HN user

tlack

1,931 karma

ex-CTO of .CO and POP.co

cofounder of http://www.modernmethod.com/, makers of destructoid and other fine internet blogry

current projects:

GLORP, a search engine - https://glorp.co classic car price science - https://classic.com

tweeter @tlack email lackner at gmail dot com

Posts42
Comments695
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blog.dnmfarrell.com 1y ago

I'm not mutable, I'm partially instantiated

tlack
225pts71
github.com 1y ago

Trap – Transformers in APL

tlack
95pts30
www.artnews.com 5y ago

Provisional Painting

tlack
1pts0
archive.fosdem.org 5y ago

AtomVM: Erlang and Elixir on ESP32/STM32/RP Pico/etc.

tlack
4pts0
dockyard.com 5y ago

Phoenix LiveView Updates: Introducing Uploads

tlack
1pts1
www.youtube.com 5y ago

TossingBot: Learning to Throw Arbitrary Objects (2019)

tlack
2pts0
medium.com 5y ago

Configuring Google Colab like a pro

tlack
3pts0
forums.swift.org 6y ago

Differentiable programming in Swift has been upstreamed to apple/swift master

tlack
1pts0
webrtchacks.com 6y ago

Breaking Point: WebRTC SFU Load Testing

tlack
2pts1
www.survivopedia.com 8y ago

Off-Grid DIY Project: Making Fuel From Algae (2018)

tlack
3pts0
github.com 8y ago

Show HN: Q-Flavored JavaScript Preprocessor

tlack
1pts2
themerkle.com 8y ago

South Korea to Permit Crypto Exchanges Under 6 Conditions

tlack
2pts0
blog.wolfram.com 9y ago

WolframScript: Wolfram/Mathematica's new CLI interface

tlack
2pts1
github.com 9y ago

WSL Terminal – Terminal Emulator for Bash on Windows

tlack
1pts0
www.creativeapplications.net 9y ago

OpenSurgery: DIY surgical robots

tlack
2pts0
getkerf.wordpress.com 10y ago

Kerf's approach to string interning

tlack
1pts0
github.com 10y ago

Beginnings of K interpreter written in OCaml

tlack
46pts12
sigmajs.org 10y ago

Sigma.js: a JavaScript library for graph drawing

tlack
201pts34
www.youtube.com 10y ago

AI-assisted code generation for React

tlack
6pts4
www.bloomberg.com 10y ago

Google exec: “your genome isn’t really secret”

tlack
2pts0
groups.google.com 10y ago

Tell HN: Q/Kdb 32-bit no longer free for commercial use

tlack
7pts1
news.ycombinator.com 10y ago

Ask HN: Founders of large tech companies that work from home

tlack
1pts0
berla.co 10y ago

iVe – Infotainment and Vehicle System Forensics

tlack
47pts24
www.bloomberg.com 10y ago

Amazon now offers one-hour booze delivery in Seattle

tlack
5pts0
news.ycombinator.com 10y ago

Ask HN: What Was Wrong with Display PostScript and NeWS?

tlack
2pts2
nubisa.com 10y ago

First Node.js Application Is Accepted to Apple’s App Store

tlack
23pts5
news.discovery.com 11y ago

New Tethered Drone Fits in Your Pocket, Flies for Two Hours

tlack
3pts0
github.com 11y ago

Swifter: Write web apps in Swift

tlack
1pts0
lump.co 12y ago

Show HN: Lump.co – instant photo galleries via web search

tlack
1pts3
bitcorati.com 12y ago

Silicon Valley Bank says no to Bitcoin businesses

tlack
29pts23

It seems like everyone is more worried about how something was made rather than what it is or whether or not the work is good on its own merit. Ironic from a group that is surely using AI tools in their own work.

If your application is pricing sensitive, check out DeepInfra.com - they have a variety of models in the pennies-per-mil range. Not quite as fast as Mercury, Groq or Samba Nova though.

(I have no affiliation with this company aside from being a happy customer the last few years)

Vast.ai is a well known provider in that category.

Runpod also has an offering in this space but I think they’re shifting toward more managed-by-them rental services.

If you want someone to take you up on that offer you gotta specify a % differential from cloud list price. :)

Sounds great to me! Just be sure the AI is capable of taking on various personas because not everyone you meet is a believer in nonviolent communication.

