lazarus01

I was thinking about this yesterday, while going through some slop documentation generated by deepseek. If you compare claude fable 5, side by side with the deepseek, the differences in prose are glaring. It's not even close. Deepseek prose reads like fragmented shorthand, where claude fable 5 comes fairly close to human, certainly not superior to human quality writing.

I watched a podcast with a cognitive scientist and one of main contributors to the theory of linguistic relativity, Lera Boroditsky.

She said something to the effect that, "in this very moment, we are speaking in ways that were never spoken before. We are saying things that no other person has said before...."

Language models are not sample efficient and cannot adapt to evolving language, unless it's documented in large amounts of examples.

So whatever isn't documented, whatever isn't in the training dataset or the rag corpus, the model will always be incredibly different in expression from humans.

with nvidia's dominance as the operating system of AI it further concentrates it's dominance in developer ecosystems, keeping costs high and creating risk as a single point of failure, as there is only one company in the world manufacturing nvidia chips in Taiwan (TSMC), making Taiwan the most important country to the ai industry

nvidia will become the next cisco - this can't last forever

In 2000, Cisco Systems became the world's most valuable company by selling the routers required to build the internet. However, telecom companies bought hardware much faster than consumers adopted internet services. When the monetization gap widened, hardware orders were canceled, Cisco's stock crashed by 80%, and the broader economy fell into a recession. If consumer demand for AI software does not soon match the trillions being spent on Nvidia's chips, a sudden cancellation of orders could wipe out massive amounts of stock market wealth tied to index funds

I’m using deepseek v4 flash to build a complex full stack production ai app and it’s a total beast.

I break out Claude when I hit some serious roadblocks, but that doesn’t seem to be happening much after the last deepseek flash release.

Deepseek prices just went up, but are still low.

I will def try GLM on my next project

Agreed. That book is the bible in applying innovation diffusion theory to your marketing and product strategy.

I use to be in sales before I became an MLE.

There is a theory called diffusion of innovation. The simple explanation is that there are 5 different cohorts of buyers. Early adopters, visionaries, pragmatists, conservatives and laggards. Early adopters and visionaries are risk takers, who will make bold moves to achieve order of magnitude results. This is called the early market, which represents 13% of the market. The pragmatists and conservatives make up the mainstream market which is about 70%.

In order to get into the mainstream market, you need solid adoption from the early market.

To choose a niche, you need to develop a solution that fits nicely into the buyers expectations for different types of market participants. There is the market alternative and product alternative. The market alternative is the solution that owns the highest proportion of market share. The product alternative is innovative tech that challenges superiority to the market alternative.

You need to introduce a solution that fits in between those participants to stand out.

To choose a solution, go to industry trade events and talk to people about high value problems that aren’t solved by current participants. That is the purpose of industry associations, to solve difficult problems.

Visionaries and early adopters love new vendors. They will champion you through their organization if your solution will help them meet their goals.

Good luck

I’m not a big poster at all, but ran into this precise issue.

They analyze the video posts on instagram. If they detect the video has even a small amount of commercial value, they classify it as branded content and you need to pay for it to get promoted.

I am taking a course through a website called neetcode.io

It is a clone of leetcode, designed to help you build intuition in a programmatic way, to learn the top 75 - 150 coding questions, common in interviews.

Each lesson comes with detailed video explanation, with practice problems. The practice problems too come with video solutions.

If you go to the main site, you will see a link to the different courses they offer and also a roadmap. The roadmap organizes the algorithms in a hierarchy, from simple complex, to help you reduce your blindspots, as you build your intuition.

I'm nearly complete with the beginner course and will move to advanced soon. For me personally, it works quite well, because I need a human to explain things to me in detail in order to understand the complexity.

Hope this helps

< I enjoy writing code. Let me get that out of the way first.

< I haven’t written a boilerplate handler by hand in months. I haven’t manually scaffolded a CLI in I don’t know how long. I don’t miss any of it.

Sounds like the author is confused or trying too hard to please the audience. I feel software engineering has higher expectation to move faster now, which makes it more difficult as a discipline.

I personally code data structures and algorithms for 1 - 2 hrs a day, because I enjoy it. I find it also helps keeps me sharp and prevents me from building too much cognitive debt with AI generated code.

