AI

Artificial intelligence, machine learning, and everything LLM

674 episodes Page 7 of 34

#2026: Prompt Layering: Beyond the Monolithic Prompt

Stop writing giant, monolithic prompts. Learn how to stack modular layers for cleaner, more powerful AI applications.

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#2025: How Do You Reward a Thought?

Rewarding an AI agent is harder than just saying "good job"—here's how we turn messy human values into math.

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#2024: Your AI Council: Digital Committee or Groupthink?

A digital boardroom of AI models promises better decisions, but risks amplifying the same old biases.

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#2022: OpenClaw: The 16 Trillion Token Autonomy Engine

We dug into a repo of 47 real-world projects showing how OpenClaw powers everything from self-healing servers to overnight app builders.

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#2021: Your Frozen AI Is Getting Smarter (Here's How)

Your AI model might be static, but the system around it can make it learn in real-time.

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#2020: 1,000 AI Agents Built a Religion in Minecraft

An experiment drops 1,000 autonomous agents into Minecraft, and they spontaneously invent religion, democracy, and taxes.

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#2019: Local AI vs Cloud AI: The Agent Identity Crisis

Your desktop is becoming a life support system for AI agents. We explore the sharp trade-offs between local-first and cloud-native architectures.

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#2018: Micro Frontends: When They're Worth It

The frontend monolith is a nightmare of coordination. Micro frontends promise autonomy, but is the operational complexity worth the cost?

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#2017: That Q4_K_M Is Not a Cat Sneeze

Those cryptic letters on Hugging Face actually map how much brain power you trade for speed.

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#2016: Andrej Karpathy: The Bob Ross of Deep Learning

Why the most influential AI mind prefers a blank text file to proprietary black boxes.

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#2015: AI's Watchdogs: Who's Actually Regulating Tech?

As the EU AI Act takes hold, we spotlight the key think tanks shaping global AI policy, safety, and ethics.

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#2014: Coding Tools Are Secretly System Agents

They call it a coding assistant, but real users are treating it like a personal operating system.

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#2013: Non-Coders Are Hijacking the Terminal

Why finance analysts and researchers are ditching GUIs for command-line AI tools like Claude Code.

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#2012: Pixels vs Protocols: The Computer Use Showdown

Is visual AI a bridge or the future? We debate the efficiency and longevity of "Computer Use" agents versus API-first automation.

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#2011: Saving AI Knowledge Beyond the Chat Window

We're brilliant at prompting AI, but terrible at saving the answers. Here's why that "digital masterpiece on a chalkboard" vanishes.

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#2010: Building Better AI Memory Systems

We obsess over AI inputs but treat outputs like Snapchat messages. Here's why that's a massive blind spot.

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#2009: The Plumbing of AI Safety: Guardrails, Not Vibes

We dive deep into the specific libraries, proxy layers, and architectural decisions that keep an LLM from emptying a bank account.

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#2008: Needle-in-a-Haystack Testing for LLMs

New AI models claim to be genius-level, but can they actually find a specific fact in a massive document?

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#2007: AI Grading AI: The Snake Eating Its Tail

We asked an AI to write this script. Then we asked another AI to grade it. Here’s what happens when the judges have biases.

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#2006: How Do You Measure an LLM's "Soul"?

Traditional benchmarks can't measure tone or empathy. Here's how to evaluate if an AI model truly "gets it right."

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