loondri

Have mentioned the source at the top right header. Its by Crustdata.

Let me check and fix. Also if possible, mind sharing for which company its marked as S19 vs S24?

PG's tweet that inspired this https://x.com/paulg/status/1994904099566031300

This is much needed! Gonna try this out. I haven't seen a good tool that lets me generate code via CLI.

You can read the full research (with some cool pictures & graphs) https://goldenpineapple.substack.com/p/the-usas-next-unicorn...

I have been tracking all of the YC companies since their inception. Today, I'm analyzing all 245 companies that have gone through the W24 batch and are presenting some of the most interesting metrics. Since all of these companies are pretty early stage and lean, I focused on the 3-4 most important areas that make sense at an early stage. 1. Monthly Traffic 2. Focus areas 3. Founder’s Previous Companies & 4. Founder’s Educational Background.

Very interesting. Does this cover all the companies founded by Tesla alumni?

I would say with work from home and AI helping you build stuff quickly, bootstrapping is a great way to validate the market needs and reach to 10k MRR

I did the same with my bootstrapped data intelligence startup

Link to the full analysis https://goldenpineapple.substack.com/p/finding-the-next-klav...

I get that everyone has their own coding style, but ditching established conventions in C for personal aesthetic seems a bit much. Like, using u8 or i32 instead of the standard uint8_t or int32_t might save a few keystrokes, but it could confuse anyone else looking at the code. And the custom string type over null-terminated strings? C's built around those, and deviating from that just feels like making life harder for anyone else who might need to work with your code.

And manually writing out Win32 API prototypes instead of including windows.h might shave off some compile time, but it's like ignoring a well-maintained highway to trek through the woods. Just seems like a lot of these changes are about personal preference rather than sticking to what makes C code easy for everyone to work with.

Blackmagic Camera app might add fancy controls to the iPhone, but it can't match the quality of real professional cameras.

This article talks about making Linux pipes faster, but other methods like shared memory or message queues might still be quicker. For example, in systems that need to move a lot of data quickly, the extra steps with pipes could slow things down. Also, when many threads are sharing data, pipes might cause more problems than other methods. So, the improvements in the article might not help much in real-world situations where speed is crucial.

Interesting, thanks for sharing this

This was a sarcasm btw

This article praises AI for improving products, but what about the jobs it might take over, like customer service roles?

And can AI truly understand human emotions to handle sensitive customer issues or create artwork that resonates with people on a deeper level? There might be more to consider than just the cool tech.

It's interesting that Pythagoras gets credit for a theorem he may not have discovered, especially when there's proof that Babylonians knew it 1000 years earlier.

This challenges the idea that ancient Greek mathematicians were always ahead of others.

I think the way the Celestial Reference Frame Department does things might be old-fashioned.

With new tech like blockchain for decentralized coordination, or machine learning algorithms that can process astronomical data more accurately and quickly, there might be better and easier ways to do celestial referencing. It might be time for a change to keep up with these new advancements.

I think Vespa's growth and innovation were driven by Yahoo's resources and infrastructure. Now as a separate entity, it might struggle to maintain the same pace of development and innovation without the backing of a tech giant like Yahoo.

I think retrofitting IPv4-only apps for IPv6 compatibility might be a short-term fix. It could be more forward-thinking to focus on developing new apps with inherent IPv6 support to prevent accruing technical debt and facing complications tied to maintaining outdated IPv4-only applications.

The trade-off between memory usage and inference time uncovers a potential flaw in prioritizing resource efficiency over performance.

This would deter real-time or near real-time applications where latency is a critical factor.

Also, the confusion over the phrase "0.5-2x slower" highlights a possible lack of clarity in communication within the community, which would hinder the accurate assessment and adoption of such optimizations in practice.

The NIST standardization process, appears to have a grey area particularly around the selection of constants.

The skepticism around standardization, advocating instead for direct adoption from cryptographers, sheds light on potential shortcomings in the current system.

There is definitely a need for a more transparent or open scrutiny in algorithm standardization to ensure security objectives are met.

FTC's narrow market definition unjustly targets Amazon, ignoring broader retail competition that could dilute its alleged monopolistic status.

I think the move towards vector databases might be more hype than necessity. Traditional databases, when properly optimized, can handle vector data for many use cases. The push for specialized vector databases could be re-evaluated in terms of efficiency and cost-effectiveness compared to optimizing existing scalar databases.

Link to the article https://goldenpineapple.substack.com/p/chips-act-impact-50-o...

It's intriguing how the DOJ is suddenly so focused on Google's practices when there are other tech giants with equally questionable strategies. Makes one wonder about the real motivations behind this trial.

Interesting to see that total grocery sales jumped by more than 10% in 2020 (probably due to COVID?). Did people just start buying more grocery? Or is this because of inflation and the dip in dollar value was not accounted for ?

Try "Building wealth tech products in the UK who raised more than 1 million"

1. Uberduck: uberduck.ai - 2.7M

2. 點單 Dimorder: dimorder.com - 550K

3. Dealls – Jobs & Mentoring: dealls.com - 500K

4. Andi: andisearch.com - 490K

5. Grey: grey.co - 485K

6. Winno: winno.app - 375K

7. Take App: take.app - 260K

8. Unlayer: unlayer.com - 240K

9. Blaze Ai: withblaze.app - 235K

10. Tradex: tradexapp.co - 230K

Here are the top 10 YC-W23 companies by web traffic

PlayHT: https://play.ht

Resend: https://resend.com

Vendah: https://vendah.com.br

Glass Health: https://glass.health

Unify: https://unify.ai

RiVet: https://rivet.gg

Vocode: https://vocode.dev

Stack AI: https://stack-ai.com

CreatorML: https://creatorml.com

Recent data challenges Vinod Khosla's claim that working at McKinsey might be a waste of time.

In fact, McKinsey alumni are leading in venture-backed business creation, especially in the Healthcare sector, even outpacing tech giants like Google and Microsoft in other sectors.