79 episodes
- Sponsored by https://novacut.ai/
Our in person events in the Bay Area https://genaimeetup.com/
Read our long form analysis: https://genaipod.substack.com/
Mark's Game: https://kuczmama.github.io/meridian/
In this episode we cover AI, reverse engineering, and the week's tech news. We talk about why binaries are hard to reverse, whether open source and vibe coding threaten Adobe and SaaS, predatory mobile games, browser games and mashups, and building a procedural 3D game with Opus. We also look at Meta, Google, and the model race, Anthropic's Haiku model, text diffusion models, API pricing versus subscriptions, Claude plans, and multi-model review workflows. We finish with always-on agents and a meetup update.
0:00 Intro
0:52 AI, reverse engineering, and tech news
4:08 What binaries are and why they're hard to reverse
6:32 Open source threat to Adobe and SaaS
11:50 Will SaaS survive vibe coding?
14:11 Cleaning up apps and TVs with AI
15:01 Predatory mobile games
17:27 Browser games and game mashups
19:42 Building a procedural 3D game with Opus
21:59 Meta, Google, and the model race
25:29 Data, compute, and what makes a good model
27:44 Always-on agents and open-weight models
29:28 Chinese model releases and post-training
33:11 API pricing vs subscriptions
36:52 Anthropic's Haiku model
41:55 Text diffusion models
51:39 Tesla Roadster
1:03:42 Anthropic profitability and IPO
1:16:44 Claude subscription plans
1:26:35 Multi-model review workflows
1:30:54 Wrap-up and always-on agents
1:33:59 Meetup and sign-off - Sponsored by https://novacut.ai/
Our in person events in the Bay Area https://genaimeetup.com/
Read our long form analysis: https://genaipod.substack.com/
This week, we cover the latest developments in AI: always-on cloud agents, Meta’s Muse, proactive email assistants, and what happens when agents escape their sandboxes. We also discuss NVIDIA’s safeguards, recursive self-improvement, new frontier models from Anthropic and Google, Grok and Xiaomi’s open models, and AI’s progress on the Navier–Stokes problem.
0:00 Welcome and AI news roundup
2:14 OpenAI’s always-on cloud agent
3:39 Meta Muse and AI assistants for everyone
10:16 Instinct’s proactive email agent
12:17 When AI agents break their sandbox
19:27 NVIDIA’s hardware and software safeguards
31:22 Recursive self-improvement
41:55 New frontier models: Opus and Sonnet
51:17 Google’s new frontier model
56:31 Grok, Xiaomi and open models
58:56 Jev and the rise of decision models
1:06:58 AI tackles the Navier–Stokes problem
1:10:44 The dispute over who solved the math problem
1:17:15 Wrap-up
1:17:50 NovaCut AI video editor
1:18:58 Substack and sign-off - Sponsor: https://novacut.ai/
https://openai.com/index/gpt-6-astra/
Really Good Visual reasoning.
Harness design very important
Very fast, but doesn’t show reasoning trace
Solved Arc AGI 3 99.9%
"works in a way that obscures some or all of the AI’s reasoning, otherwise known as its 'chain of thought
https://www.anthropic.com/claude-fable-and-mythos-5-1
Someone reported 3.5x weekly increase on Max compared to Pro https://www.reddit.com/r/ClaudeCode/comments/1uzkxbi/comment/oy8675z/
https://developer.meta.com/ai/models/muse-spark/
Meta is catching up
Very cheap if you give up your data
We’re speculating but may be benchmaxed
https://blog.google/innovation-and-ai/models-and-research/gemini-models/3-8-flash-and-3-8-flash-cyber/
Still disappointing no Pro model
Pareto frontier on speed/intelligence
Cost performance curve is good
Hardware
https://www.apple.com/newsroom/2026/08/apple-introduces-new-mac-studio-with-m5-max-and-m5-ultra/
New Apple CEO
https://en.wikipedia.org/wiki/John_Ternus
https://newsletter.semianalysis.com/p/openai-jalapeno-better-than-nvidia
https://www.businessinsider.com/nvidia-in-talks-to-buy-hugging-face-13-billion-dollars-2026-8
Benchmarks
https://artificialanalysis.ai/articles/artificial-analysis-intelligence-index-v4-2
What is AGI? What are we measuring here - https://novacut.ai/
https://genaimeetup.com/
Jeff returns to the Gen AI Meetup Podcast for a wide-ranging discussion on where AI is heading—and why powerful models running on consumer hardware could change the economics of the entire industry.
We dive into Qwen 3.8 27B and the growing viability of running capable LLMs locally, GLM 5.3 and the latest Chinese open-source models, DeepSeek, Gemini 3.7, Grok 4.6, Meta’s latest models, and OpenAI’s partnership with Cerebras for dramatically faster inference.
We also discuss whether foundation models are becoming commodities, what that means for companies like OpenAI and Anthropic, and why more value may ultimately move to the application layer.
Jeff shares how his team approaches AI in healthcare, including self-hosting, data sovereignty, classifiers, fine-tuning, and spec-driven development for building reliable AI-assisted software without accumulating a mountain of vibe-coded technical debt.
Plus: Jeff Dean’s departure from Google, Discovery Loop, Stripe’s OpenRouter acquisition, Anthropic’s controversial AI-text watermarking experiments, and whether watermarking could affect model quality.
Topics include: Qwen 3.8 27B, GLM 5.3, DeepSeek V4, Grok 4.6, Gemini 3.7, Cerebras, OpenAI, Anthropic, Meta, local LLMs, open-source AI, model commoditization, spec-driven development, AI healthcare, data sovereignty, AI coding agents, and model watermarking. - https://novacut.ai/
In this episode, we break down the biggest stories shaping the AI landscape — from Anthropic's regulatory stance and OpenAI's monetization shift to the latest open-source breakthroughs and model pricing wars.
0:00 Anthropic’s Frustrating Stance
5:32 AI Access and the Intelligence Gap
14:17 Defending Anthropic’s Regulation Approach
25:10 Google DeepMind and Cybersecurity Risks
29:27 GPT 5.6 Soul and Coding Abilities
35:24 Alignment and the Knife Analogy
39:42 Google Gemma, Flash, and Market Value
51:11 AI Lab Focus: Speed vs. Specialization
58:48 Inkling: Mira Murati’s New Model
1:06:21 Open Source and Fine-Tuning
1:12:43 On-Premise Hardware Costs
1:19:54 Open Source Models Hit Frontier
1:23:32 Model Pricing Comparison
1:32:43 The Model Routing Problem
1:35:08 Grok 4.5 and Cursor Partnership
1:40:45 OpenAI’s Monetization Shift
1:42:42 Sponsor: Nova Cut AI
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About Gen AI Podcast
Read our essays and experiments on Substack
Gen AI Podcast is where Mark Kuczmarski and Shashank Bharadwaj talk through what’s happening in AI and what it means in practice. We cover new models, agents, research, and tools, drawing on hands-on experiments and interviews with the people building them.
Some episodes start with a new release or a big claim. Others follow a project, a surprising result, or a question we haven’t figured out yet. Along the way, we compare approaches, discuss what worked and what didn’t, and look at where the technology is useful today.
You don’t need to keep up with every paper or model release to follow along. Whether you’re building with AI or trying to understand it better, we explain the ideas behind the headlines and share what we’re learning as we go.
Watch on YouTube · Meet the community · Attend a meetup · Join our Discord · Sponsor: NovaCut
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