This Week in AI

Sam Altman’s AI predictions rely on a vision for “recursive self improvement” that does not yet exist, at least not publicly.

On TWiAI 36, the panel considers whether or not one frontier lab really could run away with the entire AI game, or if Altman’s “3 pathways forward for AI” prediction rests on a faulty premise?

Are the major labs talking about regulation so much because they’ve seen what kinds of models are coming next? Or just because regulation is good for whoever gets out to an early lead?

Expert panelists Jaleh Rezaei (Mutiny) and Alex Cheema (EXO Labs) join Jason and Lon for a brand-new This Week in AI.

@jason, @jalehr, @alexocheema, @lons, @mutinycorp, @exolabs

0:00 Cold Open / Show Intro
0:58 PayPal - Pay zero processing fees on your first $100K in eligible PayPal payment volume. Learn more at paypal.launch.co
2:56 How much hardware it takes to run local AI models
4:32 DHS orders DeepSeek out of federal systems
5:53 Why enterprise clients are uneasy about Chinese models
9:47 Could an open-source model "phone home" to Beijing?
14:10 Why enterprises are much more price sensitive about AI tools
16:39 Are Sam Altman's AI endgame theories "deranged"?
25:45 Why the major labs want more regulations
26:28 The ElevenLabs Archer controversy continues
34:30 Who actually owns the rights to your voice?
45:17 "Substack for AI Models"
46:20 China needs more chips than Nvidia can make
52:40 Are enterprises running more local models?

🎥 Watch the full episode here 👇

Sam Altman says it’s “quite terrible” that so much of our increasingly scarce DRAM is isolated inside everyone’s home computers instead of being available in the cloud.

But is the answer putting one company in charge of everyone’s compute? Or the Bittensor concept, pooling idle home Macs into shared inference? Or some other strategy?

On TWiAI, Lightmatter’s Nick Harris suggests that, in fact, DRAM will always be considered scarce, as long as AI continues to scale. Chips store information in flat sheets, while brains store it in three dimensions. It’s a bottleneck we can’t escape.

@theanalognick, @PeterMoralesX, @markjeffrey, @LightmatterCo, @Code_Metal_AI, @stillcorecap, @jason, @lons, @sama

1:16 PayPal - Pay zero processing fees on your first $100K in eligible PayPal payment volume. Learn more at paypal.launch.co
3:00 How much should a company spend on AI?
8:40 Engy, Lium, and the road to cheaper inference
14:57 So what's the most you'd pay per month for your agents?
22:06 How unmetered inference changes the way you work
25:33 AI Agent Show & Tell
38:57 Chip stocks sink, lenders pull back from neoclouds
45:02 Dreaming of an agentic Christmas
49:46 Sam Altman hates that you have DRAM
55:01 Leaving math and science's Age of Heroes
1:04:23 Where do the LLMs get election info?
1:15:59 Subscribe to the TWiAI newsletter!

🎥 Watch the full episode here 👇

Runlayer CEO Andy Berman oversees AI rollouts for Fortune 500s. He says the models are ready for enterprise-level work, but the companies aren’t.

“An LLM without access to the right tools and resources, and specifically the data sources, which most companies will not give access to today… is almost useless.”

New TWiAI with @berman66, @runlayer, @johnjnay, @normativeai, @jason and @Lons

0:00 PayPal - Pay zero processing fees on your first $100K in eligible PayPal payment volume. Learn more at paypal.launch.co
1:43 What we learned from Anthropic's S-1
9:30 Why only 2-3% of companies are really using AI
18:03 Jason's "reverse to-do list" agent
23:23 Will AI labs evolve beyond charging per token?
32:36 Browser use is basically solved
41:24 Are colleges giving performative "slop" degrees?
53:00 Why r/opensource banned AI projects
59:39 So what happens to the junior lawyers and analysts?
1:06:01 Peter Thiel's "math people vs. word people" binary

🎥 Watch the full episode here 👇

Is this AI's PC moment?

AI token cost is down.

Models are more efficient.

Open source is now good enough to do most work, and it's private and local.

TWiAI Episode Droppedd!

We had the honor of having @jalehr of @MutinyCorp for today’s roundtable!

Four months after scrapping her $72M-backed SaaS product, Mutiny’s revenue was growing 188% week-over-week, 12x faster than its original launch.

Catch the full episode - link in the comments.