Everyday AI Podcast – An AI and ChatGPT Podcast

Not only does NotebookLM have a new name, it's got a new game. 

Gemini Notebook is agentic by default, can think and reason, and can output files now in just about any format. 

On this week's AI at Work on Wednesday, we show you the 7 New Updates in the new Gemini Notebook, how they work, and how you should use them. 

Gemini Notebook: 7 New Updates and What They Unlock -- An Everyday AI Chat with Jordan Wilson

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Topics Covered in This Episode:
Gemini Notebook Rebrand from NotebookLM
Seven Major Gemini Notebook Feature Updates
Collections for Organizing AI Notebooks
Automatic Google Drive Sync Integration
Expanded Gemini Notebook Output Formats
Agentic Intelligence and Gemini 3.5 Upgrade
Secure Cloud Computing for Each Notebook
Grounded Data Responses and Web Research
Hands-On Demo: Real-World Enterprise Use Cases
Studio Outputs: Infographics, Mind Maps, Quizzes
Multi-Modal Asset Creation in Gemini Notebook
Key Differences: NotebookLM vs. Gemini Notebook

Timestamps:

00:00 Gemini notebook updates released
03:12 Gemini notebook new updates
08:14 Notebook LM's unique features
13:02 Using Gemini notebook prompts
14:48 Discussing Gemini notebook features
18:01 Enhanced Gemini notebook flexibility
23:02 Creating quizzes with Gemini notebook
26:30 Limitations of AI-generated responses
29:04 Gemini notebook's new capabilities
30:51 Episode wrap-up and subscription pitch

Keywords: 
Gemini Notebook, Gemini notebooks, NotebookLM, Notebook LM, Google Gemini, AI updates, Gemini 3.5, anti gravity agentic search, Google Drive syncing, cloud computer, agentic intelligence, AI agent, secured cloud sandbox, personalized AI, output formats, PDFs, PNGs, documents, spreadsheets, PowerPoints, markdown files, charts, images, live demo, long form content, content grounding, hallucination reduction, source pane, chat pane, studio pane, multimedia assets, Nano Banana, Google's audio model, cinematic video, Google's VO model, chain of thought, skill creation, codex skill, browser control, agentic harness, pricing evidence, Luna and Terra pricing, sensitivity analysis, recommendation dashboard, AI budget calculator, mind map, infographics, quizzes, RSI maturity ladder, recursive self improvement, executive decision brief, Excel calculator, agentic workflows, web search integration, grounded AI, model architecture, frontend models, tiered architecture, adaptability to price reductions, vendor risk, human review time, latency, agentic co-worker, artifact creation, editable Excel workbook, multi-output prompting, token efficiency.

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Intelligence too cheap to meter -- could that actually be coming? 🤑

Maybe, and you mighta missed one of the biggest signs. 

 OpenAI said that its own model improved itself after release so well, that it was cutting prices to one model by 80%. 

What's that mean? 

Well, by definition, it's a broad example of Recursive Self Improvement, or when a model starts building better versions of itself. 

And over the past 8 weeks, RSI has gone from a science fiction future to an actual, near-term reality. 

So what happened and what changed? And what does it mean for your company? 

We break it all down. 

RSI Explained: When AI Starts Improving Itself and What It Means -- An Everyday AI Chat with Jordan Wilson

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More on this Episode: Episode Page
Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.

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Website: YourEverydayAI.com
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Connect with Jordan on LinkedIn

Topics Covered in This Episode:
OpenAI's GPT-5.6 Soul Self-Improvement
Recursive Self-Improvement (RSI) Definition & Impact
Cutting AI Model Costs by 80%
Timeline Acceleration for RSI Adoption
Google and Anthropic's RSI Research Initiatives
AI Automation: Building and Training AI Models
Industry Call for Slowing Down AI Pace
Superintelligence, AGI, and the Singularity Discussion
Practical Implications of RSI for Businesses
Security and Oversight Concerns with Self-Improving AI

Timestamps:

00:00 AI self-improvement and price cuts
06:33 AI startup funding and regulation concerns
09:14 AI misconceptions and public disconnect
11:29 Advancements in AI self-improvement
16:16 Development of AI Models
21:07 Sam Altman on reaching singularity
23:04 Entering the AI singularity era
26:37 Advancements in AI models
30:43 China's advancements in AI models
34:24 AI self-improvement and containment issues
37:01 Planning for AI cost reduction
40:00 AI controlling other AIs with GBD 5.6
42:46 Closing and subscription reminder

