IBM Journey to AI blog

AUGUST 9, 2024

Generative AI (gen AI) is artificial intelligence that responds to a user’s prompt or request with generated original content, such as audio, images, software code, text or video. Gen AI models are trained on massive volumes of raw data. What is predictive AI?

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Unite.AI

OCTOBER 20, 2023

AI models in production. Today, seven in 10 companies are experimenting with generative AI, meaning that the number of AI models in production will skyrocket over the coming years. As a result, industry discussions around responsible AI have taken on greater urgency. In 2022, companies had an average of 3.8

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Unite.AI

FEBRUARY 25, 2025

Imandra is dedicated to bringing rigor and governance to the world's most critical algorithms. The company has built a cloud-scale automated reasoning system, enabling organizations to harness mathematical logic for AI reasoning.

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Automation Neural Network Explainability Algorithm 100

Unite.AI

DECEMBER 27, 2024

Heres the thing no one talks about: the most sophisticated AI model in the world is useless without the right fuel. Data-centric AI flips the traditional script. Instead of obsessing over squeezing incremental gains out of model architectures, its about making the data do the heavy lifting. Why is this the case?

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IBM Journey to AI blog

JANUARY 25, 2024

Yet many AI creators are currently facing backlash for the biases, inaccuracies and problematic data practices being exposed in their models. These issues require more than a technical, algorithmic or AI-based solution. How might this insight affect evaluation of AI models? How are you assessing fairness?

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Unite.AI

SEPTEMBER 23, 2024

Critics point out that the complexity of biological systems far exceeds what current AI models can fully comprehend. While generative AI is excellent at data-driven prediction, it struggles to navigate the uncertainties and nuances that arise in human biology. One major hurdle is the ‘black box’ nature of AI algorithms.

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Unite.AI

NOVEMBER 22, 2024

Artificial Intelligence (AI) is making its way into critical industries like healthcare, law, and employment, where its decisions have significant impacts. However, the complexity of advanced AI models, particularly large language models (LLMs), makes it difficult to understand how they arrive at those decisions.

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ODSC - Open Data Science

NOVEMBER 30, 2023

Healthcare systems are implementing AI, and patients and clinicians want to know how it works in detail. Explainable AI might be the solution everyone needs to develop a healthier, more trusting relationship with technology while expediting essential medical care in a highly demanding world. What Is Explainable AI?

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IBM Journey to AI blog

OCTOBER 12, 2023

The tasks behind efficient, responsible AI lifecycle management The continuous application of AI and the ability to benefit from its ongoing use require the persistent management of a dynamic and intricate AI lifecycle—and doing so efficiently and responsibly. Here’s what’s involved in making that happen.

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Unite.AI

APRIL 9, 2024

The adoption of Artificial Intelligence (AI) has increased rapidly across domains such as healthcare, finance, and legal systems. However, this surge in AI usage has raised concerns about transparency and accountability. Composite AI is a cutting-edge approach to holistically tackling complex business problems.

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Unite.AI

DECEMBER 13, 2023

Ultimately, staying updated empowers enthusiasts to leverage the full potential of AI and make confident decisions in their professional and personal pursuits. AI-Powered Threat Detection and Response AI takes the lead in making the digital world safer.

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IBM Journey to AI blog

JUNE 26, 2023

What is generative AI? Generative AI uses an advanced form of machine learning algorithms that takes users prompts and uses natural language processing (NLP) to generate answers to almost any question asked. You can start by learning more about the advances IBM is making in new generative AI models with watsonx.ai

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Unite.AI

MARCH 18, 2024

As generative AI technology advances, there's been a significant increase in AI-generated content. This content often fills the gap when data is scarce or diversifies the training material for AI models, sometimes without full recognition of its implications.

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Unite.AI

SEPTEMBER 13, 2023

Increasingly though, large datasets and the muddled pathways by which AI models generate their outputs are obscuring the explainability that hospitals and healthcare providers require to trace and prevent potential inaccuracies. In this context, explainability refers to the ability to understand any given LLM’s logic pathways.

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Dlabs.ai

AUGUST 16, 2022

One of the major hurdles to AI adoption is that people struggle to understand how AI models work. This is the challenge that explainable AI solves. Explainable artificial intelligence shows how a model arrives at a conclusion. What is explainable AI? Let’s begin.

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TransOrg Analytics

FEBRUARY 11, 2025

These are just a few ways Artificial Intelligence (AI) silently influences our daily lives. As AI continues integrating into every aspect of society, the need for Explainable AI (XAI) becomes increasingly important. What is Explainable AI? Why is Explainable AI Important?

