(Luc Wey*)

learn, build, repeat

[Mustafa @oprydai]

people often think tensors are just bigger matrices.

they’re not.

a matrix is one kind of tensor, just as a vector is another. tensors are the broader idea. they’re mathematical objects that represent relationships across multiple dimensions while preserving those relationships even when you change your coordinate system. that’s why physicists care much more about how a tensor transforms than how it’s stored in memory. the array of numbers is just one representation. the underlying object is independent of your choice of coordinates.

this is what makes tensors so powerful. the stress inside a bridge, the curvature of spacetime, the electromagnetic field, the inertia of a robot arm, and the activations inside a neural network can all be described using tensors. at first glance these seem like completely unrelated problems. mathematically, they’re variations of the same language. tensors let you describe quantities that have direction, interaction, and structure in a way that remains consistent regardless of your point of view.

the deeper lesson is that mathematics evolves by abstraction. numbers describe single values. vectors describe direction. matrices describe transformations. tensors describe relationships in arbitrarily many dimensions. each step isn’t about making mathematics more complicated. it’s about building a language capable of describing a richer reality. that’s why once you understand tensors, you start seeing the same mathematical structure hiding underneath robotics, computer vision, quantum mechanics, relativity, continuum mechanics, and deep learning.

[(Luc Wey*) @lucwey]

@pipenetwork strange... cant find the crypto-payment button

[LM Studio @lmstudio]

Meet LM Studio Bionic.

The Agent made for Open Models.

https://t.co/VwbbqsdFuI

[(Luc Wey*) @lucwey]

@_CryptoNotes_ @renaissxyz GM bro 🫶

[(Luc Wey*) @lucwey]

@0x0SojalSec Ornith 1.0 ?

[(Luc Wey*) @lucwey]

@openclaw built-in liteRT support?

[(Luc Wey*) @lucwey]

@fhenix Feel safe with the fhenix. decrypt bikini & enjoy a sun.

[(Luc Wey*) @lucwey]

@JackdeS11 What about .litert ?

[Tom Dörr @tom_doerr]

Uses 18 AI personas to deliberate complex decisions

https://t.co/Bn6ykj7Nyl

[Google Gemma @googlegemma]

Gemma 4 E2B goes super fast on Intel AI PCs thanks to LiteRT NPU support on OpenVINO!

⚡1.3x faster prefill performance over GPU
📈2.8x improvement in performance-per-watt
🔋Runs background LLM tasks with zero thermal throttling or heavy battery drain

[(Luc Wey*) @lucwey]

@analogalok How to correctly measure the effectiveness of llm discillation?

[(Luc Wey*) @lucwey]

@TheAhmadOsman speed or vram

[(Luc Wey*) @lucwey]

F*ck, how disappointed iam. only three years old...

@googleaidevs
@IntelAI

[number zero @n0computer]

secure video, anywhere.

https://t.co/xSjJy1Uqrn

[(Luc Wey*) @lucwey]

@petergostev tensors of 32 GB? I doubt it ...

[(Luc Wey*) @lucwey]

@steeve How many tps/dollar for big qwen?

[JFrog Security @JFrogSecurity]

🚨 New PyPI variants found, now with prompt injection to bypass AI scanning:

[email protected]
[email protected]
[email protected]
[email protected]

Our blog will be updated soon with the technical details.

[(Luc Wey*) @lucwey]

@nanobot_project It would be great to have integration

[Walrus 🦭/acc @WalrusProtocol]

Soon, millions of AI agents will be making decisions, moving money, coordinating work, and acting across organizations. That only works if memory holds up across apps and sessions.

Walrus Memory gives AI agents portable, verifiable memory they can carry, share, and trust.

Built for agent coordination at scale. 👇

https://t.co/JX5lJA7aiC

[Peter Naftaliev @peternaft]

We built a simple to use @ffmpeg downloader with all the major ffmpeg binaries, providers, and explanations
https://t.co/vcGVcbjIi8

LMKWYT

[Unsloth AI @UnslothAI]

Gemma 4 12B can now run locally on just 8GB RAM via Dynamic GGUFs.

Google's new model, Gemma 4 12B Unified supports image, audio and 256K context.

You can run and train the model via Unsloth Studio.

GGUF: https://t.co/8cL321pVDh
Guide: https://t.co/odRo9WjRpA