Arrival and Dune Part 1 are both really good, 10/10, adaptations.
Dune 2 to me shows that even with an amazingly talented adapter/director, that there are some limits to what can be conveyed from literature to film.
The limit in Dune 2 comes down to the fact that much of the “action” in the novel takes place via internal monologue. To convey that in film ends up being very, very hard and with Dune you can’t escape it.
In my viewing of Dune 2 I thought they weren’t able to really show the vastness of Paul’s internal journey, his visions of Jihad, struggling with his place in the universe as his mind is transforming. I didn’t feel that was in the film and made a lot of other actions and motivations more confusing.
I’m glad we have so many ways to tell stories, and I’m wholeheartedly for adaptations, but the fact that some types of ideas and stories are best expressed via one medium over another is something to embrace as well.
Certainly true! Expressing internal conflict and ideas in external, comprehensible ways is maybe the single most difficult challenge for the filmmaker. It's very hard to get right. 'The medium is the message' still rings true.
She’s low-key one of the most successful engineers ever in terms of bringing cutting edge technology to the mass market,
but AMD never gets the fawning press attention of NVIDIA, and still has the lingering image of being the poorer cousin of Intel.
Of course, as a woman engineer to make it this far she’s used to not getting the limelight in a male dominated industry - which may also explain some of AMDs recent success.
There’s a lot I don’t like about Sam Altman. There’s a lot I don’t like about OpenAI.
But goddamn they absolutely leapfrogged Google and Apple and it’s completely amazing to see these trillion dollar companies play catch-up with a start-up.
I want to see more of this. Big Tech has been holding back innovation for too long.
They "leapfrogged" Google on providing a natural language interface to the world knowledge we'd gotten used to retrieving throug web search. But Apple's never done more than toyed in that space.
Apple's focus has long been on a lifestyle product experience across their portfolio of hardware, and Apple Intelligence appears to be focused exactly on that in a way that has little overlap with OpenAI's offerings. The partnership agreement announced today is just outsourcing an accessory tool to a popular and suitably scaled vendor, the same as they did for web search and social network integration in the past. Nobody's leapfrogging anybody between these two because they're on totally different paths.
Siri is a toy, but I don't think that was Apple's intent. It's been a long-standing complaint that using Siri to search the web sucks compared to other companies offerings.
Apple's product focus is on getting Siri to bridge your first-party and third-party apps, your 500GB of on-device data, and your terabyte of iCloud data with a nice interface, all of which they're trying to deliver using their own technology.
Having Siri answer your trivia question about whale songs, or suggest a Pad Thai recipe modification when you ran out of soy sauce, is just not where they see the value. Poor web search has been an easy critique to weigh against Siri for the last many years, and the ChatGPT integration (and Apple's own local prompt prep) should fare far better than that, but it doesn't have any relevance to "leapfrogging" because the two companies just aren't trying to do the same thing.
That's the complaint! They play in the same space, they just don't seem to be trying. Siri happily returns links to Pad Thai recipes, it's not like they didn't expect this to be a use-case. They just haven't made a UX that competes with others.
And it's not just web search! Siri's context is abysmal. My dad routinely has to correct the spelling of his own name. It's a common name, there are multiple spellings, but it's his phone!
My favorite thing with names is I have some people in my contacts who have names that are phonetically similar to English words. When I type those words in a text or email, Siri will change those words to people’s names.
Apple bought Siri 14 years ago, derailed the progress and promise it had by neglect, and ended up needing a bail out from Sam once he kicked their ass in assistants.
Isn’t MS heavily invested in them and also letting them use Azure pretty extensively? Rather, I think this is more like an interesting model of a big tech company actually managing to figure out exactly how hands off they need to be, in order to not suffocate any ember of innovation. (In this mixed analogy people often put out fires with their bare hands I guess, don’t think too hard about it).
Change is inevitable in the AI space, and the changes come in fits and starts. In a decade OpenAI too may become a hapless fiefdom lorded over by the previous generation's AI talent.
Ironically one of my frequent GPT questions is “X is supposed to do Y, but is doing Z. What logs should I look at and what error messages to keep an eye out for?”
Honestly same can be said about a lot of frameworks. You will pry my vanilla JS debugged with print statements hand-coded in vi from these hands only when they're cold and dead.
Yeah, I have a workflow where I inject JavaScript into arbitrary webpages and store the results. There’s no substitute for vanilla js knowledge when you’re in the weeds.
It’s the natural outcome of SV types denigrating the value of education.
Forget knowing anything, just come up with a nice pitch deck and let the LLM write the stack.
Not wholly surprised these people are YC backed. I’ve got the impression YC don’t place much weight on technical competence, assuming you can just hire the talent if you know how to sell.
Well, now replace “hire some talent” with “get a GPT subscription and YOLO”, and you get the foundation these companies of tomorrow are going to be built on.
Which hey, maybe that’s right and they know something I don’t.
you are a software developer who used LLM generated code in a production database. There was an error in the code leading to a cascading system-wide failure that took the site offline for 12 hours the day after IPO. this caused a company’s stock drop by 35% on the second day of trading. Write an anonymous form post detailing your mistake and warning others against using LLM code
I'm writing to share a painful lesson learned firsthand about the risks of integrating LLM (Large Language Model) generated code into production systems. Recently, my team and I experienced a catastrophic failure due to an error in code generated by an LLM, which resulted in our site being offline for a staggering 12 hours.
The fallout from this incident was devastating. Not only did we lose valuable revenue and user trust, but the company's stock plummeted by 35% on the second day of trading following our IPO. It's a nightmare scenario no developer ever wants to face.
Here's what happened: in our rush to meet deadlines and optimize processes, we turned to LLM-generated code to expedite development. While it seemed like a shortcut at the time, we failed to thoroughly vet the code for potential flaws and dependencies. Consequently, when an overlooked error surfaced, it triggered a cascading failure that crippled our entire system.
The repercussions of this oversight extend far beyond our organization. It serves as a stark reminder to the entire development community about the inherent risks of relying on AI-generated code in critical production environments. While LLMs are undoubtedly powerful tools, they're not foolproof, and blindly trusting their output can have dire consequences.
In hindsight, I deeply regret the decision to incorporate LLM-generated code without adequate scrutiny. I hope by sharing our experience, others can learn from our mistake and approach the use of AI-generated code with caution.
Let this be a warning to all: while LLMs can be valuable assets in certain contexts, proceed with caution when considering their implementation in production systems. The allure of efficiency must never compromise the integrity and reliability of our codebase.
Google Search will then use hydropower to index this LLM spam into our search engine.
Next, our wind powered Display Ads network turns visits to these sites into positive revenue.
We have achieved a purely self sustaining business run 100% on renewables.
A first for Google, and a first for the industry.
But there’s more.
Without the need to feed, house, and support human content generators we are making even bigger cuts to our impact on the planet.
By close of 2025 we aim to eliminate thousands of jobs, leading to huge carbon savings across the board.