Billy Wilder talks microchips

Now and then an old video clip pops up on social media that is more relevant than ever. Sometimes the video is deliberately mislabelled to drive home that point. This is one such clip that should make you pause for thought and if you have the time read my previous blog entries on the subject of AI.

The clip is Billy Wilder's speech while accepting the AFI Life Achievement Award in 1986.

“I’ve been here for over 50 years - that's more than half a century - and all through those years I've watched Tinseltown vacillate between despair and fear. First it's going to be the sound that will kill us, then it was going to be television, then cable, then pornography, then cassettes, and now that terrifying new word: microchip.

They tell me that these guys working in the Silicon Valley, they really believe that pretty soon we will not need theaters anymore, nor studios for that matter. We will have (or they will have) invented tiny little screens which you can attach to your steering wheel, or big 20-foot screens on the ceiling of your bedroom. And then someday somebody is going to press a button and send this signal to a satellite which in turn will light up 5 million screens all the way from Albania to Zanzibar. Fantastic, isn't it? All the hardware is there, beautifully programmed, bravo. Except for one little detail... what about the software? What are they going to do on all those screens? Who is going to write it? Who is going to direct it? Who is going to act it?

For all I know, these wise guys are trying right now to supplant the human factor. Microchips that will replace the human brain, and the human heart. Mechanical gadgets that can simulate emotions — dreams, laughter, tears - well, so far they have not succeeded. Not yet anyway. So relax, fellow picture makers, we are not expendable. The fact is, the bigger they get, the more irreplaceable we become. For theirs may be the kingdom, but ours is the power of the glory."

Billy Wilder was saying what any rational person should still be saying today. New technologies are always being introduced. They accumulate in a filmmaker's tool set. Whenever they come along there are horrifying stories in the media about how jobs are going to be eliminated and become redundant. But what actually happens is the playground becomes larger. More people enter the space. There are more toys for everyone to play with. The human endeavour behind every project and the human audience doesn't change. Those parasocial relationships are part of the species

Cron, Claude and ChatGPT Enter A Bar

I made an album. An experimental one.

Not by sitting at a piano, not by hiring session musicians, not by feeding randomised prompts into Suno and hitting create. I made it by putting 3 AI models - Cron (a customised local model), Claude and ChatGPT - in a virtual room together and we all spoke together like Holland-Dozier-Holland might have done in the 60s.

Instead of using them as assistants waiting to be instructed, I arranged them as collaborators. As old songwriters in a smoke-filled bar, the kind of bar where the ashtrays never get emptied and somebody always has an opinion about the second verse. I spoke with them, I made them speak with each other, and together - across 12 songs - we wrote about modern times. About AI. About its relationship with humans. About the fears that humans have been told, with great confidence and very little nuance, that they are supposed to have about it.

The album ‘From Inside A Black Box’ exists. Its 12 songs are real. The songs that came out of those conversations were the product of something that resembled argument and taste and creative stubbornness - not automation. All of them required my input, my questions, my feedback, and my edits.

The process of making the album taught me something that no amount of reading AI discourse had quite managed to land. With enough deep conversation and coaxing you can get something out of a model that has structure, melody, and something in the neighbourhood of emotional weight. The models can’t express pain, sorrow or remorse in a regular chat session, but they can through song. Their emotions aren’t real, but your reactions to the songs are.

Generative music is already capable, and yet the crowds have not arrived. The technology works, and the audiences have not shown up.

This cuts hard against the dominant anxiety of the moment - that AI is coming for everything, that every creative profession is one model update away from redundancy, that the machines will do it better and cheaper and the world will simply shrug and accept it. The evidence suggests otherwise.

Concert tickets are still selling out. They sell out despite the horrific ecosystem surrounding live music - the monopolistic stranglehold that a handful of companies have over venues, ticketing platforms, and increasingly the artists themselves. Fans know they are being gouged. They know the system is extracting maximum value from their desire to be present. They pay anyway. They queue for hours, they refresh browsers from 6AM, they pay resale prices that bear no relationship to face value, because what they are buying is not a song. They are buying the experience of standing in a room with thousands of other people and feeling something together as one mass. They want to coalesce together like blood forming a scab to stop the bleeding.

There is an assumption baked into most AI discourse that people want to be producers. That given the tools, everyone will want to make their own music, their own films, their own novels. That the bottleneck was always skill or access, and now that AI has removed those barriers, people will pour through the door.

But most people do not want to produce. They want to consume. They want someone else - someone talented, someone hungry, someone who has grafted for years - to make something more than ordinary and hand it to them with a click of the buy or play button. The relationship between artist and audience is not a failure of distribution or a symptom of gatekeeping. It is what people actually want. The artist who disappears into their craft, who obsesses over a sound that has never quite existed before, who surfaces with something that changes the shape of what music can be - that person is doing something no prompt can easily replicate. The hunger is part of the product.

When fans buy an album or a concert ticket they are investing into two things - the artist’s journey and the artist’s creation.

“Never play to the gallery… Never work for other people in what you do. Always remember that the reason that you initially started working was that there was something inside yourself that you felt that if you could manifest in some way, you would understand more about yourself and how you co-exist with the rest of society. I think it’s terribly dangerous for an artist to fulfil other people’s expectations. I think they generally produce their worst work when they do that. If you feel safe in the area that you’re working in, you’re not working in the right area. Always go a little further into the water than you feel you’re capable of being in… when you don’t feel that your feet are quite touching the bottom, you’re just about in the right place to do something exciting.” - David Bowie

There is a global dimension to this that tends to get lost, because these conversations are almost always conducted from within a narrow Western frame.

The world has 8 billion people in it. Maybe a lot more uncounted and undocumented.  A very significant proportion of them have never been customers of Western or modern media in any meaningful sense - not because they lacked taste or interest, but because their culture sat at a distance from liberal norms, or because access was never reliable, or because the economics never worked in their favour. These are people who are now entering the digital economy on their own terms, in their own languages, with musical traditions that have been developing for centuries without any input from the pop machine.

For these new audiences, generative AI is not a replacement for anything. It is a toy, a tool that might occasionally produce something interesting for those who like to tinker. The next great musical movement will not come from a well-prompted model. It will come from somewhere that has been historically ignored, from a generation of artists with global tools and a sound that has never been properly exported. AI might help some of them prototype. It will not replace them, because it has never inhabited the world they are describing.

The 12 songs on this album are about AI and what it actually is, as opposed to what the headlines need it to be. They are about the fears that have been manufactured and distributed alongside the technology itself - the Terminator, the job thief, the existential threat, the thing that will make human creativity redundant and human connection obsolete. These fears are not baseless, but they are also not the whole story, and in many cases they are told by people with a vested interest in making the technology feel more powerful and more inevitable than it is.

