Ahmet Bulut

Head of Computer Science at Acıbadem University pursuit of simplicity.

[Startup Archive @StartupArchive_]

Ben Horowitz: “Do not expect life to be fair. It will only defeat you.”

The Andreessen Horowitz co-founder is asked for advice that he has found useful in his own life. Ben responds:

“The thing that I would say has had the biggest effect on me is something my father said to me years ago: ‘Life isn’t fair.’ That advice seems really simple, but the thing I’ve seen that defeats people more than any other thing in life is the expectation of some fairness.”

He continues:

“There are all kinds of things that are going to happen to you that don’t happen to other people and are completely unfair. But it doesn’t matter because that’s the way it is. And as soon as you can get that idea out of your mind [that life should be fair], you can just deal with it… ‘What should I do now?’ is the real question — not ‘How do I go back and get people to be fair?’… Life’s not fair. That’s the nature of it. If you think about it more than five seconds, you’ll realize that… As an individual, do not expect anything to be fair. It will only defeat you.”

Source: @lennysan (Sep 2025)

[Ahmet Bulut @kral]

you vs. the younger you.

[Aadit Sheth @aaditsh]

Andrej Karpathy shares a 3-step blueprint on how to master anything

[Ahmet Bulut @kral]

Digital text does not exist.

[Nassim Nicholas Taleb @nntaleb]

1/n
A physical book is a real object, anchored. If you read a particular edition, you remember not only the contents but the object itself: its cover, typography, smell, even where a passage sat on the page.
Books organize themselves in memory by place --the ancient method of loci.
Digital text does not exist.

[Ahmet Bulut @kral]

Today = tomorrow;
Need to focus on present to be in future.

[dale @daleverett]

Today, we’re launching pgGraph: an Apache open-source graph traversal engine for Postgres, written in Rust 🦀

When we started Evokoa, we kept running into the same wall every serious agent team eventually hits:
> Agents need to reason across relationships.
> But graph DBs are expensive AF, and suck to use.

So, we built pgGraph around a simple, single idea:

Postgres should stay the source of truth, and the graph engine should live beside it.

pgGraph does something different.
> It keeps the rows in Postgres,
> Compiles the topology around them,
> Creates a virtual graph layer using CSR-style adjacency arrays.

We're making your existing postgres database graph-traversable for agents without any of the usual BS.
> No recursive join hell.
> No ETL pipeline.
> No second source of truth.
> Blazing fast performance

pgGraph is already live in production workflows across RevOps, healthcare, and visa services.

We’re open-sourcing it because graph traversal should become a default primitive in the agent stack, not an enterprise migration project.

Treat Postgres as a graph.
Zero data migration.
This is what Apache AGE should have been.

Docs + Repo below.

[🍂 @Lovandfear]

“The purpose of knowledge is action, not knowledge.”

— Aristotle

[Carnivore Aurelius ©🥩 ☀️🦙 @AlpacaAurelius]

you need to be delusionally optimistic

negative thinking poisons your brain and leads to congitive decline

whereas positive thinking, and gaslighting yourself into thinking everything is amazing, ACTUALLY makes your life amazing too.

you must be a silly goose

[Ahmet Bulut @kral]

As AI systems move closer to real-world reasoning, success may depend less on memorizing language and more on building internal models of how the world actually works.

[Atal @ZabihullahAtal]

🚨 BREAKING: Tsinghua University researchers find that AI reasons more like humans when it can imagine visually instead of thinking only through text.

The study found that multimodal systems perform better when they internally generate visual representations while reasoning.

The paper, "Visual Generation Unlocks Human-Like Reasoning through Multimodal World Models" studies how visual generation changes the way AI solves problems.

It identifies a critical shift:

- Text-only reasoning works well for abstract tasks
- But physical and spatial problems require richer internal representations
- Visual generation helps AI build better “world models”

This creates a major advantage.

Instead of only describing the world with language…

AI can now internally simulate and reason through visual structures more like humans do.

The research shows that combining visual and verbal reasoning significantly improves performance on tasks involving:

- physical understanding
- spatial reasoning
- real-world interactions

This directly highlights one of the biggest limitations in current AI systems:

Language alone is not enough for true world understanding.

The researchers built a new benchmark called VisWorld-Eval to test these capabilities.

Results showed that interleaved visual-verbal reasoning consistently outperformed text-only reasoning on tasks that required deeper world modeling.

This is a major shift from how AI is usually designed today.

Most systems still reason mainly through text.

This work suggests that future AI may need to:
- generate visuals
- simulate environments
- reason across multiple modalities simultaneously

The bigger implication is not just intelligence, it’s perception.

As AI systems move closer to real-world reasoning, success may depend less on memorizing language and more on building internal models of how the world actually works.

This points toward a deeper shift in AI:

From predicting words
to simulating reality

article link below:

[Probability and Statistics @probnstat]

One theorem every ML engineer should know:

The Johnson–Lindenstrauss Lemma.

It states that high-dimensional data can be projected into a much lower-dimensional space while approximately preserving pairwise distances.

Why it matters:

• Explains why random projections work
• Enables scalable learning in high dimensions
• Used in embeddings, compressed learning, and ANN search
• Helps fight the curse of dimensionality

The surprising part:

You can reduce dimensions dramatically without destroying the geometry of the data.

That’s why many ML systems can operate efficiently even with massive feature spaces.

