You're describing a Taravangian prompt situation (a character in a book series who wakes up with a different/random intelligence level each day and has a series of tests for himself to determine which kind of decisions he's capable of that day). https://coppermind.net/wiki/Taravangian
For many of us, even if drawing that line exactly is debatable, a prompt-generated image, where the "artist" didn't interact with any of the pixels is across the line for "too much AI".
It can definitely take creativity and fortitude to get an AI model to draw what you want it to. But if you worked at a fantasy publishing house and commissioned a cover painting, it might take a fair amount of work for you to get the artist to create something in line with what you envisioned. But you wouldn't get artistic credit for the resultant painting; the artist would! If AI is creating the piece, it is the artist; and you're merely the commissioner of the work.
What I like about this piece is how it shows the technical prowess underpinning the visual outputs in a film like what Disney puts out.
I only wish it went further! There are a ton of lessons those of us outside films/games could learn from working in that kind of deadline-consttrained innovative landscape. Tell about how you fought against the rendering deadlines and sped up the snowscape frames by 30% to get it in under the wire!
Instant Pot Garbanzo beans/chickpeas with a tiny bit of salt are a favorite in my home. Creamy, savory, and delicious! Cannellini beans are also lovely.
Imperva, a Thales Company | Data Scientist for Bot Detection | Full-Time, Hybrid (Vancouver)| imperva.com for the company | Hiring two candidates.
We are looking for talented, experienced Data Scientists who are ever curious about data problems and eager to write code to get those problems solved.
Members of this team creatively find problems as well as solve them. Much of the work is analyzing detection mechanisms and bot behaviors, making advances in realtime bot detection and mitigation, and implementing those advances in production.
The positions are on the team I lead. The data and problem are interesting, data is intrinsically useful in bot detection, and there is no shortage of challenge to working a difficult problem. Python, SQL, and Rust are some languages we're currently using for most of our work. The ideal candidate has worked as a software engineer and data scientist and wants to do both.
There's a fundamental reality that shapes both Netflix and Spotify's trajectory: content licensing. 2012 Netflix had access to vastly more of everyone else's library, so it was closer to an indexed search of what was available that one could watch and then getting that video onto your screen. Over time, other companies understood that they were underpricing their content and Netflix was reaping the benefits. Once external forces adjusted, the TV/film bidding wars began. Today, netflix doesn't have nearly as much content as they used to have.
That risk (losing all content and facing extinction) is what pushed Netflix in the direction of being a content-producer, rather than a content aggregator. I agree with everyone's points on the influence of the median user in diluting the quality of the content Netflix produces, but that's not the only forced that pushed us here. Spotify faced a similar crossroads and decided to broaden beyond music once they started losing bidding wars for licensing.
Being a faster horse wasn't an option available to either Netflix or Spotify; there is no path for a 'better 2012 version of netflix or spotify' in 2025. They each had to change species or die, and they chose to keep living.
Imperva, a Thales Company | Data Scientist for Bot Detection | Full-Time, Hybrid (Vancouver)| imperva.com for the company | Hiring two candidates.
We are looking for talented, experienced Data Scientists who are ever curious about data problems and eager to write code to get those problems solved.
Members of this team creatively find problems as well as solve them. Much of the work is analyzing detection mechanisms and bot behaviors, making advances in realtime bot detection and mitigation, and implementing those advances in production.
The positions are on the team I lead. The data and problem are interesting, data is intrinsically useful in bot detection, and there is no shortage of challenge to working a difficult problem. Python, SQL, and Rust are some languages we're currently using for most of our work.
Imperva, a Thales company | Data Scientist for Bot Detection | Hiring 2 candidates | Vancouver, Canada | Hybrid
We are looking for talented, experienced Data Scientists who are ever curious about data problems and eager to write code to get those problems solved.
Members of this team creatively find problems as well as solve them. Much of the work is analyzing detection mechanisms and bot behaviors, making advances in realtime bot detection and mitigation, and implementing those advances in production.
The positions are on the team I lead. The data and problem are interesting, data is intrinsically useful in bot detection, and there is no shortage of challenge to working a difficult problem. Python, SQL, and Rust are some languages we're currently using for most of our work.
Imperva, a Thales company | Data Scientist for Bot Detection | Hiring 2 candidates | Vancouver, Canada | Hybrid
We are looking for talented, experienced Data Scientists who are ever curious about data problems and eager to write code to get those problems solved.
Members of this team creatively find problems as well as solve them. Much of the work is analyzing detection mechanisms and bot behaviors, making advances in realtime bot detection and mitigation, and implementing those advances in production.
The positions are on the team I lead. The data and problem are interesting, data is intrinsically useful in bot detection, and there is no shortage of challenge to working a difficult problem. Python, SQL, and Rust are some languages we're currently using for most of our work.
I'm largely in favor of SSO, but it's not without its downsides, going beyond capital costs: SSO can also be implemented in a way that introduces an onerous latency tax when using services.
Before they were acquired by Google, looker had a bunch of really engaged community support people, and the docs were great for what the product did. There were learning paths for different types of users and tutorials linked to references in a way that made sense. I learned a lot about effective documentation (and looker!) from going through what they had.
Even if 100 US-based community support folks were making $300K in total comp, why would you not spend $30MM to keep your $2.6B acquisition humming along? A bit mystifying.
For those unaware, this is a long-form article by the renowned (late) neurologist and writer Oliver Sacks about his personal mental and emotional experiences of what it was like to not feel his leg.
The piece is much more of a New Yorker style than a Paul Graham style. Enjoy it for what it is!
Nearly half of admitted white students at Harvard got in via a VIP lane, which is really high.
But that doesn't necessarily tell the story for what it would be like to apply to Harvard as a white student. There is a subtle yet important distinction in this.