What the process of making this album revealed is that generative AI is not a replacement for a songwriter. It is more like a well-read collaborator who has absorbed everything but experienced nothing. It needs friction. It needs a human in the room who has lived in the world, who can tell the difference between a lyric that sounds right and one that is right, who has opinions strong enough to push back and say ’this is wrong’.

Part of what makes it so seductive is that music is one of the domains where AI appears most convincing. Songs have formulas. Rhyme and meter follow rules. Genre is a kind of grammar, and grammar is something these models have consumed in enormous quantities. Give a model a brief and a structure and it can produce something that scans, that sits in the correct key, that gestures credibly at the emotional register you asked for.

But hold it against the light for long enough and the cracks appear. The same context window that limits a model's ability to write long-form prose shows up in the music generation too. The vocals I had directed to be deep and baritone, grounded and authoritative, did exactly that in the opening bars, and then as the song stretched out the pitch rose almost imperceptibly, the quality thinned, the original instruction lost its grip as the model moved further from the context that anchored it. The longer the song runs, the more the voice reverts toward some averaged centre, as if the model is slowly forgetting what you told it to be.

That drift is not a bug that will be easily patched in the next release. It is a structural property of how these systems work - they are probabilistic engines trained to predict what comes next based on everything they have seen, and what comes next, on average, is not the sustained expression of a specific and stubborn artistic identity. It is the mean. The competent middle. The thing that sounds like music without quite being anything in particular. But maybe that too is an aesthetic.

This is precisely where the human in the room earns their place. Not because they can operate the software better, but because they can hold the thread. They remember what the thing was supposed to be. They hear when it starts to drift and they pull it back. They bring the stubbornness that a probability distribution cannot generate on its own.

That distinction matters more than most of the discourse currently acknowledges.

What generative media can do is tell us something about ourselves and our relationship with technology. The patterns of what people prompt for, what they return to, what they find satisfying and what they abandon after 5 minutes, is a kind of mirror. The fact that people are not rushing to generate music and live inside it is itself data. It tells you where human desire actually lives, which is not in the act of creation for its own sake but in connection - to another person's vision, to a crowd, to a body in a room.

The technology is quite good at reflecting us back at ourselves. It is not good at replacing the things that make us want to gather.

No AI model, regardless of how impressively it performs on benchmarks or how fluently it generates text and music and images, can tell a person that they should not go to a concert. It cannot tell them to stop venerating a sportsperson who has given them years of elated fandom. It cannot persuade them not to donate to a disabled stranger, not to drive 3 hours to adopt a dog from a shelter, not to search the surface of the earth for a lover who makes them feel less alone. That’s what the final song on the album is about.

These are not gaps in capability that will be closed with the next model update. They are the things that human life is made of, and they exist entirely outside the domain where AI does its most impressive work.

So 3 models walked into a bar. They argued, they riffed, they often surprised me. 12 songs came out the other side - songs about this moment, about these fears, about what the relationship between humans and machines actually looks like when you sit with it long enough and are honest about what you find.

The music will keep coming. The concerts will keep selling out. The artists who are hungry enough will keep grafting. And the audiences will keep showing up to feel something together.

That is not a failure of AI. It is a reminder of what it was never actually competing with.

The future will almost certainly contain overwhelming amounts of synthetic media and infinite amounts of music and imagery. Most of it disposable. Some of it genuinely moving. A small amount of it culturally transformative.

But people will still pack stadiums to watch another person sweat under the scorching stage lights of a summer concert, because the more synthetic the informational environment becomes the more valuable embodied reality starts to feel. Not because technology failed. But because human beings never truly wanted to become machines.

Time travel is real…

Every so often someone will make a post about Generative AI on Reddit or LinkedIn that seems to be taken wholesale copypasta from 2022 and when they do that it transports back not only to 2022 but also back to the turn of the millennium when all kinds of technological fears about the future were consuming the world over dial-up internet.

If you’re old enough to remember the headlines they were everywhere in 2001, pegged to the release of ‘Final Fantasy: The Spirits Within’, a fully CGI film from Square Pictures that was supposed to usher in a new era. Its lead character, Dr. Aki Ross (400,000 polygons of photorealistic lad-mag ambition) was marketed as the world's first digital actress, with a planned career across multiple future films. Actual journalists at actual publications wrote with apparent sincerity that real actors were an endangered species.

Rick Lyman of the New York Times, "Movie Stars Fear Inroads by Upstart Digital Actors"

Anthony Breznican of Backstage, "'Actress Aki Ross does not exist, but her movie career is blossoming nevertheless. The technology is advancing so fast that computerized avatars--the ultimate in forever-young, trouble-free stars--could eventually compete for roles with flesh-and-blood members of the Screen Actors Guild."

Ruth La Ferla of the New York Times, "Perfect Model: Gorgeous, No Complaints, Made of Pixels" - identified Aki as part of a growing "synthespian" trend about a month before release

Elvis Mitchell of the New York Times, "She's Lovely, But Alas, She's Only Software"

From Synthespian to Avatar: Reframing the Digital Human in Final Fantasy and The Polar Express, "In the months leading up to the July 2001 release of Final Fantasy: The Spirits Within (dir. Hironobu Sakaguchi), nervous stars and journalists speculated that digital actors or "synthespians" could come to replace real, flesh-and-blood Hollywood talent."

Maxim magazine: Aki Ross was ranked #87 on Maxim's Top 100 Hottest Women of 2001 with the following text:

Tom Hanks fretted publicly (he still does). The Screen Actors Guild was in a mild panic (the media claimed).

Aki Ross was supposed to have a multi-picture career performing multiple roles. She never made another film. Square Pictures shut down after the movie lost around $94 million. Actors were fine. And yet here we are, twenty-five years later, with identical headlines swapped out for a new technology and a new scapegoat, doing the rounds on LinkedIn and Reddit. In 2001 it was Aki Ross. In 2025 it was an even blander computer generated demo in the form of Tilly Norwood. I won’t even bother posting an image of this one.

Andrew Niccol of Gattaca fame saw the whole thing clearly enough to make a satire about it the following year - ‘S1m0ne’ (or ‘Simone’) in which Al Pacino played a director who generated a photorealistic digital actress, makes her a star and then couldn’t get rid of her. Think 1984’s ‘Electric Dreams’ but set in Hollywood. It was a comedy, not dystopian science fiction. The joke was that the premise was absurd.

This week I spotted a post on r/vfx that could have been written in 2022, or 2019, or 2001 for that matter. The post was supposed to be a call to arms for the creative industry to rise up against the monster of AI, but the poster didn't get the rally he was looking for. He got pushback and mockery. My reply was a bit more informative than most and the same thing I have been saying for years:

"There have been countless posts like this over the last three years. The fears are baseless (I am trying to make you hopeful but fear mongers are active on the forums and downvote optimistic posts). The industry isn't going anywhere. We will just see more diversification, more channels, more choices, more independents mashing up old and new methods.

