The Happening Part 2
Arleen Jerdee
Simon Sinek is a spark that ignites passion and ideas. He envisions a world in which the vast majority of people wake up every single morning inspired, feel safe wherever they are, and end the day fulfilled by the work they do. As an unshakeable optimist, he believes in our ability to build this world together.
A trained ethnographer, Simon is fascinated by the people and organizations that make the greatest and longest-lasting impact. Over the years, he has discovered some remarkable patterns about how they think, act, and communicate and the environments in which people operate at their natural best.
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He continues to share inspiration through his best-selling books, including global best seller Start With WHY and New York Times best sellers Leaders Eat Last and The Infinite Game, as well as his podcast, A Bit of Optimism. In addition, Simon is the founder of the Optimism Company, a leadership learning and development company, and he publishes other inspiring thinkers and doers through his publishing partnership with Penguin Random House called Optimism Press.
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Mind you, this is coming from someone who is not a developer, nor do I have deep expertise in training large language models. What I designed is a system that used GPT to do a bunch of reasoning and content work.
First, I was building business products. Applications that would reduce the time and cost of work in professional services. Products like this need to be consistent and reliable. This is not always the case with GPT.
- True/False: Can GPT consistently determine what is true or false based on a large amount of data (lots of tokens)?
- Reasoning: More complex than True/False, we ask GPT to analyze a large amount of data against some criteria and that needs to turn into a valuable insight or output.
It is possible to get very clear and repeatable answers from GPT, but for large amounts of information , the consistent quality was lacking enough to make me timid about how trustworthy the results could be (with GPT 3.5 or 4).
Example: I asked GPT to example a large amount of property data to see if there is any environmental concerns that might complicate the sale of a property. I provided the rules in which to judge that scenario, and perhaps 7 or 8 times out of 10 times it would maintain the correct answer, those 1 or 2 times it would make the wrong assessment.
It's amazing what can be done when you throw a couple hundred million dollars at a training model, and what's Coming Soon! is going to be wild. This could be in the form of a GPT-4 TURBO or GPT-5, but here's the rundown on what that means:
- The volume of data that can be ingested and the picture window (how much information GPT can keep track of at any time) will get bigger and bigger. So in a relatively short time, I believe you will not have to parse or clean information before you give it to GPT with a prompt. That pretty much invalidates any coding work needed up front.
- The rate that the knowledge and reasoning engine has changed from 3.5 to 4 was amazing enough, and I believe OpenAI is sitting on their hands with GPT-5. It's likely ready, but they're giving us time to adjust to what we already have. GPT-5 will invalidate a lot of prompt engineering. You won't have to be as clever as you are right now to get stellar results.
I had the opportunity to speak with a family friend who happens to be a venture capitalist. He said a few things that instantly cleared up why I feel this is not the time (for me) to build products that are overly reliant on GPT.
When you build a product that is 85% GPT, 10% UX and prompt engineering, and maybe 5% python/SQL, you're way too reliant on GPT, and you're only going to be around until there's a big enough product update that invalidates the value of your overlay.
We received severe thunderstorms with hail a few days ago, which bruised my woad plant a little. I attempted to extract the woad blue pigment from the bruised leaves but was unsuccessful. I think it was too early to harvest them for pigment extraction. I must wait patiently.
The growth of Japanese indigo has been relatively prolonged. I might have to give them a nitrogen boost or do some research to troubleshoot. Although, the plants on my balcony are growing much better. I love this part of gardening when you are challenged and learn a lot during the process.
I have done ALL of Jyotsna's courses and they are brilliant. The presentation is really nice and the content has set me off on a kind of obsessive exploration of hunting for colours in nature, making pigments and the excitment of seeing what colours will come (often unexpectedly) from a plant. If you are interested in pigment making then do those courses and then the paint making one as you will then have your own 'materials' ready. Go for it!
My first introduction to the world of making my own watercolours was when I stumbled upon Jyotsna's website . And therein I was sucked into her beautiful , natural , organic and colourful world . Needless to say , I spend a lot of time going through her site and gaining from her knowledge . So when she announced an online resource I immediately signed on. It is now very helpful to have lifelong access to her online lessons in basic watercolour making from pigments . Her scientific background adds to making this resource very organised . I find her energy and happiness in doing what she does both contagious and inspiring , and this comes through in her videos.I am sure I will keep returning to her online platforms and also her course material on a very regular basis , as I continue to find and make my own way towards creating my own sustainable watercolours
The courses are absolutely amazing, and I plan to sign up for all of them! The content is very comprehensive and easy to understand. Jyotsna has a PhD in chemistry and not many other people in the world would have her intimate knowledge of the dye and ink-making processes. Her passion for sustainable art making and organic farming is second to none. The price of the courses are also very affordable, and I would highly recommend this course to anyone who is interested in sustainable art practice.
I vividly remember the icily electrifying effect of the opening scene of The Happening, a stroke of genius in its merciless, methodical stripping away of our humanity, into machines of flesh whose prime directive was to terminate ourselves.
The existentially panic-inducing vision of normality switched to nightmare reminded me of a scene I saw a year before, in Zodiac, where the couple at the lakeshore are set upon by the killer in a beekeeper costume, announcing their demise in a stentorian voice of the cruellest kind. Where David Fincher played on suddenness and shock effect, however, M. Night Shyamalan took a more subtle, creepier route to a similar destination.
The next scene employs a louder, direct shock approach to a still satisfying effect: at a construction site workers start to jump off a tall building in a mass self-extinction event. You would now expect the sort of masterpiece that mainstream American cinema can give us: a highly dramatic story, staged with such elegance, invention and impact as to lift it up to a plane of great resonance.
What we get instead, after a tolerably engaging classroom scene, is a gradual, almost systematic dismantling of everything that made the first two incidents distinctive, infectious cinema. Watching The Happening is like being trapped inside the mind of Kevin Wendell Crumb of Split and Glass: two split identities, one delivering suicide scenes of an unflinching nature as well as other intermittent moments of resonance, and another identity insisting on interrupting the program with quirky humour, kooky characters, vague personal conflicts, nebulous character motivations, and at times inexplicable behaviour.
Compared to The Green Effect, the original script for the film, The Happening has been considerably strengthened scientifically. For example, the bees disappearing is a real-life problem which at the time was only starting to attract public attention. (Speaking about topicality, the Iphone arrived just the year before the film and is actively used for playing video clips of far-away suicides and greatly helps them spread virally, a human parallel to the suicide epidemic.) Its science and themes of environmentalism are summed up and discussed in chapter nine (pages 167-188, try Google Books here) of the book Homer Simpson Marches on Washington: Dissent through American Popular Culture. (A lot of the science mentioned in the film seem to be sound: red tides are real, plants have defence mechanisms [here, here and here], and they can communicate.)