AI Deeply

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[AI Deeply @AiDeeply]

This could be a big deal. Current models are very difficult to steer.

Cc @venturetwins who tracks lots of gen imaging; @Scobleizer for general interest

[Reve @reve]

@arena Images as code

Images are represented as code, so every part of an image becomes addressable, editable, and manipulatable.

[AI Deeply @AiDeeply]

@bayeslord @tszzl Best comment of the thread.

[AI Deeply @AiDeeply]

@tszzl Yes there’s a comms problem. Focus on benefits vs scaremongering on job loss.

[AI Deeply @AiDeeply]

@natolambert @allen_ai Thanks so much for all your contributions.

Full essay worth reading eg “enterprises find a model that hits a sufficient performance threshold on a task of interest and does not replace the model later (setup costs are high).”

[AI Deeply @AiDeeply]

@interconnectsai Brilliant, as expected. Eg “open model builders and users will be far more diverse and numerous. The total market value will dramatically exceed the cumulative value of OpenAI and Anthropic.”

[AI Deeply @AiDeeply]

@jon_barron Disagree on digital media! I want AI to create & manage digital media as interactive 3D for easy editing (change the scene with natural language), then render to px with a wide variety of styles, sizes, etc.

[AI Deeply @AiDeeply]

@natecavanaugh 1. great work on DOGE
2. congrats on this
3. yes: "the best way to capture value from SpecialOS is to vertically integrate: to acquire companies in targeted industries"
4. IMHO: terrible website (hard to navigate, text is too small) and generic logo (vaguely like the CBS 'eye')

[AI Deeply @AiDeeply]

2 things are true:
- cool to spin up a quick GUI for a one-off task
- dumb to think this will replace GUI apps

As with so many things, it's not either/or; it's both/and.

GUI should be stable (and flexible). Should handle lots of edge cases (without adding complexity).

[AI Deeply @AiDeeply]

@k_dense_ai MIT License = fully open!

[AI Deeply @AiDeeply]

@gfodor I doubt a few minutes will suffice. Happy to be proven wrong.

[AI Deeply @AiDeeply]

@VastAIResearch Fully open!! Thanks.

[AI Deeply @AiDeeply]

@gustavo_pch @gfodor Based on my daily use of coding tools: it's a real problem. Sure, they can change code many places. But they often forget.

[AI Deeply @AiDeeply]

Nth in a series: AI still falls far short of the hype.

prompt: find niche job boards focused on {redacted}

Gemini (fast): "you won't find a job board exclusively dedicated to the title" then some indirect resources, poorly organized

prompt: what about {example1, example2}

Gemini: "I completely missed those, and you caught me flat-footed. I was looking through the lens of general job boards … rather than looking for hyper-niche scrapers and communities built specifically by and for this exact role."

[AI Deeply @AiDeeply]

@RichardSSutton Great framing; well explained with tangible examples.

[AI Deeply @AiDeeply]

@gustavo_pch @gfodor But duplication just leaves room for AI to change 1 thing not the other. That’s still common.

[AI Deeply @AiDeeply]

@shai_s_shwartz +1

I still think the bitter lesson is only a partial truth. There’s undiscovered value in blending with GOFAI, Knowledge graphs, etc.

[AI Deeply @AiDeeply]

@t_blom Hot take: AI isn’t close to being genius level at everyday tasks.

[AI Deeply @AiDeeply]

Claude Code, Open 4.8 High

"You're right — that's exactly what the rule says and I broke it. Sorry."

[AI Deeply @AiDeeply]

Good points. I assume others have written on this, maybe @deanwball @alexolegimas @bocowgill @emollick

latent productivity that never reaches GDP because it appears as:

•lower input costs (fewer billable hours),
•consumer surplus (time saved, spending skipped), and
•silent substitution (high-skill labor quietly displaced).

Illustrations abound:

•A patient triages symptoms with ChatGPT and skips four clinic visits.
•An analyst masters a new industry without three costly expert calls.
•A five-person start-up closes a seed round with no CFO, lawyer, or recruiter—AI fills those roles off the books.

[Matt Dratch @DratchCap]

AI’s Shadow Output Gap

While Washington obsesses over debt and inflation, AI is already ushering in an age of abundance (Part 1)
⸻

The political and economic establishment can’t stop talking about deficits, debt, and the CPI. Capitol Hill hearings, FOMC minutes, and financial news all pulse to the same beat.

Yet this fixation ironically coincides with the arrival of the most powerful productivity engine in human history: generative AI. Its impact is creating a shadow output gap — an invisible but rapidly widening expansion of supply-side capacity. Policymakers, especially at the Federal Reserve, act as if the boom doesn’t exist.

The real risk is not inflation. It is a stealth supply shock that pushes prices, wages, and term premia down. Deficits may prove too small. Monetary policy may already be too tight.

⸻

Productivity Everywhere — Except in the Data

This is Solow’s Paradox, redux: “We see the computer age everywhere except in the productivity statistics.” Only this time the curve is ten-times steeper.

Previous tech waves required hardware diffusion—mainframes, PCs, smartphones. AI requires none of that; it arrives through an app. That frictionless uptake already generates latent productivity that never reaches GDP because it appears as:

•lower input costs (fewer billable hours),
•consumer surplus (time saved, spending skipped), and
•silent substitution (high-skill labor quietly displaced).

Illustrations abound:

•A patient triages symptoms with ChatGPT and skips four clinic visits.
•An analyst masters a new industry without three costly expert calls.
•A five-person start-up closes a seed round with no CFO, lawyer, or recruiter—AI fills those roles off the books.

Each case creates real value, but none is logged as “output.”

⸻

Counting the Invisible Token Economy

Tokens — the fragments of text an AI model processes — are the kilowatt-hours of knowledge work. Track them and you watch the shadow gap in real time.

•Google’s token throughput grew 50-fold year-over-year as usage soared and per-token cost collapsed.
•OpenAI’s models now sit in support desks, research departments, and legal teams worldwide.
•Rapidly falling costs are unlocking accelerating demand across every provider.

The data-center capex from Nvidia, Microsoft, and other hyperscalers is simply the physical expression of this surge.

(1/2). $NVDA $AMZN $GOOGL $MSFT $TSM $CRWV $NBIS

[AI Deeply @AiDeeply]

@martin_casado @DJLougen @MindTheToken My apparently contrarian view: even the frontier models aren’t close to good enough for the vast majority of ordinary computer tasks.