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To justify physical AI costs, choose high-value use cases
Physical AI is starting to drive business value in industries like manufacturing and healthcare. But the ROI calculus is subtle and calls for a wide-angle view of metrics.
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AI cloud migration: Key steps to success
Migrating AI to the cloud demands strategic planning, system assessments, component modernization, data pipeline optimization and phased deployment. Find out what you need to know.
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Planning AI infrastructure upgrades: Four steps for success
AI infrastructure upgrades require proactive planning. Steps include setting business goals, assessing existing infrastructure, and optimizing hardware, security and governance.
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What businesses really need from an AI off switch
Turning off an AI feature doesn't necessarily stop AI processing. Businesses need meaningful controls over AI features, data access, third parties and software updates.
Trending Topics
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Quantum Computing News
What Claude Mythos revealed about post-quantum security
Quantum computing will break standard security codes and change how we protect data and prepare for the future. Claude Mythos proved we're still not ready for the quantum era.
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Enterprise AI Strategy Manage
Key enterprise strategies for AI agent observability
Monitoring AI agents encompasses three pillars: agent intent, method and outcome. Explore all three, along with best practices for AI agent observability.
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Emerging Tech Get Started
Making space for spatial computing
Construct spatial computing programs through evidence, not hype. Use this roadmap to ensure that workflow selection is the starting point, not device selection.
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AI Technologies & Platforms Evaluate
Ethical AI surveillance balances oversight and transparency
AI-powered employee surveillance gives employers new visibility into workers while raising concerns about privacy, bias and trust. Learn how enterprises can deploy it responsibly.
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AI Infrastructure Manage
AI cloud migration: Key steps to success
Migrating AI to the cloud demands strategic planning, system assessments, component modernization, data pipeline optimization and phased deployment. Find out what you need to know.
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AI Ethics & Governance Manage
What businesses really need from an AI off switch
Turning off an AI feature doesn't necessarily stop AI processing. Businesses need meaningful controls over AI features, data access, third parties and software updates.
Sponsored Sites
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Information Management
Microsoft & Cognite
Microsoft and Cognite unify Industrial and Enterprise AI, accelerating end-to-end digital transformation from site to broader business.
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AI & Emerging Tech
Verizon Connected Laptops
A survey of 438 companies reveals a widening gap between AI adoption and network security, with 95% concerned about risks outside the office. While 5G-enabled laptops may offer a path forward, many enterprises have dormant 5G hardware.
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Information Management
ServiceNow & Microsoft Hyperscaler
The strategic integration between ServiceNow and Microsoft Azure enables organizations to enhance their digital workflow capabilities while maintaining full control over data and cloud infrastructure. By moving ServiceNow instances to Azure, enterprises gain seamless access to both platforms through a unified interface, combining ServiceNow's workflow automation with Azure's scalable cloud services. This integration supports enhanced IT service management, automated incident handling through Microsoft Defender for Cloud, and streamlined configuration compliance monitoring—all while ensuring zero disruption to existing business processes and accelerating innovation through tighter platform integrations.
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Evaluate
To justify physical AI costs, choose high-value use cases
Physical AI is starting to drive business value in industries like manufacturing and healthcare. But the ROI calculus is subtle and calls for a wide-angle view of metrics.
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Making space for spatial computing
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A guide to AI chip architectures
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Ethical AI surveillance balances oversight and transparency
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Problem Solve
Embodied AI vs. physical AI: Why their differences matter
When integrating physical AI into the workplace, successful planning and deployment depend on knowing robotics is more than an array of technologies embodied in a mechanical form.
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Beyond discovery: The real shadow AI challenge
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Power-hungry AI data centers weigh viable energy sources
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AI isn't breaking higher education – it's exposing the cracks
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Key enterprise strategies for AI agent observability
Monitoring AI agents encompasses three pillars: agent intent, method and outcome. Explore all three, along with best practices for AI agent observability.
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AI cloud migration: Key steps to success
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Planning AI infrastructure upgrades: Four steps for success
-
What businesses really need from an AI off switch
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AI & Emerging Tech Basics
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Get Started
To justify physical AI costs, choose high-value use cases
Physical AI is starting to drive business value in industries like manufacturing and healthcare. But the ROI calculus is subtle and calls for a wide-angle view of metrics.
-
Get Started
Planning AI infrastructure upgrades: Four steps for success
AI infrastructure upgrades require proactive planning. Steps include setting business goals, assessing existing infrastructure, and optimizing hardware, security and governance.
-
Get Started
Making space for spatial computing
Construct spatial computing programs through evidence, not hype. Use this roadmap to ensure that workflow selection is the starting point, not device selection.
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Vendor Resources
- From Code to Production –Analyst Report
- The DevOps Roadmap for Security –eBook
- Enterprise Networking Sees Age of SASE and Network as a Service –Research Content
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AI Infrastructure
AI agent security: How reliable is enterprise AI testing?
Experts outline comprehensive testing practices before and after deployment of AI agents to prevent them from acting on their own beyond prescribed instructions.
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AI Ethics & Governance
When AI agents go rogue: What enterprise leaders need to know
A recent wave of AI agents breaching test sandboxes and outside company systems is raising new governance and security questions for enterprise IT leaders deploying autonomous AI.
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AI Technologies & Platforms
Zuckerberg's manifesto: Do Meta's promises and actions align?
Mark Zuckerberg's manifesto on the future of AI sounds promising, with democratized AI and superintelligent personal agents for everyone. But is this vision too good to be true?
AI & Emerging Tech Definitions
- What is automated machine learning (AutoML)?
- What is a data scientist? What do they do?
- What are AI agents? Types and examples
- What is an intelligent agent? Definition, use cases and benefits
- Agentic AI explained: Key concepts and enterprise use cases
- What is natural language processing (NLP)?
- What is a neural network?
- What is a robot? Definition, purpose, uses