yoyaqim

Brain, Machine, Math and Truth.

[Benedict Quartey @Benedict_Q]

Officially a Doctor! 🎓🤖

Yesterday I defended my PhD on Scaling Trusted Autonomy: exploring how we can build generally capable robots whose decisions remain verifiable, interpretable, and worthy of our trust.

I’ll share more over the coming weeks.

For now … I’ll just be watching the sun rise on a slightly more grateful universe. 😄

[Y Combinator @ycombinator]

In 2001, @JeffDean and Sanjay Ghemawat did the math and realized Google’s entire search index would fit in RAM — then shipped it in a few days, and search got fast.

In 2013, another napkin calculation showed that three minutes of daily speech recognition per user would require doubling Google’s server fleet. That one became the TPU.

At Startup School 2026, Google’s Chief Scientist talks with YC’s @sdianahu through the thought experiments behind both, why inference hardware is the next specialization, and where two or three people in a room can still win.

00:07 — Are AI Models Already Junior Engineers?
01:44 — AI Systems That Improve Themselves
02:40 — The Google Search Breakthrough That Changed Everything
04:38 — AI Agents Will Run for Weeks
05:58 — The Napkin Math That Led to TPUs
09:20 — How to Find Breakthrough Ideas
10:25 — The AI Engineer's New Mental Model
12:33 — Why AI Is Really an Energy Problem
16:11 — Context Engineering Is the Next Frontier
19:46 — The Skill That Made AI Better at Optimization
22:13 — Why Long-Running Agents Fail
25:21 — Where Startups Can Still Beat Google
31:19 — How to Become an AI-Native Founder
36:36 — Question Your Biggest Assumptions
42:08 — AI That Builds Better AI
50:02 — Build Something That Truly Matters

[yoyaqim @cor_quaerit]

@Benedict_Q All the best👍👍

[Paul Azunre @pazunre]

Yesterday, Ghana's finance minister @Cassielforson presented 2026 mid-year budget review

To increase accessibility of this information to people who may not speak English, I created an explainer of his report in Twi & Ewe - using @KhayaAI @claudeai Skills.

Took me <20 mins!

[AY🪵 @Agonizo_mai]

Resist the temptation to reduce people to their usefulness. Their worth lies not in what they can offer you, but in their inherent dignity as bearers of the image of God.

[yoyaqim @cor_quaerit]

@CalebisGaven 🤣😭

[yoyaqim @cor_quaerit]

@owusu_oo Ikr🤣😭

[John Hewitt @johnhewtt]

I’m at ICML! I’m hiring PhD students for my lab at Columbia. DM me here on twitter to set up a time to chat.

https://t.co/jcUlyBiX1o

[yoyaqim @cor_quaerit]

Interesting stuff to see!

[Martin Schmid @Lifrordi]

We are looking for more amazing researchers and engineers to join our team. EquiLibre Technologies is a frontier AI trading research lab. We train our own foundational models, use our own RL algorithms, and trade our own money.

The proof is in the pudding. [THREAD]

https://t.co/sRHFJQfle6

https://t.co/zqi7GOXNdd

[Simon Prince @SimonPrinceAI]

I'm updating and improving chapters from Understanding Deep Learning and posting them to https://t.co/8zGsFiXjXd.

The latest unit describes a framework for loss functions from which least squares, binary cross-entropy, and multiclass cross-entropy losses can be derived.

[AY🪵 @Agonizo_mai]

2 fully funded RA offers
Alfred W. Moltke Memorial Fellowship recipient
Member, Xi Sigma Pi
4 publications ( 1st authored 3)

Graduated from the #1 Forestry program in the U.S. and #2 in the world, while mourning the loss of my Asare, whose spirit continues to inspire me❤️

[Robert @RobertBoatengD1]

Honestly, this is a sign that we need more engineers and technical people in politics.

[Dwarkesh Patel @dwarkesh_sp]

New blackboard lecture w @reinerpope

How do chips actually work – starting with basic logic gates, and working up to why GPUs, TPUs, FPGAs, and the human brain each look the way they do.

0:00:00 – Building a multiply-accumulate from logic gates
0:16:20 – Muxes and the cost of data movement
0:25:59 – How systolic arrays work
0:39:00 – Clock cycles and pipeline registers
0:51:40 – FPGAs vs ASICs
1:03:14 – Cache vs scratchpad
1:07:16 – Why CPU cores are much bigger than GPU cores
1:11:49 – Brains vs chips
1:15:22 – A GPU is just a bunch of tiny TPUs

Look up Dwarkesh Podcast on YouTube/Spotify/etc to watch. Enjoy!

[Arsenal @Arsenal]

We did it, together.

[Arsenal @Arsenal]

This belongs to all of us.

[Dmitrii Kovanikov @ChShersh]

For my non-tech friends, this is like Ronaldo joining Manchester City

[Dwarkesh Patel @dwarkesh_sp]

Continual learning sometimes gets discussed as if the goal is to dissolve the context/weights distinction. Let the model just keep accumulating, fine-tuning itself on the fly.

@karpathy points out, though, that this isn't how humans do it.

Our working memory gets wiped regularly. What we actually have is a consolidation process (sleep) that distills stuff into the brain, in a weird and lossy way.

This is very different from how people sometimes talk about continual learning. It's not obvious it's something you can get for free from doing long enough RL loops.

[Steven Brunton @eigensteve]

I Wrote a New Book!!!

Optimization: A Bootcamp for Machine Learning, Inverse Problems, and Control

Pre-Order Now (July 31)
https://t.co/EoDMFapUUf

Coming Soon:

* Free PDF on website
* YouTube Videos for entire book
* Python code on GitHub

[Mathilde Papillon🦋 mathildepapillon .bsky .social @mathildepapillo]

🏆 The 2026 Topological Deep Learning Challenge is officially live, now in its 4th edition! 🏆
This year’s theme is “Bridging the Gap” between the GNN and TDL worlds.

Win incredible prizes including up to $1000 in cash 💸 and AI research internships!

Submission deadline: Aug. 1

[yoyaqim @cor_quaerit]

I love casios😍😍

[Sci-Fi Archives @SciFiArchives]

Casio A158 “RoadRunner” by EONwatches