I find most AI generated code is over engineered and needs a thorough review before being deployed into production. I feel you still have to do some of it yourself to maintain an edge. Or at least I do at my skill level.

Great article. I def experienced this new form of burnout. I’ve gotten use to working with AI systems to produce code, mainly the velocity of code production. It took me four months to develop an intuition of how to maintain a healthy pace and when to rest. I still feel that the pace is very fast, but my ability to consume code and update my mental model has improved. I try my best not to push past a certain point. I feel once the cognitive load is at capacity, you’re going to reduce quality in your outputs. So I’ve given myself a set threshold that I won’t cross. If things are slower, so be it. It’s not worth the added stress to have completed functioning code, with outsize cognitive debt.

Im fortunate to live in an area dense with traditional taxis and Ubers, no Waymo yet.

I rarely take taxis, the exception is when I have to haul my gear to the studio for a jam session. I always take a taxi, because it’s cheaper and faster than using an app to call an uber.

On 80% of the trips, I end up having a nice chat with the driver and learn something new about humanity or myself.

I really enjoy these interactions, but I feel for the drivers, it’s a very tough job where most taxi drivers have to scramble to find places to urinate or do so in an empty bottle between their legs. There is not much dignity in the job. I feel a negligible segment enjoy it as a reliable career.

I wonder what will happen to the drivers if a large representation of the 1 million+ daily trips are displaced by automation?

You completely missed the crux of the story.

I'm speaking specifically to the example given by the author.

He was approached by an engineer that saw a critical flaw in the software that goes beyond simple "backlog prioritization".

The engineer "quietly" escalated his concerns by showing a thoughtful approach to fixing a global problem that goes beyond his assignment, that if left unsolved can cause problems for everyone.

Given the managers experience, he understood the engineers intrinsic motivation to do good (not biased in self promotion) and believed that the idea would speak for itself and gain the confidence of other engineers, which it did.

This approach is antithetical to what you described. The engineer did not advocate for himself or his idea, he identified a bigger problem that was far more important than his assignment. He brought the idea to leadership out of concern, to deal with conflicting priorities above him. He was not caught up in politics or transactional thinking.

The message the author is trying to convey, people with significant talent that have higher order values, are not concerned with labels such as "wanting to be a 10x engineer". They just focus on what they believe are the most important problems that they can solve that benefits everyone, not just themselves.

These people are truly rare and your argument that playing politics is necessary to promote ideas, proves how rare it is to come across these people.

I don't see things the way you do.

You look at gaining recognition for good ideas as a zero sum game that requires self promotion.

If you develop a good original idea that solves a problem and it gets implemented, you have created positive impact without self promotion. If you're not concerned with public perception, then the discussion stops right here.

Someone can take credit for your idea to gain perception that it was their original idea. But in the end, someone who self promotes that can't come up with original ideas will eventually lose their believability factor and will be unable to promote themselves much further.

> Good work speaks for itself.

I really enjoyed reading this story. I personally believe in subscribing to self concordant goals and working altruistically to cultivate the good Society.

I also agree with the statement above. But what the author leaves out is that good work that speaks for itself can also create insecurity for those that are in an intense competition for recognition.

People’s reality is entirely subjective, where even well intentioned people may reject ideas that don’t contribute to their interpretation of reality.

In my personal experience, when I came up with and executed ideas that made substantial impact and outperformed others, I wasn’t given proper recognition, mostly due to others insecurity and politics to support a subjective reality that everyone can agree to. Particularly leadership who were non-technical sycophants that cared more to please their master than to do the right thing for the company or even themselves.

Humans are complicated social creatures where ethics and altruism often lose to filling personal voids.

I do believe in the concept of the wolf, someone who has reached self transcendence that doesn’t need to subscribe to a subjective shared reality and can achieve personal satisfaction through mastery by exercising their will to do something they believe is intrinsically meaningful.

> Quality of the content doesn't matter at all

Exactly.

Engagement is prioritized over quality on most mediums. I find user generated content on social media absolutely abhorrent.

Thank goodness for hacker news. I can read something, share my views and in some cases, my views may be based on some weak intuition and I learn from polite correctness.

I was wondering what preclinical models meant. It would be more accurate to call it animal models. I read roughly 3% - 5% of compounds move from preclinical cancer therapies to fda approval. That’s a tough success rate.