Viso.ai

FEBRUARY 12, 2024

True to its name, Explainable AI refers to the tools and methods that explain AI systems and how they arrive at a certain output. Artificial Intelligence (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.

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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

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning. MLOps and IBM Watsonx.ai

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Unite.AI

SEPTEMBER 20, 2024

Its specialization makes it uniquely adept at powering AI workflows in an industry known for strict regulation and compliance standards. Palmyra-Fin integrates multiple advanced AI technologies, including machine learning, NLP, and deep learning algorithms.

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IBM Journey to AI blog

JULY 6, 2023

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does. Deep learning algorithms are neural networks modeled after the human brain.

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IBM Journey to AI blog

JULY 17, 2023

Generative AI has the potential to significantly disrupt customer care, leveraging large language models (LLMs) and deep learning techniques designed to understand complex inquiries and offer to generate more human-like conversational responses. Watsonx.data allows scaling of AI workloads using customer data.

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Marktechpost

JULY 22, 2024

With deep learning models like BERT and RoBERTa, the field has seen a paradigm shift. Analyzing the decision-making process of AI models is essential for building trust and reliability, particularly in identifying and addressing hidden biases. This is a critical limitation as the demand for explainable AI grows.

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Marktechpost

MAY 8, 2024

Among the main advancements in AI, seven areas stand out for their potential to revolutionize different sectors: neuromorphic computing, quantum computing for AI, Explainable AI (XAI), AI-augmented design and Creativity, Autonomous Vehicles and Robotics, AI in Cybersecurity and AI for Environmental Sustainability.

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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. The output of this can be used for models like XGBoost, GNNs or techniques for clustering, offering better results when deployed for inference.

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Pickl AI

OCTOBER 8, 2024

This blog will explore the concept of XAI, its importance in fostering trust in AI systems, its benefits, challenges, techniques, and real-world applications. What is Explainable AI (XAI)? Explainable AI refers to methods and techniques that enable human users to comprehend and interpret the decisions made by AI systems.

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ODSC - Open Data Science

FEBRUARY 18, 2025

This is not science fiction, as these are the promises of PhD-level AI agentshighly autonomous systems capable of complex reasoning, problem-solving, and adaptive learning. Unlike traditional AI models, these agents go beyond pattern recognition to independently analyze, reason, and generate insights in specialized fields.

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ODSC - Open Data Science

FEBRUARY 25, 2025

Generative AI TrackBuild the Future with GenAI Generative AI has captured the worlds attention with tools like ChatGPT, DALL-E, and Stable Diffusion revolutionizing how we create content and automate tasks. This track provides practical guidance on building and optimizing deep learningsystems.

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Marktechpost

JULY 19, 2023

Researchers have also shown that explainable AI, which is when an AI model explains at each step why it took a certain decision instead of just providing predictions, does not reduce this problem of AI overreliance. Check out the Paper and Stanford Article.

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Heartbeat

SEPTEMBER 13, 2023

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). For example, explainability is crucial if a healthcare professional uses a deep learning model for medical diagnoses.

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Unite.AI

JUNE 24, 2024

Because mathematicians tend to favor elegant solutions over complex machinery, I’ve always tried to emphasize simplicity when applying machine learning to business problems. What are some future trends in AI and data science that you are excited about, and how is Astronomer preparing for them?

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ODSC - Open Data Science

DECEMBER 17, 2024

Types of Data Used in AILending One of AIs greatest strengths is its capacity to handle diverse datasets. Beyond traditional credit scores and income statements, AI models often incorporate behavioral data, transaction patterns, and online activity. For one, AI models inherit biases from the data they are trainedon.

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Pickl AI

SEPTEMBER 17, 2024

This allows cybersecurity teams to focus on high-level strategy and decision-making, while AI handles the day-to-day monitoring and incident response. Moreover, AI enables cybersecurity solutions to adapt and learn from new threats, continuously improving their detection capabilities.

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The MLOps Blog

JUNE 27, 2023

It offers a vast collection of models, including cutting-edge architectures like transformers, for tasks such as text classification, sentiment analysis, and question-answering. You can deploy and scale machine learning models in production, and it supports a wide variety of deep learning frameworks, including TensorFlow, PyTorch, and ONNX.

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Defined.ai blog

AUGUST 10, 2023

Businesses can transform raw numbers into actionable insights by applying AI. For instance, an AI model can predict future sales based on past data, helping businesses plan better. Interpreting these requires a keen understanding of your business context and the specific problem the AI was set to solve.

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Viso.ai

DECEMBER 6, 2023

Therefore, edge devices like servers or computers are connected to cameras and run AI models in real-time applications. Real-Time Computer Vision: With the help of advanced AI hardware , computer vision solutions can analyze real-time video feeds to provide critical insights. Read our article about ethical challenges at OpenAI.

