Ubajihand 🇳🇬

Senior Data Scientist @BluechipTechNG. Craftsman.
Thought. Math. AI. In that order.
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Making GPUs go brrr.

[Ubajihand 🇳🇬 @Ubajaka_CJ]

🤖 AI is powerful, but you are irreplaceable.
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📖 Read it here: https://t.co/aWkLO4C8ku

#BluechipTechnologies #artificialintellegence #LLMs

[Ubajihand 🇳🇬 @Ubajaka_CJ]

Solid take @Sai_Ishaya_ !!!

[Sai Ishaya @Sai_Ishaya_]

Pure maths runs through all the sciences. I don't see any "death" anytime soon.

When electronic calculators emerged in the mid-20th century, people feared human arithmetic skills would atrophy & destroy mathematical thinking. We saw actual protests in the streets.

Instead, they liberated minds from tedious manual arithmetic, letting students focus on deeper algebraic concepts & reasoning. It evolved.

In the 80s & 90s, the same panic happened in applied mathematics with the rise of computing. Suddenly, numerical simulations could do the heavy lifting. Again, the field didn't die; it evolved.

The barrier to entry shifted from computational stamina to system architecture & algorithmic logic.

I don't see the current AI transition any different. Even if OpenAI solves all the millennium maths problems. My biggest worry will be the demotivation, not the death of pure maths. We are moving from a paradigm of "generating the solution steps" to "verifying & guiding the system."

The future of pure math (& most cognitive disciplines) isn't outright extinction; it’s an evolution toward high-level curation, theory framing, & conceptual synthesis.

We have always adapted to elevate our thinking, skills, and roles as technology advances. Even in a cognitive revolution like this, I still believe that will be the case. We have to start teaching students to be master curators and system-level architects of their disciplines, or at least to start thinking like one.

[Jared Duker Lichtman @jdlichtman]

Indeed, it seems that the Caltech undergrads in question are showing remarkable perseverance adapting to this brave new world.

Many senior academics should take note, lest the Planck funeral march become deafening.

It's always important to understand the counterfactual: do you want students empowered to use models at scale, or (as the null-hypothesis) just the labs internally?

I strongly encourage everyone to read their thoughtful response to the letter:
https://t.co/7jxUDPAYy0

[Ubajihand 🇳🇬 @Ubajaka_CJ]

@JordanBelonwu @JordanBelonwu, actively resisting "Attention is all You Need" writings 😄

[Ubajihand 🇳🇬 @Ubajaka_CJ]

Massive congratulations, @dolaoseb, @emeskey and the team!

[Debo Olaosebikan @dolaoseb]

Today, after 7 years in stealth, I, @emeskey and our co-founders are proud to announce @keplercompute.

The world is much better off when we give power & intelligence to the people. When everyone can become their highest selves by pairing their human creativity with the exponentially rising intelligence from our magnificent computers.

Our goal is to unlock the power of frontier intelligence for everyone by pushing memory and logic chip manufacturing to the limits of physics.

To achieve this, we will move the world from one of compute scarcity to abundance where we can make orders of magnitude more chips per dollar and can lower datacenter energies to the limits of physics. We will use physics to ensure we have enough chips and that we can power them on.

Why is compute scarce?
Today's dominant approach - shrinking transistors with EUV - has run into $20B-$40B fabs that take years to build. Sized against that risk, the industry (quite rationally!) grows capex much slower than AI demand that can grow 10x in a year.

In the current system, scarcity is built in.

A different way is possible.

We founded Kepler on the following beliefs:
1. It is possible to build leadership chips without a dependence on EUV
2. It is possible to achieve multiple orders of magnitude more intelligence per watt by evolving chips 2D Silicon to 3D Beyond silicon
3. It is possible to get much closer to the physical limits of computing than we are today while staying within mainstream digital computing

Memory is the biggest binding constraint on AI compute and so we start with a new frontier of AI memory- approaching the bandwidth per watt of SRAM, going up to 10x beyond the capacity of HBM. We use 3D and materials innovations that allow for leapfrogging leading nodes while requiring no EUV lithography and allowing us use fabs that already exist.

Our team co-led one of the industry's first 3D chip-stacking technologies, has led and scaled seven generations of DRAM and multiple logic designs into billions of chips. We built the world's first commercial physical synthesis tool and techniques at the heart of the logic design industry and solved long standing challenges in ferroelectrics, invented beyond CMOS logic devices. We would love to work with you to reinvent chip manufacturing here in America.

