Forbidden

i don't know what to put here | thoughts on AI + tech + culture

[Jeffrey Katzenberg @jeffreykWNDR]

The World is Changing: AI For Creativity

By Jeffrey Katzenberg

A few months ago, I sat in my office in Silicon Valley and watched as a tech founder showed me something extraordinary. On the screen was a fully realized, beautifully lit, well-composed animated scene. It was stunning and it made me feel exactly what I felt in 1986 watching Luxo Jr. That was the first time I watched a computer-animated 3D character take a breath and seem, against all reason, to have life. It left me in awe.

Later that day, I received a text from an artist I've known for thirty years, 350 miles to the south, in the city where I spent most of my career. After seeing a similar video, she texted: "Is this the end of us?" My answer was, "Certainly not.”

I have spent the better part of the last decade in Silicon Valley, but the heart of my career has been in Hollywood. Being deeply connected to both worlds means I have deep loyalties to each and a responsibility to speak honestly to both.

In 2023, I said that these new AI tools would cut the time and cost of producing world-class animation by as much as ninety percent within three years. Some colleagues were alarmed, many were furious.

There is growing fear and resistance surrounding AI within the creative community. I deeply understand it, because I've spent countless hours walking through animation studios watching gifted artists bent over their desks, rebuilding a single second of film for the tenth time because the ninth version wasn't quite right. I've sat in screening rooms where four years of people's labor played out in minutes, and I knew the name of every person that had spent countless hours bringing those images to life. The creative process is a calling, there's really no other way to describe it. From the outside some see resistance. From the inside, it is love.

People do not fight this hard for things they don't care about. The pushback coming out of Hollywood represents the collective effort of people who are deeply passionate about their craft.

Is History Repeating Itself?

The history here is more complicated than either side may realize. In 1906, the most famous composer in America, John Philip Sousa, published an essay titled “The Menace of Mechanical Music." He warned that the phonograph would become "a substitute for human skill, intelligence and soul."

Sousa's fight was not really about the machine, it was about money. The machines were playing his compositions, and the men who built them weren't paying him a cent. His campaign helped create the Copyright Act of 1909. He did not stop the technology. He changed the terms under which it could use his work.
A hundred years ago, sound came to the movies. We remember it now as a miracle, and it was. What we forget is who paid for it. Before sound, tens of thousands of musicians made their living in the orchestra pits of movie houses, scoring every film live, every night, in towns all over the world. When the soundtrack arrived, the work of one composer and one orchestra was recorded for a film that went into thousands of theaters. The union fought back with everything it had, taking out newspaper ads across the country warning against the menace of "canned music," one of them showing a mechanical man tearing the strings out of a harp while an angel wept.

They were not fools, and they were not Luddites. They were right. Those pit jobs did not come back. And yet (this is the part we have to be brave enough to admit), sound gave us the movie musical, the modern score, sfx, sound design, audio engineering, and an art form vastly larger than the one it disrupted. And it helped keep Hollywood in the forefront of world entertainment for the rest of the century and into the next. The loss was real. And yet the art form expanded.

This is a story that has been told over and over again. To resist technology is to risk irrelevance. Just look at Kodak or Blockbuster. To embrace technology is to open doors of new possibility. Just consider Apple and Netflix.

What I Learned From Walt Disney

In the mid-1980s, I was tapped to lead Disney's animation division at a moment when the studio was at an inflection point. Animation wasn't just another business unit. It was the soul of the company, a medium revered because of Walt's genius and his passion. But the production system was cumbersome and unforgiving. A single movie was 125,000 individual hand-drawn and painted cels, photographed one frame at a time. Every revision carried a cost measured in months. These degrees of difficulty shaped the kinds of stories we could tell.

We found our way forward in an unexpected place: Walt himself. The Disney archives held astonishing recordings of Walt explaining his creative process. His own writings. His notes and storyboards. Work product captured at every stage of his process. This was truly a gift. Listening, reading, sitting with the work itself, we heard him talk about character, about emotion, about how an audience feels when a character truly comes alive. He talked about making bold choices and refining a scene until it genuinely moved people. We didn't hear a word about pencils or paintbrushes. In fact, Walt was famous for being a technologist, forever hunting for state-of-the-art tools, often inventing them himself to achieve the images he saw in his head. But he never defined animation by the tools. He defined it by whether the audience believed the character. His principles were timeless. The tools were not.

That realization changed everything. We co-developed the Computer Animation Production System (CAPS) with a young Northern California company called Pixar, replacing hand-painted cels with CGI. In The Little Mermaid, the final scene shimmered with a dimensionality and light that the old process simply couldn't achieve. In Beauty and the Beast, the ballroom sequence moved with a cinematic sweep that placed the audience inside the emotion of the moment. In Aladdin, the Cave of Wonders felt vast and alive, and the Magic Carpet became an intricate, compelling character all its own. In The Lion King, the stampede carried a scale and intensity that raised the emotional stakes beyond anything we'd done before. Technology didn't diminish the craft, it expanded the canvas. It gave artists more room to create.

