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AI governance can make or break data monetization
As pressures mount for businesses to get the most value from their data, AI governance ensures the data to be monetized is secure, protected, trustworthy and used responsibly.
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Optimizing hybrid cloud architecture for AI workloads
Hybrid cloud architecture can help with the unique scalability, hardware and governance needs of AI workloads. But is it the right choice for your business?
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4 types of machine learning models explained
Rigorous experimentation is key to building machine learning models. Learn about the main types of ML models and the factors that go into picking and training them for a specific task.
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Setting the stage for 2026: Continuing AI pragmatism
Physical AI adoption, shifts in generative AI dominance and sovereign AI's rise in Europe and India are some predictions for 2026, according to Omdia's Mark Beccue.
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Optimizing hybrid cloud architecture for AI workloads
Hybrid cloud architecture can help with the unique scalability, hardware and governance needs of AI workloads. But is it the right choice for your business?
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Why business leaders must explore post-quantum pre-quantum
With the continual advance of quantum technology comes threats to traditional cryptographic standards. Discover how to prepare for PQC pre-quantum.
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AI Platforms Get Started
AI governance can make or break data monetization
As pressures mount for businesses to get the most value from their data, AI governance ensures the data to be monetized is secure, protected, trustworthy and used responsibly.
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ML Platforms Get Started
4 types of machine learning models explained
Rigorous experimentation is key to building machine learning models. Learn about the main types of ML models and the factors that go into picking and training them for a specific task.
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AI Business Strategies Evaluate
Setting the stage for 2026: Continuing AI pragmatism
Physical AI adoption, shifts in generative AI dominance and sovereign AI's rise in Europe and India are some predictions for 2026, according to Omdia's Mark Beccue.
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How generative AI is changing creative work
As generative AI accelerates concepting and production, creative teams are evolving, requiring new skills, governance models and stronger human insight to guide meaningful work.
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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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Accelerating Application Transformation with Amazon Q Developer
Amazon Q Developer transformation capabilities accelerate large-scale transformation of enterprise workloads with domain-expert generative AI agents to simplify .NET porting, VMware modernization, mainframe application modernization, and Java upgrades. Put experience of AWS and the power of generative AI to work to simplify your application migration and modernization journey and transform your business.
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Artificial Intelligence
AWS and Deloitte
Your potential is our purpose. Innovation is not just about generating ideas; it’s about realizing your potential through solutions that spark real progress. The Deloitte AWS alliance brings together two world-leading organizations, putting best-in-class talent, vast industry experience, broad capabilities, and the resources to invest deeply in innovation, at the service of our clients’ most pressing problems. Together, we empower you to navigate the future confidently and turn potential into business outcomes.
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Why business leaders must explore post-quantum pre-quantum
With the continual advance of quantum technology comes threats to traditional cryptographic standards. Discover how to prepare for PQC pre-quantum.
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AI governance can make or break data monetization
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Setting the stage for 2026: Continuing AI pragmatism
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11 emerging technologies to watch in 2026
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How to build an AI-augmented workforce: The CIO's guide
An AI-augmented workforce pairs humans with AI to boost performance. Learn ways to build it, review examples, know the challenges and explore future trends shaping enterprise roles.
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Integrate and modernize legacy systems with AI
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Strategies to reduce machine learning bias
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3 enterprise AI horror stories for CISOs from 2025
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How to prepare your business for agentic AI adoption
Agentic AI adoption can go awry without a clear plan in place. Use this guide to ensure AI agents are deployed correctly and optimized for successful business outcomes.
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10 AI topics for 2026 that enterprise leaders need to know
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AI regulation: What businesses need to know in 2026
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9 top generative AI tool categories for 2026
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Enterprise Artificial Intelligence Basics
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Why business leaders must explore post-quantum pre-quantum
With the continual advance of quantum technology comes threats to traditional cryptographic standards. Discover how to prepare for PQC pre-quantum.
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Get Started
AI governance can make or break data monetization
As pressures mount for businesses to get the most value from their data, AI governance ensures the data to be monetized is secure, protected, trustworthy and used responsibly.
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Optimizing hybrid cloud architecture for AI workloads
Hybrid cloud architecture can help with the unique scalability, hardware and governance needs of AI workloads. But is it the right choice for your business?
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AI's impact on Google search engine antitrust ruling
While some believe the ruling was too light, it does emphasize the role of GenAI vendors as competitors in the market.
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Artificial intelligence platforms
Anthropic announces $13B fundraise, $183B valuation
While the vendor's valuation is still far away from OpenAI's, investors still have confidence in the vendor -- especially as it focuses on enterprise safety and coding.
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AI technologies
The implications of OpenAI's speech model gpt-realtime
While the new model is beneficial for the expressiveness of voices, it also shows how blurry the lines are between human and AI voices.
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