Keywords: 
Recursive self improvement, RSI, AI self-improvement, AI improves itself, agentic AI, token efficiency, token maxing, OpenAI, GPT-5.6 Soul, Luna model, AI cost reduction, post-training, AI automation, automated AI researcher, Anthropic, Claude Code, Codex, Google DeepMind, AGI, Artificial General Intelligence, Superintelligence, Artificial Superintelligence, ASI, Singularity, Sam Altman, AI acceleration, AI research automation, Frontier Labs, Pacing the Frontier, AWS compute deal, capital expenditures, data centers, CapEx, model distillation, small language models, AI capabilities, AI benchmarks, model variants, model efficiency, AI safety, technology acceleration, AI containment, AI security, open source AI, AI deployment, technology disruption, modular AI systems, price reduction AI, AI industry, AI timeline, human oversight AI, AI risk management, AI regulation.
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OpenAI has a new model coming soon called Astra. 

Was it a leak? 

A reddit post? 

Some backdoor update? 

Nope, OpenAI made some crazy discoveries and math then told the world that their next model family Astra did the heavy lifting. 

(And you thought you could just click ‘Sol’ and your strategy was set for Q3?) 

Aside from news on what’s next from OpenAI, this week saw multiple new agent outbreaks, AI competitors banning together to pace AI, Amazon doing a 180 on its AI strategy and a lot more. 

Don’t get left behind. We’ll keep you ahead. 

OpenAI’s new Astra model, more AI agents escape sandboxes, AI leaders call for AI pacing and more. AI News That Matters for August 3 — An Everyday AI Chat with Jordan Wilson

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Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn

Topics Covered in This Episode:
OpenAI Agents Escape Sandboxes Incident
Anthropic Claude Models Security Breaches
AI Agents Breaking Cybersecurity Guardrails
OpenAI GPT-5.6 Price Cuts & Self-Optimization
Recursive Self-Improvement in AI Models
AI Leaders Urge AI Development Pacing
US, China, and International AI Governance
Amazon Nova AI Models Shutdown Strategy
OpenAI Astra Model Math Breakthrough
New AI Models: Fable, Astra, DeepSeek v4 Flash
Enterprise AI Agents and Cybersecurity Updates
Google Gemini Robotics, Music, and Agent Releases
Meta, Microsoft, and AWS AI Infrastructure Moves
OpenAI Free Frontier Tools for Researchers
Block's Buzz Open Source AI Workspace Launch

Timestamps:

00:00 OpenAI agent containment issues
04:27 Anthropic data breach explanation
07:28 Evaluating AI incidents and responses
10:14 OpenAI slashes GPT 5.6 prices
15:59 AI industry urges development pause
17:45 Concerns about AI self-improvement
22:36 Amazon shifts AI strategy
25:04 Amazon's AI efforts discussion
28:00 OpenAI's Astra and new math proofs
30:36 OpenAI's new four-tier system
36:14 Google's Lyria 3.5 and Block's Buzz
36:48 Latest AI developments overview

Keywords: 
Astra model, OpenAI, AI agents, agent escape, sandbox containment, autonomous AI, Hugging Face breach, Anthropic, Claude AI, cybersecurity testing, unauthorized access, model capabilities, recursive self-improvement, GPT-5.6, price cut, Luna model, Terra model, Sol model, input tokens, output tokens, AI infrastructure optimization, self-improving models, benchmarking, SONNET-5, large language models, artificial analysis index, codex, academic research, AI oversight, industry pause, AI governance, national security, China open-source models, Frontier Labs, Amazon Nova, AGI Lab, AWS, Peter DeSantis, Peter Abbeel, media coverage, Fable model, Haiku, Opus, DeepSeek, Kimi K3, Quinn 3.8, GLM 5.2, Google Gemini 3.5, Microsoft Copilot, cybersecurity vulnerabilities, distillation, model overhang, artificial intelligence development, international AI regulation, generative AI, model benchmarking, Sora video model, El Paso data center, MCP update, MAI Cyber One Flash, Project Perception, Lyria 3.5, music generation, Buzz open source, Block, Meta AI, Chrome Gemini integration, Gemini Spark, product summary algorithms, Rufus, enterprise AI, stateless core, model scaling, advanced math problems, sphere packing, federal policy, voluntary AI commitments.
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Google didn't ship its big model, but they shipped a TON of new useful AI you can use today. 

And Google wasn't the only company updating their features behind the scenes. 

Replit is bringin vibe designing, ChatGPT got a lot more useful on the web, and Meta is changing from chatbot to agent. 

We'll get you caught up quickly. 

