AI Strategy and Data Quality - Artificial Intelligence Zone

Why data quality is critical for marketing in the age of GenAI

AI News

APRIL 4, 2024

Without that, the AI falls flat, leaving marketers grappling with a less-than-magical reality. AI-powered marketing fail Let’s take a closer look at what AI-powered marketing with poor data quality could look like. I’m excited to use the personal shopper AI to give me an experience that’s easy and customised to me.

Data Quality

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How to build a successful AI strategy

IBM Journey to AI blog

DECEMBER 20, 2023

By giving machines the growing capacity to learn, reason and make decisions, AI is impacting nearly every industry, from manufacturing to hospitality, healthcare and academia. Without an AI strategy, organizations risk missing out on the benefits AI can offer. What is an AI strategy?

AI Strategy

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Basil Faruqui, BMC Software: How to nail your data and AI strategy

AI News

SEPTEMBER 27, 2024

First is clear alignment of the data strategy with the business goals, making sure the technology teams are working on what matters the most to the business. Second, is data quality and accessibility, the quality of the data is critical. Poor data quality will lead to inaccurate insights.

AI Strategy

AI Strategy Automation Data Quality Big Data

Webinars

4 HR Predictions for 2025: Supercharge Your Employee Experience with Internal Communications

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AWS’ Generative AI Strategy Starts to Take Shape and Looks a Lot Like Microsoft’s

TheSequence

DECEMBER 3, 2023

📝 Editorial: AWS’ Generative AI Strategy Starts to Take Shape and Looks a Lot Like Microsoft’s The AWS re:Invent conference has long been regarded as the premier event of the year for cloud computing. Bedrock has emerged as the cornerstone of AWS's generative AI strategy, now supporting Anthropic’s Claude 2.1

AI Strategy

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Narrowing the confidence gap for wider AI adoption

AI News

DECEMBER 9, 2024

The best way to overcome this hurdle is to go back to data basics. Organisations need to build a strong data governance strategy from the ground up, with rigorous controls that enforce data quality and integrity.

Explainability

Explainability AI AI LLM

AI Bias & Cultural Stereotypes: Effects, Limitations, & Mitigation

Unite.AI

OCTOBER 4, 2023

Hence, it is vital to rapidly minimize issues present in Generative AI technologies. Several key strategies can be implemented to reduce bias in AI models. Some of these are: Ensure Data Quality: Ingesting complete, accurate, and clean data into an AI model can help reduce bias and produce more accurate results.

AI

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With generative AI, don’t believe the hype (or the anti-hype)

IBM Journey to AI blog

SEPTEMBER 3, 2024

.” “When we think about applications of AI to solve real business problems, what we find is that these specialty models are becoming more important,” says Brent Smolinksi, IBM’s Global Head of Tech, Data and AI Strategy. In this context, data quality often outweighs quantity.

Generative AI

Generative AI LLM AI AI

Siloed No More: How AI-Driven Tech Stack Consolidation Boosts Revenue

Unite.AI

MARCH 6, 2024

Criteria for an Effective AI Strategy The benefits and transformative power of AI are well documented, but that doesn’t mean organizations should load every AI-powered solution they can find into their shopping carts.

Automation

Automation AI AI AI Tools

How Axfood enables accelerated machine learning throughout the organization using Amazon SageMaker

AWS Machine Learning Blog

FEBRUARY 27, 2024

Monitoring – Continuous surveillance completes checks for drifts related to data quality, model quality, and feature attribution. Workflow A corresponds to preprocessing, data quality and feature attribution drift checks, inference, and postprocessing. Workflow B corresponds to model quality drift checks.

Machine Learning

Machine Learning DevOps Data Scientist Data Quality

LXT’s Report ‘The Path to AI Maturity 2024’: Unmasking the Future of AI Innovation and Corporate Transformation

Unite.AI

MARCH 14, 2024

The demand for high-quality training data is intensifying , with 66% of respondents anticipating an increase in their training data needs over the next two to five years. This underscores the critical role of data in training more sophisticated and accurate AI models.

Computer Vision

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Maximizing compliance: Integrating gen AI into the financial regulatory framework

IBM Journey to AI blog

AUGUST 12, 2024

Compliance with these regulations involves providing clear explanations of AI model decisions, ensuring data privacy, and implementing safeguards against biases and discriminatory practices. Financial institutions must stay informed about evolving regulatory requirements and adapt their AI strategies accordingly.

Automation

Automation Generative AI AI AI

Pascal Bornet, Author of IRREPLACEABLE & Intelligent Automation – Interview Series

Unite.AI

JUNE 17, 2024

For organizations to ensure that AI augments rather than replaces human workers, they need to take a human-centric approach to AI implementation. This means putting people at the heart of their AI strategies and focusing on how the technology can empower and enhance human capabilities. One key aspect is job design.

Automation

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Archana Joshi, Head – Strategy (BFS and EnterpriseAI), LTIMindtree – Interview Series

Unite.AI

NOVEMBER 21, 2024

How does LTIMindtree’s AI platform address concerns around AI ethics, security, and sustainability? As we continue to roll out new AI tools and platforms, we must ensure they meet our standards and regulations around the technology’s use. Our platform is built around the principles of responsible and mindful AI.

DevOps

DevOps Automation Responsible AI Software Development

16 Companies Leading the Way in AI and Data Science

ODSC - Open Data Science

FEBRUARY 28, 2023

Making Data Observable Bigeye The quality of the data powering your machine learning algorithms should not be a mystery. Bigeye’s data observability platform helps data science teams “measure, improve, and communicate data quality at any scale.”

