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Category Podcast

In The Loop Episode 9 | Apple’s AI Crisis Exposed: Is It Having A Nokia Moment?

Table of contents
Apple Intelligence: false advertising, embarrassment, and a deepening crisis
Why people should be worried about Apple?
1. Hardware vs. software
2. Vertical integrations
3. Lack of urgency in innovation
What could Apple do to stay in the AI game
1. Acquire a large language model provider.
2. Build an AI agent-first operating system
3. Win big in voice and wearables
4. Invest in robotics (eventually)
Closing thoughts
Jack Houghton
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Category Blog

When To Use Agentic RAG—And What Is It Anyway?

Table of contents
What is the difference between RAG and agentic RAG?
Why do we need agentic RAG?
Is normal RAG better than agentic RAG?
When to use agentic RAG?
1. When creating adaptive learning paths
2. When supporting diverse learning modalities
3. When enhancing assessment and feedback loops
4. When localizing and contextualizing global content
Anna Kocsis
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Category Blog Thought Leadership

AI Expert Interview: The Benefits And Drawbacks Of Agentic AI

Table of contents
What are the benefits of agentic AI?
In summary, the benefits of agentic AI are:
What are the drawbacks of agentic Ai?
In summary, the drawbacks of agentic AI are:
What are the risks of agentic AI?
In summary, the risks of agentic AI are:
Will AI agents replace humans?
Exciting future developments in agentic AI
Conclusion
Barrie Hadfield Wic Verhoef
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Category Blog

Agentic AI 101: Everything You Ever Wanted To Know About AI Agents But Never Dared Ask

Table of contents
What is an AI agent in simple words?
Examples of agentic systems
What is the main task of an AI agent?
Understanding the architecture of an AI agent
Core Principles of AI Agents
How do AI agents work?
The Four Fundamental Rules of AI Agents
What’s the difference between horizontal, vertical, narrow agents?
Horizontal AI agents
Vertical AI agents
Narrow AI agents
What types of agentic systems are there? (For The Technical Reader)
Workflow or GUI agent: How to choose
Workflow agents
GUI agents
Other comparable AI paradigms
How are AI agents trained?
Benefits, risks, and challenges
Conclusion: Are AI agents just hype?
Anna Kocsis
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Category Podcast Podcast

In The Loop Episode 1 | DeepSeek’s AI Breakthrough: Hype or Game-Changer? A No-Nonsense Breakdown

Table of contents
What is China’s DeepSeek Ai?
What did DeepSeek do different
How AI models are created and ran
What’s so great about DeepSeek?
Improvement #1: 8-bit floating-point numbers
Improvement #2: Compress key-value memory by 93%
Improvement #3: Predict multiple words at once
Improvement #4: Mixture of Experts (MoE)
Debate: Did DeepSeek use distillation?
How distillation works
What DeepSeek actually did…
What this means for AI
Why this was misunderstood
Why DeepSeek is a big deal
Reason #1: It's come at a time of big geopolitical tension
Reason #2: A new scaling law - AI Is moving from training to inference
Reason 3: Reduced costs through open-source and commoditized models
Reason #4: Big Techin frenzy: Is it time to go bigger and more expensive?
Market reaction, winners, and losers—My take
Why did DeepSeek affect NVIDIA?
Jack Houghton
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