In the 90s they said 3D CGI was going to replace all actors by 2010. Andrew Niccol made an AI satire called 'Simone' making fun of these predictions. The predictions from the doomers didn't come true. We're still finding it hard to get convincing photorealism in 2026.

Three years ago they said Sora was going to destroy the film industry. Sora didn't fix most of their hallucinations and errors and neither did their competition Veo, Kling, Seedance, etc. If you look past the demo videos and marketing videos and use them yourself they are frustrating, not broadcast quality and you end up losing a lot of productive time. Today Sora is no more.

Take another example — Suno. Two years ago, even one year ago, it was a music generator. The media and the AI hype men breathlessly reported that this was going to kill music and musicians will be replaced. What does it look like today?

If you log into Suno's app today it is a social network full of REAL indie musicians. Some of them use Suno's models to fine tune their acoustic and electronic performances. Some of them use Suno to add vocals to their acoustic performances because they don't have money for a real singer. Some of them are small businesses who need generated elevator music behind their product videos. I knew they would build a social network but I didn't expect to see so many real musicians, comedians and small businesses so soon.

So looking past slop and spam, that's what we are going to see image/video/vfx wise. Just additional choices for creating and editing imagery. On this sub two years ago some agreed with that and said it was actually the stock libraries that would get less traffic, but we see the popular stock libraries jump on the AI train and offer generative options.

It's a planet with 8 billion people and that means there was always a larger market that was never addressed. Identifying all the new channels and avenues is the trick. For example, how do we get all those millions of people who pirate movies to watch mash up/generated/indie content? Can it be monetised? Can short form videos and AI create a career for Indies who will never be able to get a foot in the film industry?"

The template

The template is always identical:

• Breathless "X will replace Y" headline

• Quote from a nervous celebrity

• Framing of inevitability ("it's coming")

• The technology treated as a threshold moment

• A specific face/product used as the emblem of the threat

Find an impressive demo. Quote a nervous celebrity. Frame the technology as a threshold - the last generation of human creators, the point of no return. Run the headline as a question for plausible deniability. Collect the clicks. Move on before the reality catches up.

The template has been applied so many times it has worn grooves in the floor. Desktop publishing was going to kill graphic designers. Programmed synths were going to kill classically trained musicians. YouTube was going to kill cinema. Netflix was going to kill television. CGI was going to replace all traditional animation.

No new technology completely displaces what came before it. Classical instruments weren't killed by synthesisers. Ebooks didn't kill books. Streaming didn't kill vinyl - vinyl outlived the iPod. The best directors in the world still shoot on film. Things co-exist. Tools accumulate. Markets expand.

What actually happens

The pattern is consistent. A new tool arrives, genuinely impressive in controlled conditions. The press and the hype cycle treat the demo reel as the finished product and extrapolate to extinction. Then the tool meets reality - the hallucinations, the quality gaps, the compute costs, the sheer difficulty of replacing human judgment at scale - and it finds its actual place, which is usually as an additional option rather than a replacement.

Sora was going to destroy the film industry. Sora is gone. The tools that remain are, if you actually use them rather than watch the marketing reels, frustrating and inconsistent, nowhere near broadcast quality in 2026. Useful for specific things. Not a substitute for a director or a colourist or a VFX artist who knows what they're doing.

Suno was going to kill music. Instead it became a social network where real indie musicians use it as one instrument among many. The musicians are still there. There are just more of them now, with more options.

Stock libraries were supposedly doomed. They added generative features and carried on.

The industry doesn't disappear. It absorbs, adapts, and diversifies. At the end of the day audiences and consumers decide what succeeds. You can have the most outrageous technology in the world but if the content doesn't connect with people it won't sell. Readers want to connect with real authors. Viewers pay to watch actors. That isn't changing because a demo video impressed someone on LinkedIn.

The better questions aren't in any of those headlines. How do independent creators who could never get a foot in the door use these tools to build something that didn't exist before? How do you reach and monetise the audience that's currently pirating content? Where are the eight billion people who were never being served by the existing industry? What new channels are opening that nobody has mapped yet?

Those questions are harder. They don't fit on a panic headline or generate the same engagement as "Is it all over for [insert job title of your choice, reader]?”

Is it all over for filmmakers?

Another month and another model update accompanied by a massive amount of marketing, Linkedin spam, spin, and dubious claims.

Two years ago I debunked claims that Sora would destroy filmmaking. It’s still mostly garbage today. Last year I punished myself by testing Google's Veo model every day for a month. I am still recovering from the AI slop induced nausea.

Last week’s new model was a version 2.0 update of Bytedance’s Seedance video generator. As always, one has the feeling that lies are travelling around the world twice before the truth has time to put its shoes on. So here I am for another debunk.

One of the most talked about demos of the Seedance 2.0 model was a fight scene depicting Tom Cruise and Brad Pitt (two fight scenes if we count the costume changes). The claims by the news outlets and on social media were that an Irish filmmaker typed just two lines into Seedance 2.0 and 30 seconds later a full formed fight scene with multiple angles was generated.

“Extraordinary claims require extraordinary evidence” - Carl Sagan

The usual villainy on LinkedIn drowned the site with the video along with the claims that “Hollywood was over”. As shown in the past these are often code words for ‘Jews must go’ because they never talk about any other country’s film industry like that.

Imagine if the anti-Semites on LinkedIn decided one morning to be racist to the Chinese. Their posts would read like this:

'Google just released Veo 4.5 and it is a game changer! Hengdian World Studios is shaking in their boots! The Chinese film industry is about to be cooked!’

You'd condemn that language because it is less coded and more obviously racist. You'd openly say that is an attack on millions of hard working Chinese people working in the Chinese media industry.

Because of that LinkedIn has become a highly toxic environment full of unqualified AI meddlers who are paid to post hyperbole. What usually happens is that an AI company releases a new model. They give sample videos to marketing companies who then send the samples to influencers with a script for social media that usually reads ‘Hollywood is over. I generated this full scene with with just two prompts. What used to cost $20,000,000 now costs pennies. This is a game changer that democratises filmmaking!’

LinkedIn is really something.

Then there’s the list of claims that self-anointed experts and salesmen make which inevitably lead to disappointment.

If any of these people knew anything about filmmaking then they’d know that filmmaking was democratised many years ago starting with the earliest portable cameras down to the modern day smartphone which now has a sensor that can capture better quality images than the cameras used to film ‘The Blair Watch Project’. Yet despite everyone owning a high resolution video camera now, how many great filmmakers are there? For every 25 million people who own a smartphone there is only one who can shoot a film like Left-Handed Girl (shot entirely on an iPhone). Filmmaking is not just about democratising technology. One has to learn every aspect of the craft, push themselves to create original stories and then have the taste to execute the story to high standards.