A decade later, the canvas expanded again. When Disney released Pixar's Toy Story, it wasn't simply a technical milestone. It was proof that a fully computer-animated film could carry real emotional weight, that it could make audiences laugh, cry, and believe. At DreamWorks, we made the difficult decision to sunset hand-drawn animation and become a fully computer-animated studio. It was the right thing to do, but it was not without pain. It cost talented people their place in an industry where they had worked their whole lives. Some made the leap to the new tools and did the finest work of their careers. Some never did.

Tools are never the point. The instruments change with every generation. What endures is taste and imagination. The magical ability to make an audience feel. One of the greatest storytellers of our generation, George Lucas, succinctly captured the eternal essence of this issue: “It’s not the how, it’s the why.”

A Distinction With a Difference

I asked one of the leading AI models a question that has been challenging me for months. What is the difference between reasoning and creating? Its answer changed how I think about almost everything happening in this industry. It said . . .

Reasoning and creating are two distinct cognitive modes, though they also work together. Reasoning is fundamentally evaluative and analytical. It operates on what already exists: facts, premises, evidence. It moves toward a conclusion that was in a sense already implied by the input. Reasoning is constrained by logic and truth. Its goal is to arrive somewhere correct, not to invent somewhere new.

Creating is fundamentally generative. It produces something that didn't exist before. And crucially, there's no single right answer waiting to be found. A blank page has infinite valid responses. Creation involves choices that can't be fully justified by logic alone. Taste, intuition and vision fill the gap where deduction runs out.

Reasoning is what Silicon Valley has been perfecting. Creating is what Hollywood has been practicing for more than a century. AI today operates almost entirely on the reasoning side of the line. It can deduce, evaluate, optimize, and pattern-match brilliantly. And while it can create, there is a real distinction to being creative. What it doesn’t yet have is those things that make us human: empathy, devotion, serendipity, the kind of creativity that comes from a person trying to say something only they could say. When the bot generates a piece of art, it is not trying to communicate anything. It is statistics, not soul; it is emulating things that have been done. By contrast, human creativity isn’t about repeating patterns of zeros and ones; it is about doing something new.

One day, AI may close this gap. Three years ago, the leaders building AI would have called what they are achieving today, improbable, if not impossible. Impossible is no longer improbable.

Today, the line between reasoning and creating is real. Even the leading technologists acknowledge we are not there yet. There is no scientific path to crossing this divide that anyone in the field can articulate today. Understanding that gap is where we will find common ground.

A Path Forward

In 2016, I closed one chapter in Hollywood with the sale of DreamWorks and opened another in Northern California, co-founding WndrCo. We’ve backed more than 50 founders building the next generation of technology and watched how breakthroughs in Silicon Valley emerge, first as experiments, then as platforms, and finally as infrastructure that reshapes entire industries. It's worth remembering that the last great revolution in animation also came from the north. Pixar was a Northern California company, forged not in the conventions of the Hollywood studio system, but in the technological breakthroughs of Silicon Valley. I've spent years on both sides of this bridge. For sure, I don’t have all the answers (take Quibi, for one!). But, from my past and present vantage points of my long career, here is what I see . . .

Brilliant people in Northern California building this technology have made something extraordinary. They have earned the right for the rest of us to be, if not believers, at least optimistic that what comes next will be remarkable. But they have not made an artist. The tools are powerful, but they are not what makes a story matter. That knowledge lives 350 miles to the south, inside people whose life's work has informed the very models you are building. The right path forward includes them by design, with credit, with consent, and with compensation. Build this with the storytellers. Not on top of them. Taste is not something that can be synthesized, it is uniquely human.

At the same time, Hollywood needs to accept that AI is not going away. The energy they are spending trying to make it disappear is energy they are not spending deciding the terms on which it will exist. And the terms are everything. The north needs something from it that they cannot build and cannot buy: creativity. The kind that takes a blank page and conjures a single right answer where there was none and has held audiences for a century. Without it, the most powerful reasoning engine ever invented will still be missing the only thing that makes a story worth telling.

The artists who learn to wield these new instruments will do things the engineers never dreamed of. They always have. Edison invented the motion picture but made terrible movies. It took Chaplin, Lloyd, Keaton and so many others to make movies emotional. Now, the canvas is about to expand yet again. We should decide now that we intend to paint on it.

There are so many valuable lessons in history. This has happened many times before, and it was never settled by the technology. It was settled by the terms. Sousa did not stop the phonograph; he helped write the law that made sure composers got paid. And two years ago, when the writers and the actors walked out, they were fighting for the very things Sousa was fighting for in 1906. Consent, compensation, the basic recognition that human creative work has a price that must be paid. The terms of that fight are still being negotiated, but the principle is older than any of us.

