chintler

Guideline #1 for comments-

Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes.

The intro is brilliant, the tech and the math is average(you can probably find way better math explanations here on HN). Check out the interview around 22 min mark for something REALLY cool!

No affiliation, I just liked the way they have covered the tech.

I'm not sure about the rebranding of products, but some of the features like the learning path creation and coding challenges definitely look interesting.

If this leads to SO regaining some of its popularity, I'm all for it!

I've bought a bunch of Philips products over the years, and always hated the fact that a simple thing like a charger breaking would lead to throwing away the entire thing- especially grooming products like trimmers. This release of 3D printable models definitely feels like a step in the right direction.

I think being snarky about little things isn't really promoted on HN- it's the first guideline for commenting here. Be kind and try to answer the question if you do have an answer.

$10 Million(M), not $10 Billion(B).

Congrats on the launch!

If I have want to help you in your roadmap- specifically around Find Companies, how can I contribute?

Cognitive Search is nowhere as good as a 'pure' vector DB. Behind the scenes, it's a managed elasticsearch/opensearch with some vector search capabilities. The 'AI' implementations I've done with Cognitive Search always boil down to hybrid(vector+fts) text search.

You can pretty much solve this using modern DL models. There are options depending on how accurate you want your model and how much compute you have.

There is an entire spectrum of models, from something like Mask-RCNN, U-Net family upto something like Meta's SAM, which you can use without even training.

I don't have enough votes to report, but my (organic) classifier reports it as spam.

I'll recommend the Spotlight paper by Google[1]. There are very interesting datasets they created for this purpose. They mention they have a screen-action-screen dataset that is in-house and it doesn't look like they'll open it. Maybe owning Android has its advantages.

There's a recent paper by Huggingface called IDEFICS[2] that claims to be an open source implementation of Flamingo(an older paper about few-shot multi-modal task understanding) and I think this space will be heating up soon.

[1] https://research.google/pubs/pub52171/

[2] https://huggingface.co/blog/idefics

[2020]

Assuming best intentions, it might be helpful to clarify why this was posted.

The YouTuber CGPGrey did this back in 2021 on Dragon's tail, a winding road in the mountains that's claimed to be the deadliest road in America[1]

[1] https://youtube.com/watch?v=d6tgmGqXysM

Based on the constraints and some of the comments, a different avenue would be to reduce your upfront ask.

Try and assess if you really need all the full-time employees you mention. You can get very far with part-time employees, freelancers and outsourced development till the point where you have an MVP built for which investors can put up money. If you really need FTEs, you can (partially)pay them in ESOPs of the company against future revenue.

This is somewhat possible. I've created a way to chat to our company's material publicly. We used a lot of prompt engineering and custom guardrails to achieve this. However, it severely limited the length of the conversation that a user can have.

I've modernized a lot of legacy pipelines and can help you if you want.

I'd like to recommend ekatra.one, a GPT-powered education platform designed for under-served learners, especially in India. Helps with personalized learning experiences and uses WhatsApp for course delivery.

The company I work for is in this space, let me know if you're interested in connecting.

I might have a solution for this. Can I drop you a note?

This is a fantastic resource for someone who's just getting interested in Photogrammetry, via Neural Radiance Fields(NeRF). I'm curious if those should be included here.

As an aside, perhaps this repo should be renamed to start with `awesome`, since it helps with SEO for github.

This[0] was posted a few days ago here.

[0] https://devblogs.microsoft.com/engineering-at-microsoft/micr...

Paging @dang, this is definitely spam.

I have been in the same position, and here's what my experience has been(sample size 1)

Standardize the stack. Use one stack, one set of tooling, one set of practices, and libraries that are very well known and has decent community support. As you start delivering code, the knowledge builds upon itself.

For example, I pretty much standardized REST API, microservices, Python, Flask, Redis, MongoDB, Nginx for the first 2-3 years. As teammates joined in, they were encouraged to reuse code. Slowly, as more senior engineers started working in the team, they brought their own processes, and consequently the organization became more flexible and robust.

I took a trip last month(within India) with about ₹600 cash and returned with ₹560, with UPI for everything from chai to flight tickets. It's just so frictionless.

UPI was built around mobile phones, and a significant part of the trust comes from the KYC that was enforced from the beginning for mobile connections. I'm not sure how well that process will scale across countries and across currencies. Still, with the international partnerships coming up, I'm excited for the possibilities that are presenting in the payments space.

Thank you for writing and making your books available. I just wish there was some way I could buy them with UPI.

I have a few counterpoints against your first sentence:

0. Tourism isn't a cure for ignorance, but it helps in widening worldview and experiencing how other people live and see. However, today it is mostly about having some time away from your residence/work.

1. Tourists are a small though non-negligible part of humanity as a whole

2. A large part of the people who have traveled as tourists have traveled to tourist spots, places that are developed to cater to the _tourists_ and hence aren't an authentic representation of the local population.

I do agree with your second sentence.

I agree to this, and I think lambdalabs is quite precisely positioned for on-prem training.

As an aside, thank you for your one-line installer script for tf/keras. Earlier, my team used to spend days figuring out the CUDA/tf/keras/CUDNN etc dependency charts, and you've brought that down to ~0.