Data Science

Data Science Auto-complete Machine Learning AI

Announcing the 2024 Data Engineering & Ai X Innovation Summits

ODSC - Open Data Science

JANUARY 2, 2024

Join us in the city of Boston on April 24th for a full day of talks on a wide range of topics, including Data Engineering, Machine Learning, Cloud Data Services, Big Data Services, Data Pipelines and Integration, Monitoring and Management, Data Quality and Governance, and Data Exploration.

Data Science

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Generative AI Breakthroughs at ODSC West 2024: 6 Must-Attend Sessions for Business Leaders

ODSC - Open Data Science

OCTOBER 21, 2024

“Day Two” Problems: 5 Hidden Hurdles to GenAI Success and How to Overcome Them Lior Gavish, CTO and Co-Founder of Monte Carlo, addresses the critical operational aspects of rolling out generative AI projects. This talk focuses on the often-overlooked processes related to compliance, quality, and scale.

Generative AI

Generative AI Large Language Models Data Science Software Engineer

Marketing Data and AI: A Guide on What You Need to Know

Defined.ai blog

AUGUST 23, 2023

AI and data analysis skill gaps within organizations can also hinder progress. To tackle this, businesses can consider upskilling existing employees or hiring AI specialists. On an organizational level, resistance to change or lack of a clear AI strategy can stall initiatives.

Machine Learning

Machine Learning Artificial Intelligence Artificial Intelligence Data Quality

AI in Stock Trading : Unlocking Profits

Pickl AI

NOVEMBER 3, 2023

To find trends and patterns traders are now actively using trading and AI strategies like statistical analysis, indicators, and chart patterns. This demonstrated the revolutionary potential of AI in forex trading. Click here to know more about how one can unleash the power of AI and ML for scaling operations and data quality.

Artificial Intelligence

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Best Practice Series #2 – The ROI for AI Projects

Wisdom Works

JUNE 17, 2021

The data may be incomplete, with data quality issues or even missing data that is needed for the success of the model. This will have knock-on implications that add pressure onto the project to solve these issues before the solution can be delivered.

Machine Learning

Machine Learning AI AI Data Science

Best Practice Series #2 – The ROI for AI Projects

Wisdom Works

JUNE 17, 2021

The data may be incomplete, with data quality issues or even missing data that is needed for the success of the model. This will have knock-on implications that add pressure onto the project to solve these issues before the solution can be delivered.

Machine Learning

Machine Learning AI AI Data Science

Mathias Golombek, Chief Technology Officer of Exasol – Interview Series

Unite.AI

MAY 21, 2024

An additional 79% claim new business analysis requirements take too long to be implemented by their data teams. Other factors hindering widespread AI adoption include the lack of an implementation strategy, poor data quality, insufficient data volumes and integration with existing systems.

Software Development

Software Development Business Intelligence ETL Automation

AI Myths Debunked: True & Interesting Facts About AI

Pickl AI

DECEMBER 17, 2024

From virtual assistants like Siri and Alexa to recommendation algorithms on platforms like Netflix, we interact with AI regularly without even realising it. Data Quality Matters While many believe that more data leads to better AI performance, the reality is that quality matters more than quantity.

Artificial Intelligence

Artificial Intelligence Artificial Intelligence Natural Language Processing AI

AI’s Life-Changing, Measurable Impact on Cancer

Unite.AI

NOVEMBER 26, 2024

AI-powered cancer tests that support clinical decision-making for doctors and their patients at every step of the cancer journey – from screening and detection, to identifying the right treatment, and for monitoring patients’ response to interventions and predicting recurrence.

Algorithm

Algorithm AI Strategy Big Data AI Tools

Artificial Intelligence Zone

Why data quality is critical for marketing in the age of GenAI

How to build a successful AI strategy

Webinars

Trending Sources

Basil Faruqui, BMC Software: How to nail your data and AI strategy

Webinars

AWS’ Generative AI Strategy Starts to Take Shape and Looks a Lot Like Microsoft’s

Narrowing the confidence gap for wider AI adoption

AI Bias & Cultural Stereotypes: Effects, Limitations, & Mitigation

With generative AI, don’t believe the hype (or the anti-hype)

Siloed No More: How AI-Driven Tech Stack Consolidation Boosts Revenue

How Axfood enables accelerated machine learning throughout the organization using Amazon SageMaker

LXT’s Report ‘The Path to AI Maturity 2024’: Unmasking the Future of AI Innovation and Corporate Transformation

Maximizing compliance: Integrating gen AI into the financial regulatory framework

Pascal Bornet, Author of IRREPLACEABLE & Intelligent Automation – Interview Series

Archana Joshi, Head – Strategy (BFS and EnterpriseAI), LTIMindtree – Interview Series

16 Companies Leading the Way in AI and Data Science

Announcing the 2024 Data Engineering & Ai X Innovation Summits

Generative AI Breakthroughs at ODSC West 2024: 6 Must-Attend Sessions for Business Leaders

Marketing Data and AI: A Guide on What You Need to Know

AI in Stock Trading : Unlocking Profits

Best Practice Series #2 – The ROI for AI Projects

Best Practice Series #2 – The ROI for AI Projects

Mathias Golombek, Chief Technology Officer of Exasol – Interview Series

AI Myths Debunked: True & Interesting Facts About AI

AI’s Life-Changing, Measurable Impact on Cancer

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