IBM Journey to AI blog

JUNE 26, 2023

Possibilities are growing that include assisting in writing articles, essays or emails; accessing summarized research; generating and brainstorming ideas; dynamic search with personalized recommendations for retail and travel; and explaining complicated topics for education and training. in 2022 and it is expected to be hit around USD 118.06

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Marktechpost

APRIL 24, 2024

To ensure practicality, interpretable AI systems must offer insights into model mechanisms, visualize discrimination rules, or identify factors that could perturb the model. Explainable AI (XAI) aims to balance model explainability with high learning performance, fostering human understanding, trust, and effective management of AI partners.

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Marktechpost

JANUARY 19, 2024

Researchers have proposed a deep learning prediction model named XAI-AGE (XAI stands for Explainable AI) that integrates previously identified biologically hierarchical information in a neural network model for predicting the biological age based on DNA methylation data.

Neural Network 102

Neural Network Deep Learning Explainable AI Explainability 102

Towards AI

FEBRUARY 22, 2024

If you are excited to dive into applied AI, want a study partner, or even want to find a partner for your passion project, join the collaboration channel! Mh_aghajany is looking for fellow learners to explore Machine Learning, Deep Learning, and LLM. Our friends at Zoī are hiring their Chief AI Officer.

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Large Language Models AI AI Explainability 101

Marktechpost

MAY 12, 2024

It is based on adjustable and explainable AI technology. The technology provides automated, improved machine-learning techniques for fraud identification and proactive enforcement to reduce fraud and block rates. CorgiAI CorgiAI is a fraud detection and prevention tool designed to increase income and reduce losses due to fraud.

AI Tools 85

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ODSC - Open Data Science

FEBRUARY 13, 2023

Well according to our research, there is quite a lot going on in the world of machine learning safety and security. Explainable AI: As in the namesake, explainable AI’s purpose is to clearly and in a transparent manner, explain why a machine learning model came to a specific decision.

Machine Learning 98

Machine Learning Explainability Data Science Explainable AI 98

Mlearning.ai

FEBRUARY 6, 2023

This is why we need Explainable AI (XAI). Attention mechanisms have often been touted as an in-built explanation mechanism, allowing any Transformer to be inherently explainable. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Serrano, N.

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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

Currently chat bots are relying on rule-based systems or traditional machine learning algorithms (or models) to automate tasks and provide predefined responses to customer inquiries. Enterprise organizations (many of whom have already embarked on their AI journeys) are eager to harness the power of generative AI for customer service.

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Unite.AI

APRIL 9, 2024

Composite AI is a cutting-edge approach to holistically tackling complex business problems. These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Transparency is fundamental for responsible AI usage.

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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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IBM Journey to AI blog

AUGUST 11, 2023

MLOps is the next evolution of data analysis and deep learning. Simply put, MLOps uses machine learning to make machine learning more efficient. Generative AI is a type of deep-learning model that takes raw data, processes it and “learns” to generate probable outputs.

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Pickl AI

JULY 14, 2023

Big Data and Deep Learning (2010s-2020s): The availability of massive amounts of data and increased computational power led to the rise of Big Data analytics. Deep Learning, a subfield of ML, gained attention with the development of deep neural networks.

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ODSC - Open Data Science

FEBRUARY 22, 2024

Andre Franca | CTO | connectedFlow Join this session to demystify the world of Causal AI, with a focus on understanding cause-and-effect relationships within data to drive optimal decisions. By the end, you will be ready to harness the platform for advanced spatial analysis and the development of sophisticated AI models.

Machine Learning 52

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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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Defined.ai blog

AUGUST 10, 2023

Emerging Trends in AI and Financial Data Analysis In the fast-evolving field of AI, new trends are constantly emerging, and financial data analysis is no exception. Let’s look at a few trends shaping the future of data analysis using AI.

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Marktechpost

AUGUST 24, 2023

r/neuralnetworks The Subreddit is about Deep Learning, Artificial Neural Networks, and Machine Learning. members and is a great place to learn more about the latest AI. It has over 37.4k members and has active discussions on various ML topics. It features various posts and regular discussions on these topics.

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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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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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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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Mlearning.ai

JANUARY 26, 2023

When it comes to implementing any ML model, the most difficult question asked is how do you explain it. Suppose, you are a data scientist working closely with stakeholders or customers, even explaining the model performance and feature selection of a Deep learning model is quite a task. How do we deal with this?

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Heartbeat

FEBRUARY 2, 2024

In xxAI — Beyond Explainable AI Chapter. Editor's Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners. Salewski, L., Koepke, A. Lensch, H. A., & Akata, Z.

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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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Dlabs.ai

MAY 22, 2022

The instructors are very good at explaining complex topics in an easy-to-understand way. Machine Learning Author: Andrew Ng Everyone interested in machine learning has heard of Andrew Ng : one of the most respected people in the AI world. These skills are a must-have if you plan to work with Google Cloud.

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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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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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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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Viso.ai

APRIL 25, 2024

While bias in AI systems is a well-established research area, the field of biased computer vision hasn’t received as much attention. However, it is worth noting that even though this class imbalance has a significant impact, they do not explain every disparity in the performance of machine learning algorithms.

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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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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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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. Overcoming the ‘black box’ nature of AI for transparent and explainable AI systems.

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Viso.ai

DECEMBER 6, 2023

Real-Time Computer Vision: With the help of advanced AI hardware , computer vision solutions can analyze real-time video feeds to provide critical insights. The most common example is security analytics , where deep learning models analyze CCTV footage to detect theft, traffic violations, or intrusions in real-time.

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The MLOps Blog

JUNE 27, 2023

This includes features for model explainability, fairness assessment, privacy preservation, and compliance tracking. Truera Truera is a model intelligence platform designed to enable the trust and transparency of machine learning models. Learn more from the documentation. Monitor the performance of machine learning models.

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DataRobot Blog

DECEMBER 20, 2022

The great thing about DataRobot Explainable AI is that it spans the entire platform. Understand & Explain Models with DataRobot Trusted AI. DataRobot AI Platform tries to bridge the gap between model development and business decisions while maximizing transparency at every step of the ML & AI lifecycle.

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Mlearning.ai

SEPTEMBER 5, 2023

Our AI technologies meticulously sift through Big Data, capturing valuable nuggets often overlooked by traditional dashboards and reports. This report not only ranks your insights but deciphers them too, courtesy of eXplainable AI. Next, we introduce “Lean Reporting” with a single-page layout.

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Snorkel AI

MARCH 19, 2024

Google’s thought leadership in AI is exemplified by its groundbreaking advancements in native multimodal support (Gemini), natural language processing (BERT, PaLM), computer vision (ImageNet), and deep learning (TensorFlow).

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Snorkel AI

MARCH 19, 2024

Google’s thought leadership in AI is exemplified by its groundbreaking advancements in native multimodal support (Gemini), natural language processing (BERT, PaLM), computer vision (ImageNet), and deep learning (TensorFlow).

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