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Marktechpost

JULY 6, 2023

Furthermore, there is very little tolerance for error as ML models gain popularity in a number of crucial industries, like medical diagnostics, credit card fraud detection, etc. As a result, it becomes necessary for humans to comprehend these algorithms and their workings on a deeper level.

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Towards AI

JULY 22, 2023

Last Updated on July 24, 2023 by Editorial Team Author(s): Data Science meets Cyber Security Originally published on Towards AI. Now Algorithms know what they are doing and why! Let us go further into the enigmas of Artificial Intelligence, where AI is making waves like never before! SOURCE: [link] A.

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ODSC - Open Data Science

JANUARY 29, 2025

It is a critical aspect of making AI systems more effective in real-world applications as it helps bridge the gap between humans and machines through contextual understanding. Grounded AI models have improved accuracy and reliability, enabling them to better interpret the nuances of human language and behavior.

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IBM Journey to AI blog

SEPTEMBER 20, 2023

Foundational models (FMs) are marking the beginning of a new era in machine learning (ML) and artificial intelligence (AI) , which is leading to faster development of AI that can be adapted to a wide range of downstream tasks and fine-tuned for an array of applications.

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NVIDIA

MARCH 1, 2024

Developers of trustworthy AI understand that no model is perfect, and take steps to help customers and the general public understand how the technology was built, its intended use cases and its limitations. Privacy: Complying With Regulations, Safeguarding Data AI is often described as data hungry.

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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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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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Unite.AI

SEPTEMBER 20, 2024

This transition from static, rule-based systems to adaptive, learning-based models opened new opportunities for market analysis. Key milestones in this evolution include the advent of algorithmic trading in the late 1980s and early 1990s, where simple algorithms automated trades based on set criteria.

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IBM Journey to AI blog

JULY 6, 2023

Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention. Deep learning algorithms are neural networks modeled after the human brain. Some people worry that AI and machine learning will eliminate jobs.

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Flipboard

JUNE 20, 2023

Understanding AI’s mysterious “opaque box” is paramount to creating explainable AI. This can be simplified by considering that AI, like all other technology, has a supply chain. AI models are also created and delivered via supply chains. What factors does it weigh?

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Towards AI

OCTOBER 3, 2024

Ongoing Challenges: – Design Complexity: Designing and training these complex networks remains a hurdle due to their intricate architectures and the need for specialized algorithms.– These chips have demonstrated the ability to process complex algorithms using a fraction of the energy required by traditional GPUs.–

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IBM Journey to AI blog

FEBRUARY 8, 2023

Adherence to responsible artificial intelligence (AI) standards follows similar tenants. Gartner predicts that the market for artificial intelligence (AI) software will reach almost $134.8 Manual processes can lead to “black box models” that lack transparent and explainable analytic results. billion by 2025.

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Unite.AI

JANUARY 12, 2024

Processing multiple data streams strains compute resources, demanding optimized model architectures. Advances in attention mechanisms and algorithms are needed to integrate contradictory multimodal inputs. Enhancing user trust via explainable AI also remains vital.

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

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Mlearning.ai

DECEMBER 31, 2023

Principles of Explainable AI( Source ) Imagine a world where artificial intelligence (AI) not only makes decisions but also explains them as clearly as a human expert. This isn’t a scene from a sci-fi movie; it’s the emerging reality of Explainable AI (XAI). What is Explainable AI?

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Dlabs.ai

JULY 19, 2023

Example: Algorithmic Bias in the UK A-level Grading To illustrate, consider a real-world example that occurred during the COVID-19 pandemic in the UK. With the traditional A-level exams canceled due to health concerns, the UK government used an algorithm to determine student grades.

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IBM Journey to AI blog

JULY 17, 2023

While traditional AI approaches provide customers with quick service, they have their limitations. 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. Watsonx.ai

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Towards AI

APRIL 2, 2024

However, the AI community has also been making a lot of progress in developing capable, smaller, and cheaper models. This can come from algorithmic improvements and more focus on pretraining data quality, such as the new open-source DBRX model from Databricks. X’s Grok Chatbot Will Soon Get an Upgraded Model, Grok-1.5

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AWS Machine Learning Blog

NOVEMBER 15, 2024

Robustness in AI systems makes sure model outputs are consistent and reliable under various conditions, including unexpected or adverse situations. A robust AI model maintains its functionality and delivers consistent and accurate outputs even when faced with incomplete or incorrect input data.

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Dlabs.ai

JULY 25, 2023

In an era where AI and machine learning have streamlined everything, including hiring processes, the balance between efficiency and equity comes into question. With algorithms, machine learning, and statistical modeling defining who gets hired or promoted, are these decisions genuinely fair? Who do AEDT Regulations address?

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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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