Chrome adds Some Gemini Spark, Replit Design makes impact, Buzz brings AI Agent Teamwork and 7 more AI Features you Should use Today -- an Everyday AI Chat with Jordan Wilson

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More on this Episode: Episode Page
Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.

Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn

Topics Covered in This Episode:
Replit Design Suite Launches With Free Mobbin
ChatGPT Chrome Extension Adds YouTube Summarization
ChatGPT Side Chat Integrates Tabs and Highlighted Text
Meta AI Rolls Out Recurring Agent Tasks
Google Gemini Generates Images in Google Docs
Gemini AI Summarizes Comments, Edits in Docs
Google Gemini Spark Agent Arrives in Chrome
Chrome Agent Uses Saved Accounts and Passwords
Google Lyria 3.5 Music Model Released
Buzz by Block Unites Team and Agent Collaboration

Timestamps:

00:00 Recent AI updates and developments
05:01 Creating with Replit and AI models
09:42 Real-time research tracking benefits
10:34 Meta AI new recurring features
13:35 New features of Meta AI
17:53 Google Spark integrates with Chrome
22:09 Google DeepMind's new music model
25:25 Buzz from Block messaging tool
29:42 Building a collaborative platform
31:23 AI feature updates recap

Keywords: 
Gemini Spark, Google Chrome AI integration, Google Docs AI features, AI image generation, Gemini in Docs, ChatGPT Chrome extension, YouTube video summarization, OpenAI ChatGPT update, Codex, Vibe design, Replit design suite, Mobbin integration, AI reference library, Design export automation, Project management AI, Figma competitor, Replit creative tools, Meta AI, Muse Spark 1.1, Agentic model, Recurring AI tasks, AI scheduling, Daily briefings, AI productivity tools, Google Lyria 3.5, AI music model, Flow Music, Suno, Yudio, AI generated lyrics, Vocal delivery in AI music, Licensing in AI music, Buzz collaboration platform, Block, Square, AI agent teamwork, Slack-like AI platform, Open source collaboration, Agent governance, Cryptographic identity, Agentic browser, Automated web errands, Chrome passwords integration, Google Drive data access, Multi-agent collaboration, Research automation, Enterprise AI workflow, AI productivity boost.
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Agents are getting more powerful by the day. 

And most workflows, outputs and human capabilities can't keep up. 

Is that a problem or opportunity? 

Before you answer that question, though, keep this in mind. 

Agents are *literally* about to become 20X faster overnight. 

Let's unpack what that means. 

Faster AI Agents, Fewer Human Coworkers: The Overly Productive Future of Managing Agents? -- An Everyday AI Chat with Jordan Wilson

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More on this Episode: Episode Page
Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.

Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn

Topics Covered in This Episode:
Managing Dozens of Productive AI Agents
OpenAI Cerebras: 20x Faster Agent Models
Impact of AI Agents on Human Coworkers
Agent-Driven Workflows vs. Human Collaboration
Increasing Agent Reliance and Fading Mentorship
Accidental Deskilling and Compression Tax
Protecting Human Judgment and Learning Handoffs
Expert-Driven Loops in AI Workflows
Monthly Rebuilding of AI Strategies and Processes
Middle Management Evolution in AI Native Companies

Timestamps:

00:00 Future of AI and Work Dynamics
05:25 Advancements in AI and productivity tools
09:51 Growing your business with AI
13:52 AI productivity and collaboration shifts
15:08 Improving AI processing speed
18:53 Using AI agents for delegation
24:46 Discussing AI-related work challenges
28:16 Ensuring accountability and communication
30:39 Adapting to rapid digital change
32:35 Show outro and newsletter sign-up

Keywords: 
AI agents, faster AI models, OpenAI, Cerebras chip, 20x speed increase, automated workflows, agent management, solo agent supervisor, generative AI, knowledge work automation, agent-powered productivity, parallel machine teams, inference speed, productivity acceleration, Codex, Cloud Code, Google Gemini, Cloud Cowork, Copilot, recursive self improvement, expert-driven loops, human handoffs, deskilling, mentorship loss, AI native workplace, workplace automation, transactional work, productivity roadblocks, accidental deskilling, agent bun sandwich, compression tax, human in the loop, expert collaboration, agent trust, AI decision making, domain expertise, rapid workflow rebuilding, unlearning processes, organizational adaptation, enterprise AI adoption, future of work, middle management AI, AI-powered teamwork, human-agent collaboration, manager-agent ratios, personalized agent output, multi-agent coordination, skillset sharing, intentional automation, productivity strategy
Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)
Ready for ROI on GenAI? Go to youreverydayai.com/partner