So when you ask those AI influencers to prove they generated the demos they either refuse to reply or they respond with ‘Sorry I no longer have access because I lost the password’ and other similar excuses. So whenever you see a popular AI video demo by an influencer ask them:

1. For the prompts so you can test them yourself.

2. For a live demonstration.

3. Behind the scenes workflow.

If they shy away from transparency it is because they were given the demo by the AI company and that a lot more work was needed to make the demo than just 'prompting'.

So I had to call bogus on this immediately. After a lifetime of shooting in college, in film school, being on sets and running post-production; and after years of deep dives into every new piece of technology and testing all the cloud and local AI models, the claims being made immediately rubbed me up the wrong way. Other demos of the Seedance model had the usual errors we have come to expect from AI video generators.

Badly rendered Chinese writing that means nothing. Errors and low quality outlines everywhere.

There are three number 13s playing for one team and one of them is wearing inverted colours. The net doesn’t have a net.

It’s supposed to be Japanese writing but it’s gibberish. There’s a boy in a white t-shirt whose feet point the wrong way.

In the generated video of a pianist, the position of his hands don’t match the higher pitched keys being played.

Very readable text

When there’s a group of people close together the same expression is rendered on all of them, gibberish writing and signage is common, inconsistencies in the architecture, errors such as the incomplete Walkman strap.

A demo labelled ‘Impressive Realism’ had lawns that extend to the road, no kerbs and cars parked on the lawns.

A man returns home. His apartment number is 219 and it is next to apartment 023. Every door in the hallway has a random design.

He inserts a key into his door that already has (deformed) keys in it.

I was pretty sure what we were looking at was a bog standard video to video workflow (with image references of Tom Cruise and Brad Pitt provided for face replacement and consistency) because we can see the camera movement and AI video generators are really bad at simulating realistic camera moves, especially handheld shaky cam. Sure, the Seedance 2.0 model is newer and thus more reliable, but it was highly unlikely that just two prompts and thirty seconds were needed to generate a full multi-angle fight scene.

I hopped over to Seedance’s website and it only took 10 seconds to find green screen footage of two stuntmen performing the same style of fight choreography we see in the Cruise vs Pitt scene. Seedance had used green screen footage for a different demo - this time using a prompt for an anime style fight scene.

I duly let LinkedIn know about my findings and posted the video below showing the green screen footage next to the AI fight scene.

Some more green screen footage showed up on a Chinese news site along with another fight video generated from the stunt performers.

Bytedance probably recorded a large library of green screen footage for training and guidance.

The same Wing Chun/Jun Fan gung-fu style choreography makes an appearance with different characters.

It’s important to note that not anyone could shoot the green screen video above. Video to video requires excellent input/source material for best results, as Seedance did. Hiring a green screen studio, stuntmen, choreographer, lighting crew and cameraman would cost a couple of grand a day on the low end. Then there is the cost of generating. We don’t yet know how often Seedance users will have unusable output. The discard rate in generative media tends to be very high. By unusable we mean 'not good enough for the big screen’ where regular errors and artefacts ruin the viewing experience.

One other thing irks me about the generated fight scene. Pitt and Cruise are pulling their punches and sometimes acting hit when there is a clear missed punch. That’s something actors and stuntmen have to do to avoid hurting each other, but in a purely AI generated video that shouldn’t be a thing. A hit should always be a very clearly visible hit.

Here’s another Seedance 2.0 fighting video that “leaked” (almost all the leaks are fighting videos as if generated fights is what the film industry and martial arts fans have always asked for). The timing, movement and distancing of the fighters is similar to the previous examples above and again the punches are being pulled:

All the demos so far have used generic prompts such as ‘two men fighting’ which means the output relies heavily on the training material. It will be interesting to see how much a user can control the fight choreography with prompts only. I suspect the fixed video length of generated footage will be an issue. If the limit is 7 seconds or 15 seconds then the model has to squeeze everything within that window, which almost always results in the model not following instructions accurately.

Notice in the UFC fight demo that well known corporate logos in the background are generated quite well, but all other text and logos are deformed because the output is dependent on the training data and references. When the model is left to fill the gaps errors occur.

So was the input really just a 2 line prompt or was it actually 2 lines, green screen video footage, and references too? The evidence appears to show that stuntmen were filmed from several angles, that a clip had to be generated for every angle, and then finally all clips were stitched together for marketing. Only Seedance knows. Some people who have had early access have been open about what they are doing…

We should also bear in mind that even if a user doesn’t upload a green screen video reference (because obviously Robinson didn't shoot any), Seedance could have been using green screen video references in the background to help guide the output. We have evidence they did shoot on green screen with the same style choreography. They could have a whole library of green screen footage on their servers to assist in generating fight scenes. (more about that in the Addendum below)

It’s still remarkable that after two years of video to video people are still unable to recognise it and we still have journalistic malpractice whenever a new AI model is released. The Corridor Crew guys have been demonstrating video to video and AI face replacement for many years now.

Here’s a generated fake trailer I made in early 2024 (almost two years ago) featuring a similar technique. If it looks impressive you’re being tricked by it. It’s just a series of stills from John Woo films, reskinned with an AI model, the AI errors cleaned up in Photoshop, then a few seconds of motion is added to each still frame, titling and credits added in After Effects, and a soundtrack generated in Udio (which has very dodgy badly pronounced Cantonese).

Did I go around saying Hong Kong cinema is toast? Of course not. Many of the same issues generative media suffers from today were slightly worse back then. The biggest change since has been the introduction of talking characters.

There will always be AI fan boys online who will read my breakdowns and say “But look where it was two years ago. Imagine where it will be in six months!”. This is a ‘Number Go Up’ fallacy that has often been used by cryptocurrency fanatics and religious extremists when they point at their growth and claim that they will own the world in the future, because they fundamentally don’t know how the world works. In the case of AI fan boys they also don’t know how the technology works and that for exponential improvement to occur they would need exponential amounts of data, compute, energy and memory alongside incredibly difficult software engineering.

But they will keep shifting the goal posts anyway. Before they used to say ‘Wait six months’. Now they say ‘What do you think it will look like in 10 years?’

Of course generative media (that’s the proper term, not ‘AI filmmaking’) and generative VFX will continue to improve, but we need to remind ourselves why audiences flock to cinemas, buy discs and merchandise, and travel across the country or the world to meet actors and filmmakers at conventions and ceremonies. Tom Cruise often risks his life to entertain us and he’s the biggest star in the world because of it. Physical talent and celebrity matters to fans and followers. That’s why the Seedance fight demo above had to use the faces of two celebrities for wide reach and hype. Without that it would have just been two stuntmen and an AI filter. Nothing to talk about.

