howdy, it’s Barsee again.

happy thursday, AI family, and welcome back to AI Valley.

here are the biggest things worth knowing today:

• Figure is moving humanoid robots from prototype to production

• AI spots pancreatic cancer years before doctors

• $130B in AI spending, and supply still can’t meet demand

• Plus trending AI tools, posts, and resources

Let’s dive into the Valley of AI…

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THROUGH THE VALLEY

1/ Figure is moving humanoid robots from prototype to production

Figure AI has gone from producing one humanoid robot per day to one every hour in under 120 days. Inside its BotQ factory in California, it’s now building its third-generation system, Figure 03 (see the reveal), across 150+ workstations with dedicated assembly lines and layered quality checks.

They’ve produced 350+ robots so far and are targeting up to 50,000 per year, which not long ago sounded unrealistic but now looks actively within reach.

Why this matters:

The bottleneck in robotics is shifting. It used to be about not having enough real-world machines to learn from. Now it’s about whether those machines actually hold up in the wild, doing repetitive work over time without quietly breaking down.

If reliability is there, progress compounds because every deployed robot feeds the next iteration. If it isn’t, scale just exposes the problem faster.

2/ AI spots pancreatic cancer years before doctors

At the Mayo Clinic, a model called REDMOD was tested on nearly 2,000 historical CT scans that had already been reviewed and marked as normal. It still identified early signs of pancreatic cancer in 73% of cases, sometimes up to three years before diagnosis. Around the two-year mark, it detected roughly three times more cases than radiologists.

Why this matters

Pancreatic cancer isn’t hard to confirm once it’s obvious. The problem is that by then it’s usually too late to treat effectively, which makes timing everything.

Most attempts to fix this rely on new tests or additional screening, which rarely scale because they add cost, friction, and more decisions into an already complex system.

This approach pulls earlier signals from scans that already exist, moving detection forward without changing behavior. That’s why it has a real chance of becoming standard, not just studied.

3/ $130B in AI spending, and supply still can’t meet demand

Microsoft, Alphabet, Amazon, and Meta together spent around $130 billion in a single quarter, largely driven by AI infrastructure, and still reported the same issue. Demand is ahead of supply.

• Alphabet → $109B revenue (+22%), Cloud +63% to $20B, ~$460B backlog

• Amazon → $181B revenue, AWS +28%, $44B Q1 capex, chips at $20B run rate

• Meta → $56B revenue (+33%), raising capex to as high as $145B

• Microsoft → $82B revenue (+18%), AI revenue at $37B run rate, 20M Copilot users

Why this matters

These companies aren’t struggling to sell AI, they’re struggling to deliver it. Billions in demand are already sitting in backlogs, waiting on infrastructure that hasn’t been built yet.

That shifts the competition toward capacity. The advantage now comes from how quickly you can deploy compute at scale, not just how good your models are.

TRENDING TOOLS

• Gemma 4 > Google launched offline vibe coding with Gemma 4

• Stripe Link Agent Wallet > Let AI agents pay on your behalf without exposing your card, with approval required for every transaction

• Gemini > It can now create Docs, Sheets, Slides, Word docs, Excel files, and more directly in the chat

• Meta TRIBE v2 > A free AI that predicts exactly where your video gets boring BEFORE you publish it

• ElevenMusic > A new platform to discover, remix, create, and earn from music, built on the ElevenLabs music model

• Shipper > Turn any website into an native mobile app

• DeepSeek Vision > A new mode in DeepSeek Chat dedicated to image-understanding tasks.

• Motubrain > ShengShu Technology introduces a new world action model

• SureThing.io > An autonomous agent that delivers results with human-like communication

• Odyssey-2 Max > A causal autoregressive world model enabling real-time, physically accurate simulations through next-state prediction

• Cursor > Released a TypeScript SDK to build and control custom coding agents using the same system behind Cursor

• Cursor Camp > A website to hang out with other cursors

WHAT I'M CONSUMING

• The AI Layoff Trap

• OpenAI's Q4 2026 IPO might not happen

THE VALLEY GEMS

What’s trending on social today:

THAT’S ALL FOR TODAY

Thank you for reading today’s edition. That’s all for today’s issue.

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