[dead] 1 year ago

A tip, Miami guy to Miami guy - the best devs eschew PHP like the plague. The remaining PHPers are desperate work-a-day sorts who will not be bringing the latest hotness to your project. Hire an Elixir or Haskell expert and you're gonna get a much more well-traveled coder.

Kudos on your bold undertaking! I've been a side-lined QNX admirer for some time, though not a potential user in most cases. A good next step would be a series of blog posts where the author takes on common types of enthusiast projects and unpacks how QNX's strengths can be applied in those scenarios.

Do you find you really need that level of “resolution” with memories?

On our [1] chatbots we use one long memories text field per chatbot <-> user relationship.

Each bot response cycle suggests a new memory to add as part of its prompt (along with the message etc)

Then we take that new memory and the existing memories text and feed it to a separate “memory archivist” LLM prompt cycle that’s tasked with adding this new memory and resummarizing the whole thing, yielding a replacement for the stored memories, with this new memory added.

Maybe overly simplistic but easy to manage and pretty inexpensive. The archiving part is async and fast. The LLM seems pretty good sussing out what’s important and what isn’t.

[1] https://Graydient.ai

I have read a lot of reports that the job market is pretty bad.

But, bad or good, I think all you can really do is keep trying! Don't let a few rejections stymie your long term goals. Your family needs you to keep putting one foot in front of the other and applying to more and more places until you find that perfect role.

Maybe use this downtime to build yourself up: open source some stuff that defines you as a subject matter expert, or blog about some of your experiences, etc.

Wouldn't hurt to share your resume here too - lotta industry people lurking. :)

how I wish it had a strength setting..

you can try blending the before and after with PIL but it will probably look even more disturbing

    strength = 0.5
    horrific_image = Image.blend(image_with_normal_skin_and_teeth, 
    kinda_awful_gfpgan_image, strength)
let me know if you find something better

I still like that setup for using trees in low level languages.

But personally I’ve been working at higher levels of the stack the last few years, where these kinds of decisions seem less important.

And on another level, it seems like coders in general aren’t that interested in vector oriented languages and techniques which makes their study somewhat isolating.

I am experimenting with building software using the ReAct tool prompting pattern, using Llama derivative models like Manticore13B, Airoborous, etc. I script it all together using Microsoft Guidance with Llama.cpp and AutoGPTQ. Works pretty well for simple tasks and I know the costs are roughly fixed. Obviously their capabilities are far less than OpenAI's products but when you have tens of thousands of conversations to have the costs of ChatGPT become a distraction. Haven't tried finetuning yet.

Diffusion systems can’t render a great image given just “a dog” as the prompt. Imagine all the different kinds of dog images the user might be expecting.

A good prompt engineer understands the scope of keywords trained into SD and can translate the artistic vision for a finished image into specific keyword constructions.

Try creating a specific visual idea you have in your mind into a jpeg using Diffusion. You’ll see it’s not easy.

Can the user do that? Sure! Just memorize all the critical artists of the last 400 years and their important works. And learn all the specific terminology that yields great results.

Can a computer do it? Sure! Just fill out dozens of form fields to describe your specific intent.

It's good for challenges with lots of tabular data with a consistent shape and relatively simple business logic. You can get data in and out via CSV, HTTP, websockets and more, so it's not too hard to connect up with other systems.

I think it's at least worth learning because of the way it makes you think about coding.

Not quite an SPA, but we migrated our data-heavy site Classic.com from Next.js to Phoenix + LiveView + Surface.

Despite me being the only person with Elixir knowledge on the team at start, it only took our small team ~5 weeks to get a pixel-perfect replica of our most important set of page handlers.

Benefits:

  - 4X reduction in server resources while being faster and more responsive
  - Much more flexibility in how we implement things
  - Feels easier to maintain
  - Much better introspective capabilities (observing the running system)
  - SEO boost from better Google Lighthouse score (from mid-teens to mid-80s)
Challenges:
  - Definitely requires more thought to get certain things right; the component model is more complex (but more capable)
  - Fewer programmers with Elixir knowledge (but I think it's a benefit: never have to interview an idiot)
  - Little bit harder to configure for hosting/cloud but not too bad