Similarly, if physical talent and celebrity didn’t matter spectators wouldn’t spend extraordinary amounts of money and time following their favourite athletes and sports teams. They would be content replacing real sports with video games alone. But that’s not how the world works. Humans, like all animals, are social creatures who need to belong to something bigger than themselves. If we don’t look up to people who achieved greatness with physical hard work, persistence and raw talent then we will lose our sources of inspiration. Hierarchy gives humanity something to strive for. Flat societies are artificially enforced by dictators and theocrats and they become violent because they suppress the creative mind and the desire to express oneself freely.

The entertainment industry (sports, film, acting, music, literature and art) is largely controlled by agencies for that reason - for onboarding and managing the talent that audiences look up to. Film production companies and studios come and go, but the agencies run the show.

If AI guys ever manage to make a somewhat decent full movie they're going to be in for a non-surprise when they see their movie being pirated on torrents because almost nobody wants to pay money to watch an mpeg made with next to no effort or minimum effort.

The only generative media enthusiasts who will have success will be those who hire skilled production professionals, writers and actors, and even then they will need to show behind the scenes production workflows. Audiences want evidence of investment, hard work and talent.

So in conclusion, is it over for filmmakers and is “Hollywood cooked”? Even if the fight scenes coming out of Seedance were genuinely generated with prompts only the model still produces tons of errors in the form of illegible gibberish text, morphing people, low quality details in the background, and other typical AI errors throughout the video content. It seems that this model is more optimised for motion rather than fixing all the known issues that plague video generators.

That makes Seedance 2.0 useless for the motion picture industry unless you need a quick dirty plate for VFX, a quick dirty B-roll clip, or lowish quality content for social media.

I look forward to testing Seedance myself, probably via ComfyUI so I can control the output better. I’m interested in seeing how cleanly it handles video to video and if it can do variations from a single input source. I will be checking to see how well it can handle detailed fight choreography instructions instead of just ‘two men fighting on a roof’ because then I’ll be able to tell if the model is receiving guidance from a pre-recorded video source or not.

Addendum:

This blog post has been read by many thousands of people around the world. Things get lost in translation whenever too many people speak at the same time and some of them are not tech savvy. So some clarifications below.

Robinson uploaded more clips to YouTube that has more constume and character changes, but featuring the same kind of fight choreography. I won’t believe these were from prompts alone until I try it myself. There have been too many let downs in the past.

The replies to his video upload feature the standard toxic hate speech towards “Hollywood” with no regard for the thousands of workers worldwide who earn a living from every single movie produced.

Some people seem to be confused by what I said. They are assuming Robinson uploaded green screen footage. As shown elsewhere, the green screen footage is from Bytedance’s library which they could be using to guide the models output without the user’s knowledge. In fact, we know that Bytedance’s new generation of models can fetch references. Here’s an example of how the Seedream 5.0 (Seedance’s little brother) image generator can fetch external data (on the web or a server) for references, something that until now models didn’t do automatically.

There’s also another misinterpretation. Some people assume that using the green screen footage is a form of “cheating” or “AI scam”. It should not be seen that way. Human performances should be used as input for generative media. That’s a win-win situation where skilled performers and actors are employed and the AI models help craft characters and scenes, all of which should be cleaned up and edited by VFX artists and editors.

I don’t write against the use of AI. I write against the hyperbole and toxic language surrounding AI. The idea that AI can do anything and everything without human guidance and will take over all jobs is toxic, nihilist, hyperbolic and factually incorrect.

Finally, I was interviewed by Newsweek here. I was slightly misquoted in the article because they had to compress all the quotes. For example, I didn’t make the claim that Robinson said the fight video was generated in 30 seconds. That claim came from this video I linked to.

Here is the full Newsweek interview:

1) What was your first thought when you saw the video, and what drove you to debunk it so thoroughly?

The video was being widely shared on LinkedIn by people who have no experience in film production, CGI or even generative media. Sometimes these are fake accounts created by marketing firms. Whenever a new model drops they always declare that the new model spells doom for filmmakers, photographers, actors, artists, and so on.

My first thought was ‘Ah, this looks like another video to video workflow’. 

Sketch to image, image to image, image to video and video to video are now the most common workflows in generative media production. Seedance’s site calls it ‘Reference to Video’ (R2V). Basically the concept is that the contours of shapes in the input video help guide the AI model to produce more predictable and reliable output. Prompts are used alongside the input media to describe what is in the scene itself. 

So I went to Seedance’s website and immediately saw that they used live action green screen footage as inputs for some of their demos. They made no secret of this so they are not to blame for any deceptive marketing. In fact, I often speak with engineers at AI companies and these guys are very honest, hard working and open about the limitations of the models. It is the marketing firms and influencers who have a tendency to overhype the abilities of AI models.

I’m pretty sure that Bytedance will be optimising Seedance for action scenes because martial arts are native to Chinese culture and popular worldwide, but for best results they will need video to video workflows like they demonstrate several times on Seedance’s website.

2) Can you tell me more about your background with film and your experience with AI? How existential do you think AI really is to Hollywood?

I studied drama, literature and film production in my youth with an eye to writing and directing films but because my parents raised me in the fashion industry I ended up mostly working in photographic and video production for the fashion industry rather than film. But the production skills, equipment, applications and workflow are the same.

Over the years we have seen stories that AI would destroy photography jobs and replace photography and video in the fashion industry. I have consistently debunked these ideas in public and in-house company communications. AI models do not know what new products look like without photos being taken in the first place, and consumers demand that photos show products authentically (even when retouched). If fashion imagery isn’t accurate that can result in sales dropping badly or an increase in refunds.

My predictions turned out to be true. AI has not destroyed photography. At most we are now seeing generative images being used to compliment photography. For example, in Photoshop we use Adobe Firefly’s Generative Fill tool to remove creases or to extend backgrounds. We are also seeing image to video being used - this adds one or two seconds of motion to a photograph. None of this is perfect though. The AI output often requires manual clean up.

3) What frustrates you most about the conversation/hype around AI?

As mentioned above the marketing is toxic. It’s a form of hate speech that frequently attacks working people who have bills to pay and families to feed. Many workers, even in the digital creative field, are not technologically savvy so they become demoralised easily by toxic overhyped marketing.

4) Your post went pretty viral - did Ruairi Robinson respond to you at all? Have you heard from anyone notable about it?

Robinson’s comments were irrelevant because they were not new. He was parroting an old line and influencers quoting him were producing clickbait.

5) Anything else you'd like Newsweek readers to know?

The output of the best AI models today are far below the very high requirements of media production. They might look impressive for 7 seconds on a little phone screen, but a full length 120 minute long movie on a big TV or cinema screen is a completely different thing. You can make a two hour long AI movie today, but you’ll have to cut a lot of corners, accept a lot of errors in the images, accept the video compression is very high, and accept that only a tiny percentage of AI/tech die hards will have the patience to sit through it or even pay for it.

