Towards AI

AUGUST 31, 2023

Last Updated on September 1, 2023 by Editorial Team Author(s): Louis Bouchard Originally published on Towards AI. An introduction to explainable AI This member-only story is on us. Powerful artificial intelligence models like DALLE or ChatGPT are super useful and fun to use. Published via Towards AI

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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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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

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

JUNE 26, 2023

Who is responsible when AI mistakes in healthcare cause accidents, injuries or worse? Depending on the situation, it could be the AI developer, a healthcare professional or even the patient. Liability is an increasingly complex and serious concern as AI becomes more common in healthcare. AI Gone Wrong: Who’s to Blame?

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AI News

MARCH 7, 2024

If a week is traditionally a long time in politics, it is a yawning chasm when it comes to AI. But are the ethical implications of AI technology being left behind by this fast pace? Stability AI, in previewing Stable Diffusion 3, noted that the company believed in safe, responsible AI practices.

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IBM Journey to AI blog

JANUARY 25, 2024

We expect technologies such as artificial intelligence (AI) to not lie to us, to not discriminate, and to be safe for us and our children to use. Yet many AI creators are currently facing backlash for the biases, inaccuracies and problematic data practices being exposed in their models. How are you making your model explainable?

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IBM Journey to AI blog

MARCH 4, 2024

We have all been witnessing the transformative power of generative artificial intelligence (AI), with the promise to reshape all aspects of human society and commerce while companies simultaneously grapple with acute business imperatives. We refer to this transformation as becoming an AI+ enterprise.

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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. What is generative AI?

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NVIDIA

MARCH 1, 2024

Trustworthy AI initiatives recognize the real-world effects that AI can have on people and society, and aim to channel that power responsibly for positive change. What Is Trustworthy AI? Trustworthy AI is an approach to AI development that prioritizes safety and transparency for those who interact with it.

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Unite.AI

DECEMBER 13, 2023

AI transforms cybersecurity by boosting defense and offense. However, challenges include the rise of AI-driven attacks and privacy issues. Responsible AI use is crucial. The future involves human-AI collaboration to tackle evolving trends and threats in 2024. Anomaly detection is like having a vigilant guard on duty 24/7.

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IBM Journey to AI blog

OCTOBER 16, 2023

Artificial intelligence (AI) adoption is still in its early stages. As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. ” Are foundation models trustworthy?

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IBM Journey to AI blog

MARCH 7, 2023

The specific approach we took required the use of both AI and edge computing to create a predictive model that could process years of anonymized data to help doctors make informed decisions. With the doctors and nurses in mind, the team aimed to create a model that would allow the intended users to reap its benefits.

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Unite.AI

SEPTEMBER 13, 2023

The remarkable speed at which text-based generative AI tools can complete high-level writing and communication tasks has struck a chord with companies and consumers alike. In this context, explainability refers to the ability to understand any given LLM’s logic pathways.

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LevelAI

DECEMBER 5, 2023

In the realm of artificial intelligence, generative AI has emerged as a transformative force, capable of generating human-quality text, translating languages, and understanding the nuances of human language. Level AI stands out as a pioneer in this domain, setting new standards for enterprise-ready generative AI.

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IBM Journey to AI blog

MAY 9, 2023

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation to become business critical for many organizations. While the promise of AI isn’t guaranteed and may not come easy, adoption is no longer a choice. So what is stopping AI adoption today? It is an imperative.

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LevelAI

DECEMBER 5, 2023

In the realm of artificial intelligence, generative AI has emerged as a transformative force, capable of generating human-quality text, translating languages, and understanding the nuances of human language. Level AI stands out as a pioneer in this domain, setting new standards for enterprise-ready generative AI.

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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. Let us go further into the enigmas of Artificial Intelligence, where AI is making waves like never before! So, don’t worry, this is where Explainable AI, also known as XAI, comes in.

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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.

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Dlabs.ai

JULY 19, 2023

As the incorporation of artificial intelligence (AI) expands, so does the complexity and range of its risks. We delve into the heart of AI’s most pressing issues, bolstered by real-life instances, and lay out clear, actionable strategies to safely traverse this intricate terrain. The answer lies in human oversight.

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Pickl AI

APRIL 8, 2024

Summary: AI’s immense potential is undeniable, but its journey riddle with roadblocks. This blog explores 13 major AI blunders, highlighting issues like algorithmic bias, lack of transparency, and job displacement. 13 AI Mistakes That Are Worth Your Attention 1. 13 AI Mistakes That Are Worth Your Attention 1.

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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). Explainability techniques aim to reveal the inner workings of AI systems by offering insights into their predictions.

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DataRobot Blog

JUNE 23, 2022

Your artificial intelligence (AI) system has given you this “predicted feature” in addition to what you already know about the applicant. In this instance AI is a contributor to the decisions we take because of the prediction it makes. DATAROBOT AI CLOUD. Too often the new model fails the “so what” test. Learn More.

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Defined.ai blog

AUGUST 10, 2023

Welcome to the world of financial data, where every digit has a story to tell, and Artificial Intelligence (AI) assumes the role of a compelling storyteller. With more companies shifting towards data-driven decision-making, understanding financial data and leveraging AI’s power has never been more crucial.

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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. Today, 35% of companies report using AI in their business, which includes ML, and an additional 42% reported they are exploring AI, according to the IBM Global AI Adoption Index 2022.

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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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ODSC - Open Data Science

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Is an AI Coding Assistant Right For You? Here’s how.

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IBM Journey to AI blog

JULY 6, 2023

Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. Because data analysts often build machine learning models, programming and AI knowledge are also valuable. This led to the theory and development of AI. What is machine learning?

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DataRobot Blog

MARCH 15, 2022

Similarly, the desire to harness AI to radically transform the way that services are imagined and delivered is high. We’ve also felt a palpable urgency to harness AI capabilities to address the capacity and staffing challenges that have been amplified as a result of the pandemic. Secure data sharing and AI humility is a necessity.

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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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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? Casual or limited use of AI is exempt.

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Heartbeat

FEBRUARY 2, 2024

As AI strives to emulate human-like understanding, VQA plays a pivotal role by demanding systems to recognize objects and scenes in images and comprehend and respond to human-generated questions about those images. It's remarkable diversity and scale position it as a cornerstone for evaluating and benchmarking VQA algorithms.

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ODSC - Open Data Science

FEBRUARY 22, 2024

Causal AI: from Data to Action Dr. 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. No-Code and Low-Code AI: A Practical Project Driven Approach to ML ​​Gwendolyn D.

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IBM Journey to AI blog

OCTOBER 12, 2023

But the implementation of AI is only one piece of the puzzle. 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.

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Viso.ai

MAY 10, 2024

Basic types of machine learning models Some common types of machine learning algorithms include: Regression models (e.g. Step 4: Train the Model Once we have our selected model and our cleaned dataset with engineered features, we are ready to start training our AI model.

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Heartbeat

SEPTEMBER 7, 2023

Enter Comet , that streamlines the model development process and strongly emphasizes model interpretability and explainability. As we journey deeper into the era of AI , the stakes are higher than ever. Trusting these models is essential, and trust requires understanding. Why Does It Matter?

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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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