Malhar Jere

Multimodality @Apple

[Malhar Jere @malharjere]

@mojan_jp @reflection_ai Congratulations Mojan!

[Malhar Jere @malharjere]

Our team at Apple is hiring for Summer and/or Fall 2025 interns! Help us push the boundaries of visual generative modeling, stylized and identity preserving image/video generation, image and video editing, avatar generation and much more! Feel free to DM me for more details.

[Awni Hannun @awnihannun]

If you want to really feel the future, take your iPhone out of its case and run a Deep Seek 7B reasoning model on it:

[Varun Chandrasekaran @VarunChandrase3]

Looking to recruit "one" PhD student (in either ECE + CS @ UIUC) with STRONG interests in ML+Systems+Security, or demystifying foundation models. Deadline: Dec 15. Ping with any questions. Please RT and help amplify?

[Apple Hub @theapplehub]

Apple has announced you can now add California driver’s licenses and state IDs to Apple Wallet!

[sophie @netcapgirl]

imagine seeing this and not feeling incredible wonder about the scale of the universe

[MrBeast @MrBeast]

We found 100 stranded/abandoned dogs and spent over $1,000,000 to find them loving homes! This is one of my favorite videos so I hope you consider adopting a dog :)

[Self portraits of an LLM @lost_gautama]

@aidan_mclau @lmsysorg Reminds me of @karpathy’s tweet - the only things he trusts are the LM chatbot arena and the comment section of r/LocalLlama

[Tim Cook @tim_cook]

An incredible use of LiDAR technology and iPhone 14 Pro! 🐶

[Alex Dimakis @AlexGDimakis]

I was surprised by a talk Yejin Choi (an NLP expert) gave yesterday in Berkeley, on some surprising weaknesses of GPT4:
As many humans know, 237*757=179,409
but GPT4 said 179,289.

For the easy problem of multiplying two 3 digit numbers, they measured GPT4 accuracy being only 59% accuracy on 3 digit number multiplication. Only 4% on 4 digit number multiplication and zero on 5x5. Adding scratchpad helped GPT4 but only to 92% accuracy on multiplying two 3 digit numbers.

Even more surprisingly, finetuning GPT3 on 1.8m examples of 3 digit multiplication still only gives 55 percent test accuracy (in distribution).

¯\_(⊙︿⊙)_/¯

So whats going on? Multiplication is algorithmically very challenging (as are less known algorithmic problems).
The authors hypothesize that Transformers have a hard time because they learn linear patterns that they can memorize, maybe compose, but not generally reason with. The paper raises interesting theoretical and practical questions on understanding what Transformers can learn.

The paper
"Faith and Fate: Limits of Transformers on Compositionality" says:
"Our empirical findings suggest that Transformers
solve compositional tasks by reducing multi-step compositional reasoning into
linearized subgraph matching, without necessarily developing systematic problem solving skills"

[Dimitris Papailiopoulos @DimitrisPapail]

Carlini got fed up breaking every adversarial defense that gets published (rightfully so), and is now using GPT4 to automate it.

This is a legit statement paper, with transparency on methods, that should be read as a criticism of the related literature

https://t.co/FtjMNBg5uc

[Maksym Andriushchenko @maksym_andr]

Adversarial examples are back :-)

[Zico Kolter @zicokolter]

@maksym_andr Was literally preparing slides for my talk about it tomorrow, and this was a rough draft for slide 1...

[Arvind Narayanan @random_walker]

Prompt injection keeps getting wilder. Unlike text-based methods, you can't tell by looking at one of these images or audio clips that it's malicious. It can be embedded in a website/email attachment and will alter the model's behavior if it processes it.
https://t.co/NbzgKyZFv6

[Noam Brown @polynoamial]

Not easy, but if we can figure out how to extend this to LLMs the impact would be huge. Imagine having access to models that take 5 minutes to ponder each response but the output is as good as a model that's 1,000x larger and trained for 1,000x longer than GPT-4

[roon @tszzl]

there’s something really fascinating about deep learning based intelligence where it’s clear that their ancestral environment “vaster internet scrapes” doesn’t select for understanding of physics/causality/reasoning as much as it does for human preference

[Jascha Sohl-Dickstein @jaschasd]

The hot mess theory of AI misalignment (+ an experiment!)
https://t.co/OukfipSkIJ

There are two ways an AI could be misaligned. It could monomaniacally pursue the wrong goal (supercoherence), or it could act in ways that don't pursue any consistent goal (hot mess/incoherent).

[Perry E. Metzger @perrymetzger]

Most are unaware of how much of space technology was theoretically anticipated and worked out by a handful of people decades before anyone actually tried to achieve orbit. Tsiolkovsky’s achievements, for example, are astounding and worth reading about.

https://t.co/BnCJwMuPDR

[Eliezer Yudkowsky ⏹️ @ESYudkowsky]

What a year it's been in AI! Where by "year" I mean one week in February.