bilbo

deactivated mathmatician

[Degen CPA @DrewVento]

They really think this is what’s happening

[Almost Sure @Almost_Sure]

@littmath I don’t think there’s a ceiling. There’s too much maths in the world for one person to know most of it, but if you can handle university level maths then I see no reason to stop at any imaginary ceiling, if it’s an area you want to spend time on

[Daniel Litt @littmath]

One thing I find obnoxious about “hitting a ceiling in math” discourse is that it’s mostly based on people’s self-reports of having found some topic too hard. But my experience teaching math is that people are often wrong when they make such claims!

[bilbo @bilboVal]

@IlPetrolier3 assurdo google moduli per un esame

[bilbo @bilboVal]

@Cr1st14nM3s14n0 È buono per scrivere in LaTeX a partire da immagini, sia scritte a mano che non?

[Maurizio Scaltriti @ScaltritiLab]

Il primo genoma umano fu sequenziato completamente nel 2003. Ci misero 13 anni e spesero 2.7 miliardi di dollari.
Pochi giorni fa sono riusciti a sequenziarlo (molto meglio) in 4 ore, spendendo meno di 1000 dollari.
Questo è il progresso che viviamo oggi nel mio campo.

[Rhyush @Resorcinolworks]

I still think about this.

[bilbo @bilboVal]

@rpwpetal il momento k-esimo 🥹

[bilbo @bilboVal]

@mark_k @Angl14183945 the ide is 2.0 too tho

[bilbo @bilboVal]

@Techjunkie_Aman 67

[Nintendo Nostalgia @Nin10Nostalgia]

Mario Kart DS (2005)

#MarioKartDS

[Valeriy M., PhD, MBA, CQF @predict_addict]

Solid mathematical ideas almost always outperform contrived engineering tricks.

For years deep learning has been dominated by increasingly complex architectural hacks: CNN blocks, attention layers, channel mixers, residual pathways, normalization stacks.

Every few years a new architecture is announced as if it were a revolution.

One of the most famous examples was Kaiming He and Residual Networks (ResNet). At the time he was paraded around the AI world like a celebrity because residual connections supposedly “solved” deep learning.

But these were largely engineering patches.

Now something much more interesting appeared.

A new architecture called CliffordNet returns to mathematics — specifically Clifford Algebra, developed in the 19th century by William Kingdon Clifford.

Instead of stacking arbitrary modules, the model is built around the geometric product

uv = u·v + u∧v

A single algebraic operation that simultaneously captures inner product structure and geometric interactions.

In other words: the math already contains the interaction mechanism.

No attention blocks.
No mixer layers.
No architectural spaghetti.

The result:

• 77.82% accuracy on CIFAR-100 with only 1.4M parameters
• roughly 8× fewer parameters than ResNet-18

And with strict O(N) complexity.

The paper even suggests that once geometric interactions are modeled correctly, feed-forward networks become largely redundant.

A good reminder for the AI community.

Engineering tricks can dominate for years.

But eventually mathematics shows up and deletes half the architecture.

Paper:
[https://t.co/QIkCCO1tYs)

19th century geometry just walked into computer vision.

[bilbo @bilboVal]

@diquaed_ila @odrenaele

[bilbo @bilboVal]

@Sylency01 @Mixwell @OBSBOT_Official ola gringo silency

[bilbo @bilboVal]

@aimstarsHQ @odrenaele @Sylency01

[bilbo @bilboVal]

@the1truebagel @fyridk @Sylency01 @odrenaele It's a n for me, I write the m like this

[bilbo @bilboVal]

@the1truebagel @fyridk @Sylency01 @odrenaele I always write in cursive /italics

[bilbo @bilboVal]

@HamidGoog @SageTheGriffon @fyridk @Sylency01 @odrenaele Big question , I cannot answer

[bilbo @bilboVal]

@Sylency01 @fyridk @odrenaele pendejo Im panick

[bilbo @bilboVal]

@IOSSvl @fyridk @Sylency01 @odrenaele No I won't