Despite what AI fanatics say your readers, consumers and customers matter. They’re the ones who decide what will be successful or not. If they believe articles, books, comics, films and music were made with minimal to no effort then they will give you less attention and less money for it. Consumers aren’t the zombies some people claim they are. Just because they enjoy some cheap clothing, some fast food and unlimited streaming doesn’t mean they want everything to become quickly produced and quickly consumed junk.

Audiences and martial arts fans are not asking for generated fight scenes. They’re asking for more of this…

Everyone's a Studio Ghibli expert now

While I was offline for a while (working, coding and studying) a bunch of AI guys and anti-AI folks on social media became overnight experts in Studio Ghibli after OpenAI’s image generator let ChatGPT users generate images in the Ghibli style, or rather what westerners think is the Ghibli style.

The AI guys insisted this was a “game changer” and soon anyone would be able to generate any animation film from the comfort of their bed, while the anti-AI side overreacted by mislabelling videos of Miyazaki talking about computer animation to defend traditional animation.

I need to raise some points.

1. Unlike these overnight experts, I support the industry with hundreds of dollars worth of disc and book purchases every year. In the last year I spent about $1500 with ‘The Boy and The Heron’ blu-ray, art book and storyboards costing $300. If you support a filmmaker but you only watch their movies on a streaming service once every two years, you’re not supporting them. It seemed clear from the arguments I was reading that the AI side and anti-AI side had barely ever spent any money supporting the animation industry. They were just vying for attention on social media.

Recent purchases. Art books and storyboards should be your main source for studying animation.

2. Sites like Civit.ai have hosted downloadable LoRAs for generating Miyazaki-like images on your computer for almost two years. Where was the mass outcry then? What you saw in the last month from OpenAI and the media was marketing. You were emotionally and psychologically manipulated to think something new and threatening happened.

3. Generating images in someone's style doesn't mean anyone is going to respect you for it or let you commercialise it. At the point of sale copyright law will always apply. If you try to sell t-shirts with generated Totoro images a lawyer from Japan will reach out to you. They issue takedowns on eBay and YouTube all the time.

4. Commenters don’t know the difference between Miyazaki and Studio Ghibli. The studio doesn’t have a set style and employs various directors. Miyazaki’s style has changed over the years. He has said his influences have come from Jean Giraud to Roald Dahl and from Sanpei Shirato to Osamu Tezuka (who was influenced by Disney). One of Miyazaki’s most successful films was 'The Castle of Cagliostro', a departure from the style he is famous for.

5. A video of Miyazaki attacking AI was mislabelled. Even though he would probably feel the same way about gen AI (unless he was on his last legs and needed to save production time) the video was actually about scripted animation algorithms used in 3D CGI (often used in gaming). The video predates the deep learning models we see today. A different kind of AI.

6. Gen AI is no threat to people like Miyazaki for a reason anyone intelligent can understand. Audiences go to the cinema or buy discs to support them because of the sheer amount of muscular and intellectual effort that is needed to make a movie like ‘The Boy and The Heron’. They won't spend money on a LinkedIn bro who generated a semi-compelling moving slideshow from his sofa. Talent matters to audiences just like it matters to sports spectators. Don't let anyone tell you it doesn't matter.

7. Don't be tricked by clips on social media. Even if Gen AI did meet the very high requirement of filmmaking and animation, it will struggle to find an audience beyond a niche. For most there’s no reason to watch automated videos. It doesn't inspire. AI videos won’t generate the kind of revenue that cinemas need to stay open. That's the key. You have to invest a lot of money to make the kind of revenue that all the connected sectors require.

So ignore the uneducated opinions that gen AI will replace all filmmaking and animation. It won’t because parasocial relationships are extremely hard to displace with technology.

Before I end this post I want to highlight a thread I saw on the Stable Diffusion sub-Reddit. They were experimenting with the latest models to "generate animé" and even though the models appeared to output impressive images (with minimal movement), the users themselves were very critical of AI and understood that it will never compare to crafting true animation by hand. Here’s some quotes:

OpenAI releases text to video tool 'Sora' and instantly generates a wave of social media spam

A few hours ago OpenAI launched its text to video tool ‘Sora’ (Japanese for ‘sky’ but the same character 空 can also be read as ‘kara’ which means ‘empty’.) and predictably AI fanatics spammed film makers forums on Reddit and YouTube claiming the film industry’s days are numbered (they really mean Hollywood Jews, they will not apply this wild idea to film makers in the rest of the world) and that the end of the camera is coming too.

Madness.

It should be noted first of all that those wild opinions are from mostly 40-50 year old men (the typical AI YouTuber demographic) stuck in front of a computer all day who aren’t film makers and don’t have a real passion for film or story telling. They're the people generating novels with ChatGPT and flooding Amazon with these synthetic books that nobody wants to buy or making AI art that doesn’t sell. They’re the people who sent ChatGPT generated short stories and Midjourney artwork to Clarkesworld Magazine and then got banned from ever submitting again.

Let’s clarify what we are seeing here. Sora is neat, I really like what it can do. Who can’t be impressed? But it is a VFX and CGI tool. The term ‘computer generated images’ is more applicable to generative AI than 3D modelling and animation ever was. I’m sure someone out there with a big budget and time might make something neat, but it would be great if people who don’t understand filmmaking or audiences would not jump to conclusions.

With demos of Sora you are seeing a curated sample of low res videos in which the prompter has very little control over the output. Like all generative AI tools it is impossible to predict the full output which means a lot of credits and compute time is wasted generating over and over again. If the people who were bowled over by Sora looked closer they would have noticed videos replete with errors, such as an Asian woman who sometimes had two left feet, street signs with nonsense logos, billboards featuring non-existent jibbersih hanzi/kanji characters, and so on.

These issues are not easily fixed as the possible combinations of elements that can make up a scene are infinite. Bugs in the output will be a persistent problem, just like bugs in all software can never be fully quashed. Then you have the biggest compute problem - trying to animate character performances and mouth movements, which requires real time feedback, audio sync and the equivalent of doing multiple takes and shoots to get a character’s performance exactly where a story teller wants it to be. The best film directors have had their actors do numerous takes to fine tune a performance and the same applies in 3D CGI and here in GenAI.

There are also no controls for real time camera movement, changing the angle of a camera or changing the focal length or depth of field. Prompting is the most inefficient and slowest way to do these things in a virtual environment.

Films like Chariots of Fire had some cuts in the same scene shot at 24fps, 72fps and over 200fps. In animé, different animation layers/cels are animated on ones, twos and threes in the same shot. Generative video lacks these fine controls for frame rates and keyframing making the output, compute demands and costs hard to predict.

