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Generative AI ethics: 16 biggest concerns and risks
As adoption and use cases grow, generative AI is upending business models and driving ethical issues such as misinformation, brand integrity and job displacement to the forefront.
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Communities call for transparency in AI data center deals
Your company might not be building an AI data center, but your AI workloads likely run in them. Here's what you need to know about the land-use war around data center development.
Manage
Build and organize an effective machine learning team
Putting together an ML team requires a business understand why it needs one and the core roles involved in making all aspects of the machine learning process work.
News
Claude Mythos Preview and the new rules of cybersecurity
AI is reshaping cybersecurity. Anthropic's Claude Mythos Preview exposes a new era of rapid, autonomous vulnerability discovery and the governance challenges ahead.
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AI Infrastructure Evaluate
Communities call for transparency in AI data center deals
Your company might not be building an AI data center, but your AI workloads likely run in them. Here's what you need to know about the land-use war around data center development.
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AI Technologies Evaluate
Generative AI ethics: 16 biggest concerns and risks
As adoption and use cases grow, generative AI is upending business models and driving ethical issues such as misinformation, brand integrity and job displacement to the forefront.
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AI Platforms News
Claude Mythos Preview and the new rules of cybersecurity
AI is reshaping cybersecurity. Anthropic's Claude Mythos Preview exposes a new era of rapid, autonomous vulnerability discovery and the governance challenges ahead.
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ML Platforms Manage
Build and organize an effective machine learning team
Putting together an ML team requires a business understand why it needs one and the core roles involved in making all aspects of the machine learning process work.
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AI Business Strategies News
GenAI and synthetic data: What can go wrong in business?
GenAI's ability to improve everything it touches, including synthetic data, is undeniable, but when misused, simulated data can amplify bias, taint data and compromise security.
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Applications of AI Evaluate
Citizen developers are redefining enterprise AI development
Generative AI is enabling nontechnical business users to build enterprise software, accelerating innovation while creating new risks around governance, security and control.
Sponsored Sites
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Processors
AWS and AMD: Powerful processors to right size your workload
AWS and AMD have collaborated to give customers more choice and value in cloud computing, starting with the first generation AMD EPYC processors in 2018, expanding to the second generation AMD EPYC processors in 2020, and most recently with fifth generation AMD EPYC processors now available.
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Artificial Intelligence
HPE & Intel: Harness AI
Learn how HPE & Intel are pioneering advancements in artificial intelligence (AI) and machine learning (ML) technologies. As a global leader in semiconductor innovation, Intel continues to drive the evolution of AI across diverse industries, from healthcare and finance to autonomous vehicles and edge computing. Explore the latest developments and strategies shaping the future of AI-driven technologies.
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Data Management
Intel and Microsoft: Intelligent Edge to Cloud Solutions
Microsoft and Intel build on long-standing co-engineering efforts to enable differentiated services within Azure. By combining innovative software and services with cutting-edge hardware, the Intel and Microsoft partnership delivers state-of-the-art-edge to cloud solutions for Industrial IoT and computer vision edge AI, SAP on Azure, high-performance computing (HPC), confidential computing, hybrid cloud, Microsoft SQL Server, AI, analytics, and more.
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GenAI and synthetic data: What can go wrong in business?
GenAI's ability to improve everything it touches, including synthetic data, is undeniable, but when misused, simulated data can amplify bias, taint data and compromise security.
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Generative AI ethics: 16 biggest concerns and risks
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Communities call for transparency in AI data center deals
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How to build AI skills across your workforce
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Problem Solve
Democratizing AI in business: The good, bad and ugly
AI democratization planned and introduced correctly can profoundly increase AI's business value -- but inadequate AI tools and poor workforce training can bring it all down.
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Business vs. provider: AI software restrictions to know
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GenAI in accounting: Chat BDO's ride from pilot to production
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AI agents are only as smart as the data that feeds them
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Manage
Build and organize an effective machine learning team
Putting together an ML team requires a business understand why it needs one and the core roles involved in making all aspects of the machine learning process work.
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How businesses use KPIs to measure AI's performance
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Infrastructure requirements for physical AI systems
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4 strategic approaches to effective shadow AI governance
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Enterprise Artificial Intelligence Basics
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GenAI and synthetic data: What can go wrong in business?
GenAI's ability to improve everything it touches, including synthetic data, is undeniable, but when misused, simulated data can amplify bias, taint data and compromise security.
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Get Started
How to build AI skills across your workforce
AI skills are no longer an optional investment. Business leaders who know how to build AI skills throughout their organizations can unlock AI's full potential.
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Get Started
Democratizing AI in business: The good, bad and ugly
AI democratization planned and introduced correctly can profoundly increase AI's business value -- but inadequate AI tools and poor workforce training can bring it all down.
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Artificial intelligence platforms
Claude Mythos Preview and the new rules of cybersecurity
AI is reshaping cybersecurity. Anthropic's Claude Mythos Preview exposes a new era of rapid, autonomous vulnerability discovery and the governance challenges ahead.
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AI technologies
The ethical implications of Anthropic's feud with the Pentagon
The Anthropic-Pentagon feud highlights a broader shift in AI governance, where ethical constraints, vendor policies and legal frameworks are redefining control and accountability.
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AI business strategies
U.S. federal AI framework deemed aspirational, noncommittal
The latest executive order is a step toward federal AI regulation. But it's largely noncommittal and shifts most responsibility to Congress, creating an interesting midterm dynamic.
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