IBM Journey to AI blog

OCTOBER 16, 2023

. “Foundation models make deploying AI significantly more scalable, affordable and efficient.” It’s essential for an enterprise to work with responsible, transparent and explainable AI, which can be challenging to come by in these early days of the technology. ” Are foundation models trustworthy?

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Unite.AI

JULY 2, 2024

Navigating this new, complex landscape is a legal obligation and a strategic necessity, and businesses using AI will have to reconcile their innovation ambitions with rigorous compliance requirements. GDPR's stringent data protection standards present several challenges for businesses using personal data in AI.

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Unite.AI

JULY 1, 2024

Automated tools can streamline this process, allowing real-time audits and timely interventions. Transparency and Explainability Enhancing transparency and explainability is essential. Tools like IBM's AI Fairness 360 provide comprehensive metrics and algorithms to detect and mitigate bias.

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Unite.AI

SEPTEMBER 13, 2023

AI developers for highly regulated industries should therefore exercise control over data sources to limit potential mistakes. Generative AI-powered chatbots could help alleviate much of the workload and preserve overextended patient access teams.

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Aiiot Talk

JULY 7, 2023

AI can streamline and automate key safety processes such as design, monitoring, testing and more. AI-Powered Predictive Maintenance AI is a powerful tool for improving aircraft safety through predictive analytics. Generative AI can also pose risks for aviation industry applications.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

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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. These are the mathematical formulas written to simulate functions of the brain, which underlie the AI programming.

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ODSC - Open Data Science

FEBRUARY 18, 2025

Recent breakthroughs include OpenAIs GPT models, Google DeepMinds AlphaFold for protein folding, and AI-powered robotic assistants in industrial automation. These innovations enable AI to transition from tool-like applications to fully autonomous problem-solvers.

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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. AI Engineering TrackBuild Scalable AISystems Learn how to bridge the gap between AI development and software engineering.

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Viso.ai

JANUARY 21, 2025

They are suitable for various advanced high-precision computer vision applications like medical imaging, autonomous vehicles, and industrial automation. Moreover, their ability to handle large datasets with fewer resources makes them a game-changer in AI development. In computer vision, for example, its a game changer.

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Pickl AI

JANUARY 29, 2024

Opportunities abound in sectors like healthcare, finance, and automation. As we navigate this landscape, the interconnected world of Data Science, Machine Learning, and AI defines the era of 2024, emphasising the importance of these fields in shaping the future. How does AI differ from Machine Learning?

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Pickl AI

APRIL 8, 2024

Job displacement One of the biggest fears surrounding AI is that it will automate many jobs currently performed by humans, leading to widespread unemployment. While AI will undoubtedly change the job market, the extent of job displacement remains uncertain. How Can We Ensure the Transparency of AI Systems?

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The MLOps Blog

FEBRUARY 27, 2025

See in the app Full screen preview All metadata in a single place with an experiment tracker (example in neptune.ai) Integrate bias checks into your CI/CD workflows If your team manages model training through CI/CD, incorporate the automated bias detection scripts (that have already been created) into each pipeline iteration.

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Pickl AI

JANUARY 13, 2025

It simplifies complex AI topics like clustering , dimensionality , and regression , providing practical examples and numeric calculations to enhance understanding. Key Features: Explains AI algorithms like clustering and regression. Key Features: Explores AIs impact on humanity. Discusses ethical challenges of AI.

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IBM Journey to AI blog

SEPTEMBER 3, 2024

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. Those learned biases might be perpetuated during the deployment of AI, resulting in skewed outcomes.

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IBM Journey to AI blog

FEBRUARY 28, 2024

IBM watsonx™ , an integrated AI, data and governance platform, embodies five fundamental pillars to help ensure trustworthy AI: fairness, privacy, explainability, transparency and robustness. This platform offers a seamless, efficient and responsible approach to AI development across various environments.

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Pickl AI

DECEMBER 29, 2024

Societal and Economic Implications of Irresponsible AI Irresponsible AI can widen social inequities, harm marginalised communities, and destabilise economies. Automation without accountability risks mass unemployment, while AI-driven misinformation can erode democratic institutions.

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NVIDIA

MARCH 18, 2025

For AI factories, intelligence isnt a byproduct but the primary one. This intelligence is measured by AI token throughput the real-time predictions that drive decisions, automation and entirely new services.

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Pickl AI

DECEMBER 10, 2024

Businesses face fines and reputational damage when AI decisions are deemed unethical or discriminatory. Socially, biased AI systems amplify inequalities, while data breaches erode trust in technology and institutions. Broader Ethical Implications Ethical AI development transcends individual failures.

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ODSC - Open Data Science

OCTOBER 3, 2024

In this talk, you will explore how the speaker progressively rethought this process, building machine learning tools that require less wrangling, including a new library, skrub, that facilitates complex tabular-learning pipelines, writing as much as possible wrangling as high-level operations and automating them.

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AI Weekly

AUGUST 22, 2024

Here’s why that’s a problem Using generative large language models (LLMs) like those behind ChatGPT and other AI chatbots, the system can brainstorm, select a promising idea, code new algorithms, plot results, and write a paper summarising the experiment and its findings, complete with references. pdf, Word, etc.) into their platform.

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IBM Journey to AI blog

FEBRUARY 9, 2024

According to a recent IBM survey of over 1,000 employees at enterprise-scale companies , the top three factors driving AI adoption were advances in AI tools that make them more accessible, the need to reduce costs and automate key processes and the increasing amount of AI embedded into standard off-the-shelf business applications.

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