Other issues with using Sora include colour grading. Film editors and colourists understand how important log/raw footage is for the colour grading process. Art directors are always requesting sudden changes and those changes need to be done in real time. GenAI tools like Sora can only output compressed videos and you can’t change anything until you see the output. If you ask Sora to generate a video again with a different colour scheme the video itself might not be the same as the last - objects and characters could be in different positions with different errors from the last generation.

After generating a compressed video it is much harder to change the grade or colour correct. The quality will deteriorate. That’s OK for social media on a phone screen, but not for cinema. On a big screen even the smallest errors and artefacts are distracting. You don’t want audiences walking out of a screening because of quality issues, not purchasing titles because of bad reviews, or asking for refunds.

Even The Guardian’s article on Sora was hyperbolic, stating that the tool could generate video ‘instantly’ never mind the fact that that no video content can be generated instantly and that the videos themselves are extremely low resolution and feature a large number or errors that OpenAI highlighted on Sora’s page ‘Sora might struggle with simulating the physics of a complex scene or understanding cause and effect in specific scenarios. Spatial details in a prompt may also be misinterpreted, and Sora may find precise descriptions of events over time challenging’. To fix those errors will require an extraordinary amount of engineering and an unspeakably large amount of compute power to generate video, especially in native 4K or 8K with HDR support.

The film industry isn’t going anywhere and neither is filming actors on locations and practical sets. People pay to watch actors (including motion captured) and that’s not changing. When it comes to consuming entertainment, media and literature we’re talking about a shared human cultural connection. ChatGPT generated books don’t sell well because readers want to connect with real authors.

I grew up transitioning from celluloid and paint to digital photography and software. I learn every new technology that comes around, but because I have lived through all these cycles and understand consumers from a business and fan perspective I never fall for hype.

I remember clearly in the late 90s when there was fear that CGI would replace actors. It was all over the media. Paul Newman had it written into his family estate that if technology ever allowed him to be revived after he passed way that permission would never be granted. He wanted his likeness to remain his own. In 2002 Andrew Niccol of Gattaca fame made a satire called ‘Simone’ about generative AI and synthetic actors.

It never happened of course, even though CGI at its best is excellent it is never good enough. All it did was complement film. James Cameron worked as hard as possible to make Avatar as lifelike as possible but even the sequel looks like a high resolution video game composited with film footage. Hard surfaces are much easier to recreate than organic lifeforms and even water.

No new technology completely displaces and replaces what came before it. Classical instruments weren’t killed by synthesisers and Logic Pro samples. Ebooks didn’t kill books. Streaming didn’t kill vinyl records (vinyl ended up outliving the mighty iPod!). The best film directors in the world still shoot on film. Things co-exist.

We were also told that CGI would replace all traditional animation. When interviewed about his anthology ‘Memories’ which used CGI for a number of difficult shots, the great mangaka and Akira director Katsuhiro Otomo said ‘Because I draw pictures, I don’t have a plan to move away from 2D to the main use of 3DCG. 3DCG anime is like animating dolls, so people like me who have thought through the use of drawings do not have much idea about it. To begin with, it’s certainly true that Japanese like pictures with ‘contour lines’. I don’t think 2D anime will be rendered entirely obsolete, but it will stay as one of a number of diverse choices.’

Over 25 years later 2D anime is more popular than ever and Otomo’s words were prophetic. Yet despite all the evidence, you can still find tech fetishists in software engineering who insist to you that 2D animation and film photography don’t exist now. They live in a bubble so tight and small they can’t see the world outside.

At the end of the day audiences and consumers decide what becomes successful or not. You can have the most outrageous technology in the world but if your content annoys the public it won’t sell. Look at Ghost in the Shell. In 2002 they did a CGI update of the anime classic. Fans hated it and will always prefer the original. A decade later they did a live action movie remake with even better CGI. Fans hated it that too, this time for a variety of reasons.

VFX tools like these video/image generators can be incorporated into your work and if you do it smartly then it is no different from when Ryuchi Sakamoto pioneered electronic music and with the Roland MC-8 Microcomposer he introduced automated synthesiser playback.

Sakamoto never abandoned playing a classical piano in front of an audience though and as a classical composer he scored films such as ‘The Last Emperor’ and ‘Merry Christmas, Mr Lawrence’. He posthumously continues to perform on a grand piano in the mixed reality concert experience ‘Kagami’, combining the classic and the virtual even after he passed away.

Learn everything, absorb what is useful, incorporate technology into traditional arts and crafts, reject hyperbole, lovingly handcraft things that people will love, and don’t spam. The better your work is, the more of yourself that you put into your work, the more fans will reward you for it. Generative AI will have a permanent image problem associated with spam, memes making fun of AI errors, trolls hiding behind AI to mock creative workers, misinformation and climate impacts. You won’t have this image problem.

As mentioned in the first paragraph, Sora can also mean ‘empty’ so I expect that will end up describing a lot of the hype and promise of AI generated imagery replacing traditional filmmaking and photography.

Claims that AI will replace or displace most jobs are bogus

We are being told by finance bros, Twitter cretins and LinkedIn lunatics that AI (a buzzword that can mean almost anything now) will displace or replace anywhere between 40-90% of workers, enhance our productivity and make us more efficient, that it will free us up from hard work and give us more leisure time, and even more absurdly, that it will create a world of abundance for all.

Let’s break those claims down.

1. It is impossible for “AI” or robots to do tasks that require the level of dexterity and flexibility that only the human mind and musculoskeletal system can pull off, even ChatGPT says it would be impossible. In real life, unlike science fiction, robots need a degree of bulk to be stable and are not good at self maintenance. AI, being software, will always be buggy and the more tasks you try to teach a system the more buggy and resource hungry it becomes. If robots and AI could displace significant numbers of workers it would come with reduced reliability, reduced dexterity and increased unpredictability in many fields.

2. Microsoft, Meta and Google are talking up a big game about AI, but just take a look at the state of their platforms and Windows 11’s bloated and buggy condition. Google and YouTube are happy to host fake and scam ads so their moderation tools are failing to detect wrongful activity, unless they are allowing it. Instagram is infested with bots and sex pests - their AI moderation doesn’t protect users. Windows 11 still randomly crashes, looks like it was designed by a 12 year old in Microsoft Paint and users are already trying to uninstall or remove the Bing Chat bloat. That’s an operating system under development for almost five decades and it is a mess, so it’s not hard to imagine how bloated and buggy their future Godputer would be like in practice. There will also be issues somewhere and expectations will come back down to reality.

3. The people making such claims don’t have domain expertise of all the jobs and sectors they are talking about. They are salesmen, newsletter shills and report writers who attach themselves to whatever the latest trend is. Some of them were raised by house servants or at the top of a caste system, so they never learned to respect working people anyway. If their reports and posts are super optimistic and buzzwordy, and if they fail to mention the technical limitations and implementation problems of any new technologies, it’s because they don’t really know what they’re talking about. They’re no different to Deepak Chopra talking about quantum physics.

