD | Head of Data Science Research and Academic Partnerships | Allianz Personal Explainable AI (XAI) is one of the hottest topics among AI researchers and practitioners.

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