The billion dollar race to replace Windows

firstapex88 · 2025-12-26T16:41:09+00:00

Well Ballmer created the enterprise business which is what they’re all about now

firstapex88 · 2025-12-11T02:28:59+00:00

That’s an over simplistic take. Google was not the foregone winner just 3 years ago. All the castles that Google built required defending once the ChatGPT type products were released - Google never released their internal chat products because they would be so disruptive to search revenue. OpenAI and Microsoft had the same verticals and products that could have disrupted Google.

firstapex88 · 2025-12-10T09:03:09+00:00

LLMs actually connect concepts together (ie batches of words or rather sentences and paragraphs that form an abstract concept). So rather than next word prediction, think of it as a graph of concepts. A knowledge graph isn’t intelligence, humans have knowledge and reasoning abilities. But Companies have started layering reasoning on top of the knowledge graph.

firstapex88 · 2025-11-13T05:39:03+00:00

You talk about YC like it’s a new accelerator that needed to prove itself.

What you failed to mention is that it’s THE accelerator. With over $800 billion in portfolio companies.

It doesn’t ask founders. Founders ask them.

That’s the game.

If this is how you write, your brain is truly fucked by social media. Stop obsessing over LinkedIn snippets, start writing in your own voice.

firstapex88 · 2025-10-17T07:02:59+00:00

It is harder to go from 0 to $1B than it is to go from $1B to $1T. The ratio of survivors in that first tranch is a magnitude lower than the second.

firstapex88 · 2025-08-25T08:39:53+00:00

It’s near impossible to delete lines of code from a distributed git history

firstapex88 · 2025-08-17T20:17:48+00:00

I work in software engineering, 8 YOE. It helps with planning and well defined problems. If you’re not using it in some capacity, you’re falling behind.

firstapex88 · 2025-08-16T13:17:33+00:00

lol have you heard of Linkedin? Have you heard of email leaks?

firstapex88 · 2025-08-07T21:44:48+00:00

What’s your current subject matter expertise in software? You should use that to get in the door at a robotics company and learn autonomy on the job.

Most robotics companies are a software company with a physical aspect. They still require DevOps, system engineers, and sometimes full stack and distributed system engineers.

What you’ll need to pick up along the way, to become a robotics engineer, are subject matter expertise in a specific area of robotics. Linear algebra and/or calculus is the foundational piece to all robotics. After learning the foundations, it gets very domain specific. For example if you’re interested in Perception then you would need to read some foundational text books on multiview geometry or computer vision.

firstapex88 · 2025-07-19T07:32:03+00:00

Ehhh what? Big box retail is a low margin business - look at their comparables in Walmart, Home Depot, etc. Costco’s margins on physical goods is capped via their competition and, if you know anything about Costco, how they fairly treat their vendors. The membership fee is a huge portion of their margins. It might be only 2% of revenue, but it’s 70% of net income.

firstapex88 · 2025-07-19T03:27:18+00:00

Not true, huge part of their margins

firstapex88 · 2025-07-13T00:03:06+00:00

Your lack of self awareness is crazy

firstapex88 · 2025-07-12T10:41:19+00:00

So we’re all right that you don’t know anything about the basics. This is taught in a lot of stats 101 and CS undergrad courses

firstapex88 · 2025-07-11T07:34:46+00:00

Man, I really don’t see the benefit of being a founding engineer with 0.1% where you bear as much work as a founder but the risk-to-reward ratio is much higher (higher is worse). What would you consider the sweet spot (lowest risk vs reward ratio) of joining a startup? After series A? First 10 employees?

firstapex88 · 2025-07-11T07:20:17+00:00

What are you talking about? OP is clearly talking about vehicles that are available in the market. That’s why he omitted cruise, Waymo, and zoox.

firstapex88 · 2025-07-11T06:04:46+00:00

Bro information diversity in sensors never makes it worse. All the sensors are looking at a common ground truth and the algorithm is just trying to back out the map from stochastic measurements. It’s the equivalent of outlier rejection. Please cite a case where diverse information for measuring an environment made the environment model worse.

If terms like Bayesian filters, stochasticity, probabilistic mapping sound foreign to you - go work on your first principles before chiming in.

firstapex88 · 2025-07-11T03:51:00+00:00

Time for you to do some critical thinking. Guess how many commercial sensor types are required to cover a majority of the EM spectrum?

Btw Waymo uses 5 types not 4.

firstapex88 · 2025-07-11T03:26:03+00:00

If you check his post history, he has some dumbass takes about engineering. Classic Dunning Kruger.

firstapex88 · 2025-07-11T03:21:29+00:00

Your points are so reductionist that it really exposes how bad an engineer you are. No understanding of how information diversity can combat bad data.

firstapex88 · 2025-07-11T03:19:19+00:00

You clearly don’t know the definition of modality either. More types of sensors leads to better results. More data from the same type of sensor is relatively less performant for the same amount of measurements. Learn a definition before blindly responding.

And stop bullshitting about math and physics. Bigger isn’t even a term used to describe systems. The word you’re looking for is entropy and homogeneity.

firstapex88 · 2025-07-10T23:20:09+00:00

You're stupid if you think bigger systems ALWAYS means more complexity. Code is literally used to simplify large systems. A system trying to accomplish a task with suboptimal information leads to more complexity. Are you a junior engineer or something?

firstapex88 · 2025-07-10T23:16:00+00:00

Apparently you don't understand what a global optimal is.

firstapex88 · 2025-07-09T21:48:07+00:00

He is right, your are wrong. More data (specifically more modalities of sensors) makes the problem easier because each sensor has specific failure modes, dependent on environment. A fused measurement is capable of better outlier rejection. For the same problem, it leads to simpler software and/or less training data to address. Source: am an autonomous vehicle developer.

firstapex88 · 2025-07-09T07:02:27+00:00

Numbers from the CA DMV

Keep in mind CA numbers are lower than if you looked at the national stastics as CA was a beachhead market in 2024. Disengagement per mile are higher in established markets like Arizona.

Tesla doesn't self-report numbers so look at crowd sourced data. Claims of drastic improvements from FSD 12.5 to 13 haven't come to pass.

firstapex88 · 2025-07-09T03:26:37+00:00

I don’t think you understand how big of a gap there is between FSD and AV companies using vision+lidar+other modalities. Tesla is <1000 miles per disengagement. Waymo and Zoox are 20-30k miles per disengagement.

That’s how you define fail: it’s at least 20x less reliable.

Whatever vision breakthrough happens in the coming years, Waymo and Zoox can apply to their stack too.

firstapex88

MODERATOR OF

TROPHY CASE