The tools-versus-no-tools argument is a trap. First, we must all agree that there should be terms. Then we can have the crucial debate about what fairness requires.

What I Learned From Steve Jobs

Years ago, Steve Jobs said, "It's in Apple's DNA that technology alone is not enough. It's technology married with the liberal arts, married with the humanities, that yields us the result that makes our hearts sing." He was describing a device. But he could just as easily have been describing this tale of two cities.

What I See Coming Soon

As the barriers and the costs come down, more films will get made, not fewer. Studios will get to take more risks. There will be more seats at the table, and very soon entirely new forms of storytelling. In the 1980s, animation was dismissed as a niche corner of the business. Today it is one of the most beloved and profitable forms of storytelling in the world. In live action, filmmakers like Steven Spielberg, James Cameron and Peter Jackson embraced new visual tools not as shortcuts, but as instruments, and expanded cinema in the process. Every time storytelling has met a genuine technological shift, from synchronized sound to color to computer animation, it has redefined the boundaries of the medium and grown larger in the process.

Assuredly, I don’t have all the answers, but I am confident that the creative opportunities will expand yet again. How we come through this is a choice. The north has the new tools. The south has the creative soul. The best future will draw on the best of both worlds.

[elvis @omarsar0]

Must-read paper from Google on self-improving agent harnesses.

If you auto-optimize your agent's harness, your eval score can go up while the agent gets worse on real tasks.

This paper shows how to prevent that.

Of five harness-evolution methods compared on agentic workspace tasks, RRSI scored the lowest on the tasks it evolved against and highest on all three out-of-distribution benchmarks.

Automated harness evolution proposes edits to prompts, control flow, tools and memory, keeps the ones that raise the score, and repeats.

The authors show this overfits the training tasks. Meta-Harness reached 93.0 on the Harvey LAB evolve split but gained only 0.3 to 1.5 points on JobBench, GDPval and APEX-Agents.

RRSI adds regularization on both sides of the loop.

The proposer gets an edit budget that shrinks over time and is pushed toward directions it has not tried. A critic rejects benchmark-specific edits, and a pruner removes edits that are too small, too costly or no longer useful.

RRSI scored 90.5 on the evolve split and gained 3.5 to 4.7 points on the three held-out benchmarks. In the ablation, unregularized evolution used 3.80M tokens per trial against 2.42M for RRSI. With Gemini 3.5 Flash, RRSI raised Terminal-Bench 2.1 from 64.6 to 78.7 and carried a 2.2-point gain over to SWE-bench Verified.

Paper: https://t.co/SlfjDg96VI

Chat with Paper: https://t.co/gBotiH6Jfq

[Sam Z Liu @samzliu]

I've discovered two ways Jev fundamentally improves my agent workflow, and it's the opposite of how most people are using it.

The most exciting use-cases for Jev aren't about cost reduction such as model routing, context compaction, or cheaper LLM-as-a-judge. Rather, the essence of Jevon's paradox is in expanding what is possible.

Notification center for agents - Use Jev as a monitor for real time events (e.g. slack messages, webhooks, etc.). Only forward important/urgent messages to the agent. Think of this as a parallel capability to scheduled tasks that enable persistent & proactive agents.

Skill-based continual learning - Skills often fail to live up to their potential because it's not clear when to use them. The agent becomes confused when to invoke which ones and you forget which ones you even had. Add a section to the front matter which tells an agent when to use that skill. Then for every user-message, use Jev to decide which skills should be loaded.

[elvis @omarsar0]

Interesting paper on agent memory stored as a linked markdown wiki.

Lots of great ideas and insights if you work with LLM Wikis.

Wikis are useful for agents because each page holds dense text and the links between pages hold structure. WFM is a Wiki Foundation Model trained to use both at once.

It turns an LLM Wiki into a graph and retrieves from it with message passing conditioned on the query, so the text of each page and the link structure shape the result together.

The team also built a GPU-to-GPU training protocol that trains 10.5x faster, and reports strong results on five agent memory and multi-hop reasoning benchmarks.

If your agent's long-term memory is a folder of linked markdown files, WFM is designed for that format.

Paper: https://t.co/t3iwlcCFB8

Chat with Paper: https://t.co/4QL4IyKPBW

[Raoul Pal @RaoulGMI]

When people think about tokenisation they tend to think about trading Apple on a Sunday, instant settlement, 24/7 markets... That's one tiny piece of it.

The bigger story is that everything becomes a token, and the whole economy gets rebuilt around it. https://t.co/TE4LmgrkYs

[Forbidden @forbidden_mp4]

@TensaiCapital @swing_io Is this for a specific lvl of trader or is it open to those getting started dabbling into trading?