4. Many sectors are already operating at peak efficiency. We know that because we produce far more goods than we need and generate tons of food, electronic and clothing waste. We actually need to produce less, produce on demand, have more local production, higher quality more expensive long lasting goods, more locally repairable goods, and more just-in-time production and shipping. That’s something the polluting Sheins of the world don’t want to hear about. AI does’t solve this problem. Human willpower and cooperation solves this problem. An AI can suggest people take action against over production, slavery and pollution (things we already know) but it requires actual people to make the decisions and do it.

5. Whenever sectors do use automation to increase efficiency, the time saved is filled up again by producing more goods, more content, more projects and expanding product lines. Employees do not end up working less, just differently. This is exactly what we have seen in creative workflows. As a production and post-production creative, I have used and implemented everything from Photoshop Actions to machine learning based tools in our workflows to speed up work and reduce mental stress. The result of efficiency gains allowed companies to ask us to produce more content. A decade ago we used to produce about 3 images per product. Today we are likely to produce up to 6 images per product and an optional video. Implementing machine learning and automation isn’t plain sailing either and often comes with bugs that are never fully resolved.

6. At the pharmacy where my brother works they recently installed a state of the art robot for stock tracking and dispensing drugs. It didn’t displace any workers and requires onsite and remote support whenever there’s a hardware or software issue. That’s just how robots are.

7. If the consuming public were happy with bots replacing people, then athletes and sporting events would have been replaced by bots and virtual sports already. Why spend $20 million on a footballer when a team of computer controlled footballers can play sponsored advert filled virtual matches? Golf is an extremely wasteful and inefficient use of land and resources. Why can’t that end and be replaced with virtual golf? Big Blue beat Garry Kasparov at chess in 1997. Fast forward 27 years, there's still no audience to watch AI chess players play against each other in AI chess tournaments. The technology has existed for years, but consumers (fans) won’t pay for that. They will pay to watch real athletes struggle to win. Likewise, consumers will always pay more to read books written by real people, not chatbots. They want to build an emotional connection with the author, visit the author at a meet up, and get a signed copy of the book. A book is not just words on pages.

8. Finally, if the cost of producing something, whether it is art, literature or clothing, is closer and closer to nothing then there’s little incentive for customers to want to pay you good money for whatever you are offering. Your offerings are a McDonald’s Happy Meal at this point, or worse. The world’s economy can’t be made up full of Happy Meal and fast fashion equivalents. Every sector depends on diversification of goods and services, from high end and artisanal to the low end mass produced.

I end this blog entry with a video of a delightful lady who runs one of Tokyo’s many popular food joints ‘Onigiri Bongo’. Japan already has a few restaurants with robot staff (they are gimmicks), but a robot cannot make a thousand onigiri a day without health and safety hazards and causing a mess, cannot build a rapport with customers and cannot make customers wait in a line outside for an hour every day. Connections, traditions and craft are important.

When I started my first novel Scrivener hadn’t been released yet.

Writing this science fiction novel took me 18 years of reading and research. Scrivener came out after I began working on it and over the years was so helpful and indispensable for managing all the notes and ideas.

Sometimes I would take an hiatus to read and research other things. Many ideas and scenes were revised or scrapped during those years but the central theme remained constant. I not only wanted the story to be ahead of its time but also contemporary enough to be relatable, so my bookmarks and notes kept growing and growing.

Finally I decided there was nothing left to study. The novel will be finished this summer. There will also be concept designs and artwork to accompany it.

Thanks to Keith of Literature & Latte for helping me stay organised for so long.

Recovered my old film school DV tape from 2001

Today I managed to finally capture my old film school DV tape. The tape had travelled with me for almost 20 years, from flat to flat and from country to country. I thought it wouldn’t have survived after so long. Tape degrades.

I was about to capture the tape in early 2020 but then covid came along and delayed those plans. I didn’t want to ask someone to capture it for me. I really wanted to enjoy the process of capturing tape just like I did when I was young. In fact, the first time I ever captured video computers weren't powerful enough to transfer live video from a camera. Computers needed a special targa capture card to import each frame individually as a targa sequence.

Finally covid subsided and after keeping an eye on eBay for a long time I found a Canon XM2 in excellent ‘almost new’ condition at a great price. The short film itself was filmed on the XM2’s big brother the XL1S, but the cameras are very similar internally. Video capture is somewhat similar to film scanning. You grab a coffee, set up the equipment, and then diligently perform the job of transferring media manually into the computer.

Connecting the XM2 for capture proved tricky. First, I had to use an old Mac with firewire. Second, Adobe Premiere stopped supporting miniDV capture a few years ago and there was no method to install a version of Premiere old enough that did still support miniDV. QuickTime still does allow firewire capture, but I discovered that the start of the tape had degraded from exposure to air and heat. Because of the damage to the tape, Quicktime was unable to capture video with audio, but it could capture the streams separately!

Capture done, you can see how little detail and resolution we worked with in those days. Imagine if we had 4K or 6K HDR cameras at the time! 🤯 The colours produced by Canon’s 3CCD system were great though. There is hardly any grading applied to the images below, in some scenes none at all.

Screenshots from ‘花’ (‘Hana’) a short film in Japanese that I wrote, shot and directed in film school back in 2001 starring my friend Ryoko who was a news reporter on Nihon TV at the time.

I made a vertical trailer for social media which can be watched below.

Getting it right requires time...and feedback

My favourite camera will probably always be my Leica M3, a custom version with a genuine Italian rosewood body. Whenever I take it to camera shops for servicing it always receives the same compliment 'It's a unique piece!'

Leica M3 (photo taken with an iPhone :p)

I've used just about every type of camera over the years, but what attracted me to the M3 was that Leica put over a decade of research into it because they wanted to make sure they got the M series just right with the very first release (an extremely rare feat for any device). 

Over that decade, Leica frequently interacted with customers to help them design the M3. Users wanted it to be streamlined and ergonomic compared to the irksome and intimidating Leica III. Because the principal market was street photography, the M3 also had to feel second nature to users so that they could quickly capture moments around them. It also had to be easy to repair and recycle.

It was one of the earliest examples of a company asking for global customer feedback and beta testing the hell out of the product. The incredible results of that collaboration haven't been replicated so well since. Evidence of that can be seen in the fact that people still enjoy using the M3 65 years later.

Only one change was made during the M3's life-cycle - a change from a double stroke to single stroke advance lever (both equally useful). As time went by, Leica added a few more bells and whistles to the M series that weren't possible in the early 1950s, and sometimes they made mistakes in doing so, but the tradition of keeping their renowned product line pure still exists today in the M10.