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It's Gemini 3 Week! And How to Persuade an LLM to Call You a Jerk

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Manage episode 521715036 series 3703995
Innhold levert av Shimin Zhang & Dan Lasky, Shimin Zhang, and Dan Lasky. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Shimin Zhang & Dan Lasky, Shimin Zhang, and Dan Lasky eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

In this episode of Artificial Developer Intelligence, hosts Shimin and Dan explore the latest developments in AI, including Google's Gemini 3 model and its implications for software engineering. They discuss the rise of AI-driven cybersecurity threats, the concept of world models, and the evolving landscape of software development techniques. The conversation also delves into the ethical considerations of AI compliance and the challenges of running open weight models. Finally, they reflect on the current state of the AI bubble and its potential future.

Takeaways

  • The rent for running AI models is too high.
  • The AI bubble may burst, but it can still leading to innovation.
  • Persuasion techniques can influence AI behavior.
  • World models are changing how we understand AI.
  • Gemini 3 shows significant improvements over previous models.
  • Cybersecurity threats are evolving with AI technology.
  • Software development is becoming more meta-focused.

Resources Mentioned
Disrupting the first reported AI-orchestrated cyber espionage campaign
GTIG AI Threat Tracker: Advances in Threat Actor Usage of AI Tools
Why Fei-Fei Li, Yann LeCun and DeepMind Are All Betting on “World Models” — and How Their Bets Differ
Google's new Gemini 3 model arrives in AI Mode and the Gemini app
Code research projects with async coding agents like Claude Code and Codex
ADK architecture: When to use sub-agents versus agents as tools
I have seen the compounding teams
Call Me A Jerk: Persuading AI to Comply with Objectionable Requests
In Search of the AI Bubble’s Economic Fundamentals
The Benefits of Bubbles | Stratechery by Ben Thompson
Is Perplexity the first AI unicorn to fail?

Chapters

  • (00:00) - Introduction to Artificial Developer Intelligence
  • (02:44) - AI in Cybersecurity: Threats and Innovations
  • (07:35) - World Models: Understanding AI Cognition
  • (11:41) - Gemini 3: A New Era for AI Models
  • (13:31) - Benchmarking AI: The Vending Bench 2
  • (16:18) - Techniques for AI Development
  • (18:59) - Code Search Use Case
  • (22:11) - ADK Architecture
  • (27:27) - Post of the Week: Compounding Teams
  • (31:16) - Persuasion Techniques in AI: A Deep Dive
  • (36:17) - Dan's Rant on The Cost of Running Open-Weight Models
  • (45:09) - 2 Minutes to Midnight
  • (57:45) - Outro

Connect with ADIPod
  continue reading

4 episoder

Artwork
iconDel
 
Manage episode 521715036 series 3703995
Innhold levert av Shimin Zhang & Dan Lasky, Shimin Zhang, and Dan Lasky. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Shimin Zhang & Dan Lasky, Shimin Zhang, and Dan Lasky eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

In this episode of Artificial Developer Intelligence, hosts Shimin and Dan explore the latest developments in AI, including Google's Gemini 3 model and its implications for software engineering. They discuss the rise of AI-driven cybersecurity threats, the concept of world models, and the evolving landscape of software development techniques. The conversation also delves into the ethical considerations of AI compliance and the challenges of running open weight models. Finally, they reflect on the current state of the AI bubble and its potential future.

Takeaways

  • The rent for running AI models is too high.
  • The AI bubble may burst, but it can still leading to innovation.
  • Persuasion techniques can influence AI behavior.
  • World models are changing how we understand AI.
  • Gemini 3 shows significant improvements over previous models.
  • Cybersecurity threats are evolving with AI technology.
  • Software development is becoming more meta-focused.

Resources Mentioned
Disrupting the first reported AI-orchestrated cyber espionage campaign
GTIG AI Threat Tracker: Advances in Threat Actor Usage of AI Tools
Why Fei-Fei Li, Yann LeCun and DeepMind Are All Betting on “World Models” — and How Their Bets Differ
Google's new Gemini 3 model arrives in AI Mode and the Gemini app
Code research projects with async coding agents like Claude Code and Codex
ADK architecture: When to use sub-agents versus agents as tools
I have seen the compounding teams
Call Me A Jerk: Persuading AI to Comply with Objectionable Requests
In Search of the AI Bubble’s Economic Fundamentals
The Benefits of Bubbles | Stratechery by Ben Thompson
Is Perplexity the first AI unicorn to fail?

Chapters

  • (00:00) - Introduction to Artificial Developer Intelligence
  • (02:44) - AI in Cybersecurity: Threats and Innovations
  • (07:35) - World Models: Understanding AI Cognition
  • (11:41) - Gemini 3: A New Era for AI Models
  • (13:31) - Benchmarking AI: The Vending Bench 2
  • (16:18) - Techniques for AI Development
  • (18:59) - Code Search Use Case
  • (22:11) - ADK Architecture
  • (27:27) - Post of the Week: Compounding Teams
  • (31:16) - Persuasion Techniques in AI: A Deep Dive
  • (36:17) - Dan's Rant on The Cost of Running Open-Weight Models
  • (45:09) - 2 Minutes to Midnight
  • (57:45) - Outro

Connect with ADIPod
  continue reading

4 episoder

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