An off-kilter review of Dune 2

In this house, we obey the laws of thermo dynamics

I hope to say this will be my first blog of many. (Outside of my profession.) I’d like to use blogging as a method of reflection, creative expression, and professional development. 

This is a story that expands on my review of Dune 2. If you’re curious as to why the title is a direct Simpsons quote – there’s 2 things I have to tell you.

  1. I’m feeling nostalgic.
  2. It’s relevant, I promise.

An amateur review of Dune 2

I left the cinema after watching Dune 2 in a similar manner that I did with the first. Filled with questions, confusion, and a loss as to why I loved what I just watch. This story is an explanation in answering that question. Why do I love this film? Why do I care so much about how the worms take in enough daily calories or how the stillsuit thermodynamics work? (Ok, it’s a bit of a stretch.) I’ve learned that the answer doesn’t lie in a single macro-feature of the film (plot, word-building, sound), but in how it combines them all together.

After watching both of the 2 Dune films, there’s one thing that was clear to me. Denis Villeneuve had a clear vision of what he wanted – and put together the perfect team to execute his vision. When I find myself in the midst of a Marvel film, I often feel like the film is strung together by a committee. This leads to jarring moments that remove me from any suspension of disbelief. A line out of place, an over the top camera effect, or even an attempt to entire plot line can impact this. In trying to optimise a film for everyone – I find much of modern blockbuster releases (particularly the Marvel franchise) loses any sense of identity. This just isn’t the case with Dune. Through a strong vision and a diverse cast/production crew playing towards their strengths, Dune successfully has me engaged on multiple levels.

I haven’t felt this way about a film franchise since the original Lord of The Rings trilogy. A sound and score that gives me goosebumps. (Zimmers’ never failed at that.) A cinematic vision that’s both refreshing and of a scale that feels bigger than the screen it’s on. A world that’s deep with complexity, political nuance, and philosophy that makes me want to learn more about its lore. And performances that bring these elements (+ more) to life.

Digging deeper

I’ve recently learned about a piece of software used by the likes of Disney, Warner Brothers, Lionsgate, Netflix… the list is quite expansive. In-fact let’s just say as of March 2024 it’s used by the majority of production companies and streaming services we’re familiar with. It’s called Cinelytic. It claims to “support studios and independent content companies to make faster and better informed greenlight, acquisition, and release decisions.”

What does this mean? Well – it essentially uses vast amount of film data, customer preferences, and real-time tools to:

  • Find the optimal casting.
  • Simulate and deliver the optimal distribution method and release date.
  • Provide sophisticated financial models to ‘save time and reduce errors’
  • Offer ‘predictive forecasting intelligence’ through ‘revolutionary AI and machine learning’

Simply put: it helps studios turn what was once a create journey – and form of expression into a machine of vapid content production. Gone are the days of creative risk and exploration. We’ve entered a time where the content you consume on your small screens is algorithmically curated to keep you engaged as much as possible. And the content you watch on the big screen is less and less a creative vision, and more and more an ‘optimised’ attempt to generate money for the studios that apparently don’t have enough already.

This is somehow simultaneously revelationary and unsurprising. How can we come to this incongruous conclusion? I’m afraid I don’t quite know. We’ve complacently walked into some kind of meta-simulacrum.

What’s the problem?

‘Cinelytic can optimally simulate content we desire, based on our behaviours, and increase the odds more people will enjoy new releases.’ Well it also means that any creative risks may be avoided. Whereas in the past – bad films would eventually develop a cult following. Bad films today are computationally bad. In trying to cater to everyone they’re a high-production value mess of mediocrity that will be lost amidst the thousands of similar forgettable films. Perhaps this is strong take but personally, forgettable art is a lot worse than bad art.

Don’t get me wrong – in my research proposal I look at a similar algorithm that replaces DJs. I propose: Imagine walking into a club with no DJ. No entertainment booth. Your phone connects to a network of other clubbers, feeds your preferences to a computing system in the venue, and the music is mixed to deliver the ‘optimal set’.

It’s a problem that leaves me conflicted. On the one hand, you can argue that you can’t beat ‘optimal’ by definition. I would argue the big tech definition of optimal isn’t exactly truthful. It’s only optimal based on the resources it has access to. The scale of data is incomprehensible. We’re often told our devices know us better than ourselves. But there’s certain things you can’t capture with data. Things you can’t quantify. And so I’m left feeling concerned. I’m not going to give you a bull shit best of both worlds LinkedIn piece. I think this is the wrong direction for our creative futures.