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Viso.ai

JULY 9, 2024

Understanding Generative AI Generative AI refers to the class of AI models capable of generating new content depending on an input. Text-to-image for example, refers to the ability of the model to generate images from a text prompt. Text-to-text models can produce text output based on a text prompt.

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Viso.ai

MARCH 26, 2024

The integration of Artificial Intelligence (AI) technologies within the finance industry has fully transitioned from experimental to indispensable. Initially, AI’s role in finance was limited to basic computational tasks. In turn, these models are typically developed using frameworks like TensorFlow and Keras.

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Pickl AI

APRIL 8, 2024

This experiment highlighted the importance of developing robust security measures for AI systems. Lack of Explainability Many AI systems, particularly deep learning models, known for their “black box” nature. How Can We Ensure the Transparency of AI Systems?

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Heartbeat

SEPTEMBER 7, 2023

Let’s start by understanding why transparency in AI is not just an option but a necessity in today’s world. The Need for Model Interpretability and Explainability In the age of AI, models impact our lives in countless ways. Consider healthcare, where AI models are being used for disease diagnosis.

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ODSC - Open Data Science

FEBRUARY 22, 2024

Join this upcoming training session which will demonstrate how you can use low-code/no-code programming platforms to effectively integrate geospatial analysis with a variety of AI algorithms, including machine learning, deep learning, and Explainable AI. Get your ODSC East Pass today to save 50%.

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ODSC - Open Data Science

JUNE 1, 2023

Top ODSC East 2023 Virtual Sessions Available to Watch for Free With topics ranging from explainable AI to delivering data-driven presentations, these are the top virtual sessions from ODSC East that you can watch for free.

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Viso.ai

APRIL 25, 2024

Bias Detection in Computer Vision: A Guide to Types and Origins Artificial Intelligence (AI) bias detection generally refers to detecting systematic errors or prejudices in AI models that amplify societal biases, leading to unfair or discriminatory outcomes. Do the data agree with harmful stereotypes?

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Snorkel AI

MARCH 19, 2024

In an ideal world, every company could easily and securely leverage its own proprietary data sets and assets in the cloud to train its own industry/sector/category-specific AI models. There are multiple approaches to responsibly provide a model with access to proprietary data, but pointing a model at raw data isn’t enough.

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Snorkel AI

MARCH 19, 2024

In an ideal world, every company could easily and securely leverage its own proprietary data sets and assets in the cloud to train its own industry/sector/category-specific AI models. There are multiple approaches to responsibly provide a model with access to proprietary data, but pointing a model at raw data isn’t enough.

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How to Learn Machine Learning

JANUARY 21, 2023

This market growth can be attributed to factors such as increasing demand for AI-based solutions in healthcare, retail, and automotive industries, as well as rising investments from tech giants such as Google , Microsoft , and IBM. In the years to come, AI is expected to become even more powerful.

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Marktechpost

JULY 11, 2023

Called AutoGPT, this tool performs human-level tasks and uses the capabilities of GPT-4 to develop an AI agent that can function independently without user interference. GPT 4, which is the latest add-on to OpenAI’s deep learning models, is multimodal in nature. Unlike the previous version, GPT 3.5,

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Heartbeat

FEBRUARY 2, 2024

Despite its significance, a thorough analysis uncovers inherent biases within COCO-VQA that have the potential to influence the learning trajectory of AI models. Researchers and developers leverage the VizWiz dataset to advance the development of AI models that enhance the accessibility of visual information.

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DataRobot Blog

DECEMBER 20, 2022

Datarobot enables users to easily combine multiple datasets into a single training dataset for AI modeling. The great thing about DataRobot Explainable AI is that it spans the entire platform. You can understand the data and model’s behavior at any time. Predicting the Real Estate Asset’s Price Using DataRobot.

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IBM Journey to AI blog

SEPTEMBER 3, 2024

Bias Humans are innately biased, and the AI we develop can reflect our biases. These systems inadvertently learn biases that might be present in the training data and exhibited in the machine learning (ML) algorithms and deep learning models that underpin AI development. million in 2024.

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Unite.AI

JULY 1, 2024

For example, AI models used in medical diagnoses must be thoroughly audited to prevent misdiagnosis and ensure patient safety. Another critical aspect of AI auditing is bias mitigation. AI models can perpetuate biases from their training data, leading to unfair outcomes.

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AI Weekly

OCTOBER 12, 2023

pitneybowes.com In The News AMD to acquire AI software startup in effort to catch Nvidia AMD said on Tuesday it plans to buy an artificial intelligence startup called Nod.ai nature.com Ethics The world's first real AI rules are coming soon. [Get your FREE REPORT.] as part of an effort to bolster its software capabilities.

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The MLOps Blog

AUGUST 11, 2023

OpenAI, on the other hand, has been at the forefront of advancements in generative AI models, such as GPT-3, which heavily rely on embeddings. The concept of Explainable AI revolves around developing models that offer inference results and a form of explanation detailing the process behind the prediction.

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