Been tinkering on this Olmsted-inspired map of all the trees in NYC for a long time - just added some more features (seasonal colors and better search/filtering) recently.
I don't have much to say about this post other than to vigorously agree!
As an engineer who's full-stack and has frequently ended up doing product management, I think the main value I provide organizations is the ability to think holistically, from a product's core abstractions (the literal database schema), to how those are surfaced and interacted with by users, to how those are talked about by sales or marketing.
Clear and consistent thinking across these dimensions is what makes some products "mysteriously" outperform others in the long run.
I find this perspective bizarre. Though I'm not happy about it all being centralized, the closest thing we have these days to the very niche phpBB forums of the 2000s is various subreddits focused on very specific topics. Scrolling through the front page is slop, sure, but whenever I'm looking for perspectives on a niche topic, searching for "<topic> reddit" is the first thing I do. And I know many people without any connection to the software industry who feel the same way.
Perhaps swearing at the LLM actually produces worse results?
Not sure if you’re being figurative, but if what you wrote in your first comment is indicative of the tone with which you prompt the LLM, then I’m not surprised you get terrible results. Swearing at the model doesn’t help it produce better code. The model isn’t going to be intimidated by you or worried about losing their job—which I bet your junior engineers are.
Ultimately, prompting LLMs is simply a matter of writing well. Some people seem to write prompts like flippant Slack messages, expecting the LLM to somehow have a dialogue with you to clarify your poorly-framed, half-assed requirement statements. That’s just not how they work. Specify what you actually want and they can execute on that. Why do you expect the LLM to read your mind and know the shape of nginx logs vs nginx-ingress logs? Why not provide an example in the prompt?
It’s odd—I go out of my way to “treat” the LLMs with respect, and find myself feeling an emotional reaction when others write to them with lots of negativity. Not sure what to make of that.
I would like to propose a moratorium on these sorts of “AI coding is good” or “AI coding sucks” comments without any further context.
This comment is like saying, “This diet didn’t work for me” without providing any details about your health circumstances. What’s your weight? Age? Level of activity?
In this context: What language are you working in? What frameworks are you using? What’s the nature of your project? How legacy is your codebase? How big is the codebase?
If we all outline these factors plus our experiences with these tools, then perhaps we can collectively learn about the circumstances when they work or don’t work. And then maybe we can make them better for the circumstances where they’re currently weak.
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I think the utility of generating vectors is far, far greater than all the raster generation that's been a big focus thus far (DALL-E, Midjourney, etc). Those efforts have been incredibly impressive, of course, but raster outputs are so much more difficult to work with. You're forced to "upscale" or "inpaint" the rasters using subsequent generative AI calls to actually iterate towards something useful.
By contrast, generated vectors are inherently scalable and easy to edit. These outputs in particular seem to be low-complexity, with each shape composed of as few points as possible. This is a boon for "human-in-the-loop" editing experiences.
When it comes to generative visuals, creating simplified representations is much harder (and, IMO, more valuable) than creating highly intricate, messy representations.
Install Cursor (https://cursor.com), go into Cursor Settings and disable everything but Claude, then open Composer (Ctrl/Cmd + I). Paste in your exact command above. I bet it’ll do something pretty close to what you’re looking for.
I've completely switched over to Cursor from Copilot. Main benefits:
1. You can configure which LLMs you want to use, whereas Copilot just supports OpenAI models. I just use Claude 3.5 for everything.
2. Chatting with the LLM can produce file edits that you can directly apply to your files. Cursor's experimental "Composer" UI lets you prompt to make changes to multiple files, and then you can apply all the changes with one click. This is way more powerful than just tab-complete or a chat interface. For example, I can prompt something like "Factor out the selected code into a new file" and it does everything properly.
3. Cursor lets you tune what's in LLM context much more precisely. You can @-mention specific files or folders, attach images, etc.
Note I have no affiliation whatsoever with Cursor, I've just really enjoyed using it. If you're interested, I wrote a blog post about my switch to Cursor here: https://www.vipshek.com/blog/cursor. My specific setup tips are at the bottom of that post.
Ah, my mistake. "Meta AI" can generate both text and images, but apparently text prompts are handled by Llama 3.1 while image prompts are handled by Emu. I initially struggled to find the name of the image generation model.
Many AI-generated images you encounter are low-effort creations without much prompt tuning, created using something like DALL-E or Llama 3.1. For whatever reason, the default style of DALL-E, Llama 3.1, and base Stable Diffusion seems to lean towards a glossy "photorealism" that people can instantly tell isn't real. By contrast, Midjourney's style is a bit more painted, like the cover of a fantasy novel.
All that being said, it's very possible to prompt these generators to create images in a particular style. I usually include "flat vector art" in image generation prompts to get something less photorealistic that I've found is closer to the style I want when generating images.
If you really want to go down the rabbit hole, click through the styles on this Stable Diffusion model to see the range that's possible with finetuning (the tags like "Watercolor Anime" above the images): https://civitai.com/models/264290/styles-for-pony-diffusion-...
Just to clarify, are you saying these are relatively new BEV trucks coming into your shop? If so, do the mileage issues usually boil to battery degradation due to driver behavior as you’re suggesting, or is it because the EPA rated mileage was unrealistic in the first place? Or both?
I was a software intern at Bridgewater in 2013. My impressions from that time are that Bridgewater had an interesting, unique, and very intentional culture, but at some point the firm grew and Dalio started thinking about how to scale that culture. He wrote the Principles book and had everyone read and discuss it; the Dots app was implemented; etc.
The core cultural values seemed reasonable to me, but the efforts to scale the culture felt heavyhanded and seemed like they sometimes backfired. Attempting to quantify someone's "believability" based on subjective data collected on an iPad app was a bit silly and easily gameable. The fact that Dalio and other executives scored highest on basically every facet was an obvious sign that the system was a bit farcical.
Maybe the company managed to solve some of those cultural scaling challenges after 2013? I wasn't around to see what happened after.
In the past year, I've gone from near-zero understanding to pretty deep expertise in the domain of electrical grid interconnection as a product engineer. Here's how I went about it.
I think all the other comments saying "read a lot" and "talk to everyone" are correct first steps, but for me, consuming information has diminishing returns after a short while. After you've reached a point where your brain feels like it's exploding, you should switch your focus to outputting information.
If you're a "write things down" person, then write a synthesized document explaining everything you've learned, and then ask a few trusted coworkers to tear it apart.
If you're a "talk out loud" person, schedule time with coworkers to have a "teachback session" where you give a presentation about everything you've learned. Again, ask them to tear it apart.
It's crucial to build trust with a few coworkers who are willing to critique your output. Get them to rip everything you've created to shreds. Whenever you write or say something that's even slightly off compared to how someone in the industry would say it, make sure you learn about that, and learn how someone in the industry would say it.
This focus on getting the language right - especially the colloquial language of how people actually describe things day-to-day - is important for every role, but I assume it's especially important in marketing, where you need to be able to use the precise language that your customers use.
tl;dr: Read/talk to people at first, but switch to writing/presenting ASAP. Solicit and internalize as much critical feedback as you possibly can.
> Radia estimates the larger turbines could reduce the cost of energy by up to 35% and increase the consistency of power generation by 20% compared with today’s onshore turbines.
Not sure what that translates to in terms of energy output over time.
As for the sibling "Why not airships?" question, the article says:
> Blimps can’t land in windy conditions. Helicopters are more costly than airplanes, and flying with a dangling blade designed to catch wind would prove complex and dangerous.