We have raised $468m, built our own fab and our AI memories sample this year and ramp to production next year. We are allocated for 2027 and will be scaling in America by 2028.

We are open for business, please get in touch to work together. We are also growing the group of Keplerians and would love to work with you.

Learn More @ Kepler: https://t.co/PiMnFSVXRk
Read our story in @WIRED: https://t.co/wCzmUrWJjd

[Ubajihand 🇳🇬 @Ubajaka_CJ]

On Math Millenium Prize Problems🏆

[Ubajihand 🇳🇬 @Ubajaka_CJ]

@BaboskiB Or you can go the way of Grigori Perelman, no? @BaboskiB

[Ubajihand 🇳🇬 @Ubajaka_CJ]

The G.O.A.T 🐐

[Physics In History @PhysInHistory]

Grigori Perelman ✍️

[Victor Dibia @vykthur]

$22.5 million worth of compute, in a week.
Possibly the new going rate for some (mathematics) scientific breakthroughs (time and cost).
Congrats to all parties (hoping process and credit assignment issues get resolved).
Research and science is decidedly in a different era.

[Ubajihand 🇳🇬 @Ubajaka_CJ]

@vykthur The next monster is the Riemann’s hypothesis @vykthur 🤭😅

[Femi Aluko @LordBinary_]

Four years ago today, we pitched Chowdeck at YC Demo Day.

It’s crazy how quickly time flies and even crazier how much can change in four years.

For one, my hair is longer 😂 😂😂

But more importantly, @chowdeck has grown far beyond what any of us could have imagined back then.

In the video, I was so proud of delivering 800 orders in a day. Today, we do that every 15 minutes.

And yet, it’s still Day One 🚀

[Ubajihand 🇳🇬 @Ubajaka_CJ]

AI has entered the hallowed field of Mathematics and suddenly Mathematicians have become Philosophers 😂
Sha, let them solve the Riemann’s Hypothesis while they are philosophizing

[Ubajihand 🇳🇬 @Ubajaka_CJ]

@justinskycak Math and Coding, which is basically Applied Math. Math trumps!

[Ubajihand 🇳🇬 @Ubajaka_CJ]

@ekomobvng Said a prayer for you. Happy Birthday @ekomobvng

[Mustafa. @oprydai]

Mathematics is the final boss

[Ubajihand 🇳🇬 @Ubajaka_CJ]

@unicodeveloper Oshey!! 🚀

[Sathvik Redrouthu @_sathvikr]

We partnered with @AnthropicAI @OpenAI
to host the world's first math hackathon.

40 hours, $2M compute - solve, understand, and present an open problem.

Applications are live: https://t.co/3oSEmPPohL

[SIAM Activity Group on Dynamical Systems @DynamicsSIAM]

"Reflections on the Millennium Problems" (by Lloyd N. Trefethen): https://t.co/simNwLTLFo

"In this essay I reflect on the status of three of the Millennium Prize problems: the Riemann Hypothesis, P vs. NP, and the solvability of the Navier-Stokes equations."

[Bartosz Naskręcki @nasqret]

I tested GPT-Astra on mathematics. It's a quantum leap. You can talk with the model and prove the statements live in Lean. The feeling is absolutely stunning. You can verify your ideas, compile truth. For a mathematician it feels like finally we arrived in the era where we can focus entirely on the ideation and exploration. Each lemma flows once the logic is set. Before the verification was lagging behind but Astra is very fast and for many tasks the formalization happens as you write your argument in Codex.

If you tell the model to use literate programming + LaTeX you end up with your proof combined with the Lean code, everything explained as you wrote, mixed with small chunks of Lean which are digestible.

I don't want to go back to the era where the only confirmation of the proof was "aha". Now the "aha" is followed by a green tick that indeed tells you that you have captured the essence. Imagine how cool it will be to have all the lemmas of the world combined in one giant database, pointing to people and models who found them. You compose and mix your ideas and build on the shoulders of the giants. But you see much further now and build much faster. And we are just at the beginning of those changes. So much work to do, so much fun!

[Ken Ono @KenOno691]

Congrats to Youness Lamzouri for a beautiful masterpiece! We were fortunate to formalize it in Lean. Math in the future can appear with a machine-checked certificate.