[Erik Torenberg @eriktorenberg]

Introducing The Horowitz Andreessen Academy.

[signüll @signulll]

every major company is arriving at roughly the same offering:

persistent memory, email/calendar/messages, browser + computer use, background tasks, proactive notifications, voice, app/tool execution, ambient context, & some notion of a personal agent sitting above everything.

remarkable levels of convergence with very little differentiation whatsoever.

[Alex Kehr @alexkehr]

I think Silicon Valley is making a fundamental mistake with personal agents… optimizing entirely for the outcome and forgetting that, for a lot of things, the process is a very core part of experience.

Travel is the obvious example. People will almost always never want “book me a trip.” They want to browse, compare, daydream, change their mind, send options to friends, and eventually book.

And the average person probably has far fewer recurring tasks worth delegating than the AI industry seems to think.

That’s why personal agents feel more like a feature that gets absorbed into existing products than a standalone category.

[Forbidden @forbidden_mp4]

@TensaiCapital smart man. shows you take this stuff seriously

[GREG ISENBERG @gregisenberg]

https://t.co/wfHAsNRGZT

[Tensai Capital @TensaiCapital]

This is the spot for crypto where you want to be at max risk.

By “max risk” I don’t mean “irresponsibly long”. What I mean is, you should have more risk on at this moment than either one month ago or one month from now.

We are likely at the point of maximum R/R for the year. The downtrend that started last October is clearly over, and the refusal of majors to break down on CLARITY failure plus rate hike means we’re probably not getting a chance to buy lower before the next leg up.

Plenty of coins are justifiable as long-term investments. However, you shouldn’t plan to just buy and hold them all the way to your final target. You also want to set yourself up to take profits along the way.

That means sizing all your favorite positions with a plan to own LESS of them in a few months than you currently do - even though you hope that means leaving money on the table.

[Forbidden @forbidden_mp4]

@iamAliAgha how many years until we achieve real simplicity with AI products?

5-10 maybe or longer?

[vitalik.eth @VitalikButerin]

Qwen 3.8 flash is truly impressive, and llama.cpp has been rapidly getting better and better at processing it

columns are: pre-existing prompt, new prompt, generated, input tok/s, output tok/s

This is on my laptop (strix halo). I think we're very close to the point where you can just use local models for a large share of tasks, and for anything more advanced, workflows like "use your local model to orchestrate queries to powerful models so your queries don't leak your personal information" actually become viable.

[vitalik.eth @VitalikButerin]

Since many people are learning about effective altruism, it's worth learning about Mozi, the ancient Chinese philosopher who was surprisingly close to being a proto-effective-altruist (particularly the global-health-focused variety, not the AI-risk-focused variety).

He valued the twin goals of (i) universal love, loving everyone and not just yourself and people similar or close to you, and (ii) being efficient about how you use your limited resources to most effectively help people.

https://t.co/eYLH7Inzl9

[Dr Singularity @Dr_Singularity]

big AI news

Google just demonstrated a recursive self improvement loop for AI discovery

Google/DeepMind researchers introduced Dream-RSI, a system where an AI agent improves how it explores problems by replaying its past discovery attempts, testing thousands of alternative strategies cheaply, then deploying the better strategy in the next round.

Across algorithm design, mathematical optimization, and GPU kernel engineering, it matched or improved discovery quality while cutting search costs dramatically, in one setting reducing agent calls by up to 162x. 👀

Importantly, it improves the exploration policy, not the underlying model weights.

[Alexandr Wang @alexandr_wang]

We believe strongly in the necessity to invest into alignment.

1. People and businesses will only use agents that are aligned with their intent and values. If we do not build models aligned with people and businesses, then they will move to more aligned options.

2. Every lab should have a strong governance framework across training and deployment. This should include external evaluators, which are best practice for transparency, and independent oversight on things like safety criteria for model launches.

3. Every lab will need to operate within institutional protections of democratic countries. This means labs face significant liability if their models cause harm. This will push the ecosystem in the right ways.

4. Advances in the field are ultimately downstream of compute and resource allocation. Racing on recursive self-improvement is one of the riskiest pathways for potential loss of control to powerful models. Meta is committing the significant majority of our compute towards serving people rather than racing on RSI, and other labs can choose to do the same.

AI is a very powerful technology, and there is immense responsibility in developing it safely alongside the right checks and balances.

[Forbidden @forbidden_mp4]

imagine where we would be if everyone adopted this mindset

[jack @jack]

https://t.co/qAUP2dNJsi

[Marc Andreessen 🇺🇸 @pmarca]

https://t.co/lhP4mJq4Ad

[Sawyer Merritt @SawyerMerritt]

Next week, the SpaceXAI team will build a company from the ground and livestream it.

“We'll use Grok Bot for every part of the build - from ideation and product development to real engineering work and deployment.”