Modern representation learning is deeply connected to this idea:

Good embeddings preserve structure while compressing information.

In ML, compression is often not loss of intelligence —
it’s removal of redundancy.

[Ronit Pereira @CAronitpereira]

“Attack life, it’s going to kill you anyways.”

- Steve McQueen

[Ahmet Bulut @kral]

They have nobody to call when something is wrong. They have nobody who would, on a Tuesday afternoon for no reason, ask how they are actually doing. The interior of their life, the part that needs witnessing, has no audience.

https://t.co/RO4hU9hIFx

[Nassim Nicholas Taleb @nntaleb]

People who are usually private and reserved, even with their friends, end up sharing all manner of personal details on a long flight with a stranger they will never meet again.

[Ahmet Bulut @kral]

A string of helpers from the animal kingdom helped deliver the King's message to Sir David in London.

https://t.co/M9jBBhPVX8

[Nassim Nicholas Taleb @nntaleb]

@Jaffer22915438 The Roman army rule: action removes fear.

[Ahmet Bulut @kral]

As in; AI to replace IO.

[Naval @naval]

AIs replace UIs and APIs.

[Nav Toor @heynavtoor]

In 2016, a man with no CS degree quit his job to study for a Google interview.

He was an English major.
A self-taught web developer.
A former Korean translator in the US military.

He studied 8 to 12 hours a day. For 8 months straight.

Algorithms. Data structures. System design. Operating systems. Networking. Every topic Google asks.

He tracked every minute of it on GitHub. He called the repo "Google Interview University."

Then he applied to Google.

Google never called him back.

Here's the wildest part:

The repo he left behind became one of the most-starred projects on GitHub. Over 343,000 stars. Used by thousands of devs to break into FAANG.

He got hired at Amazon as a Software Engineer.

His name is John Washam. The repo is now called coding-interview-university.

Inside you get:

- A multi-month study plan, week by week
- Every CS topic Google, Amazon, Meta and Microsoft actually ask
- Algorithm patterns with worked examples
- System design from zero to senior
- Big-O, data structures, trees, graphs, recursion, dynamic programming
- Behavioral interview prep
- Mock interview drills
- Book and lecture recommendations he personally used
- Flashcards, video resources, and a coding question practice plan

Self-paced. Free. No course. No paywall. No upsell.

Just one engineer's 8-month study log, open for anyone who wants to follow it.

If you are preparing for a tech interview, this is the most complete free roadmap on the internet.

100% Open Source.

(Link in the comments)

[Ahmet Bulut @kral]

Leave your body alone so it can heal itself.

Nature is natural. Intervention via Modern Medicine is not.

[Kosuke @kosuke_agos]

東京大学の研究により、白髪が単なる老化現象ではなく、損傷した幹細胞のガン化を防ぐための「防衛メカニズム」であるという衝撃的な事実が明らかになりました。

ストレスや睡眠不足によるダメージから身体を守るため、細胞の老化プロセスを自律的に防止する事象です。

その衝撃の全貌と頭皮の最適化を3つのポイントにまとめました。

1. 細胞の『自律的停止』
白髪の正体は、色素を生み出す幹細胞が損傷した際、それがガン化するという構造的な問題を防ぐために細胞分裂を物理的に停止させるメカニズムです。身体がシステムのエラーを検知し、安全装置を自律的に稼働させています。

2. 防衛の『強制稼働』
慢性的なストレス、睡眠不足、栄養不足という摩擦コストが蓄積すると、このプロセスは劇的に加速します。本来の寿命を迎える前に、環境的なダメージによって防衛システムが強制稼働させられている状態です。

3. 環境の『最適化』
これを防ぐには、7〜8時間の深い睡眠によるDNA修復の実行と、銅や亜鉛などの栄養素の補給が必須です。さらに化学物質を排除し、血流を改善することで、頭皮全体を完全に最適化することが可能です。

[Ahmet Bulut @kral]

“ An injury-free year of moderate training beats 4 months of aggressive training interrupted by three months of rehab.
Every single time. ”

Consistency eats Intensity for breakfast.

[Howard Luks MD @hjluks]

Age-related muscle loss (sarcopenia), reduced circulation, and reduced tissue repair capacity all contribute to slower recovery. Unless training… muscle mass continues to decline with age, and deconditioning following injuries or illness can happen quickly.

This creates a cruel paradox: It takes us longer to build fitness, but we lose it just as fast - maybe faster - when we stop. A few weeks off due to injury sets you back months from where you were. Then you’re older than when you started, so rebuilding takes even longer.🤦‍♂️

This is why protecting training time matters more than maximizing training volume.

Consistency»» Intensity.

An injury-free year of moderate training beats 4 months of aggressive training interrupted by three months of rehab. Every single time.

[Ahmet Bulut @kral]

Write, Human ✍️
for God’s sake.

[Athenaeum Book Club @athenaeumbc]

So it turns out that writing is thinking. It's the same process.

"Writing compels us to think — not in the chaotic, non-linear way our minds typically wander, but in a structured, intentional manner."

Outsourcing writing to LLMs is THE SAME THING as outsourcing thinking.

[Ahmet Bulut @kral]

Be on the lookout for your thought patterns, which often lead to self-sabotage. As soon as you observe any one of them, keep in mind to remember to look at the sky. As the Prophet Muhammed (sav) said, there is peace of mind up there.