vik
@vikhyatk
Followers
7,371
Following
530
Media
664
Statuses
3,861
teaching computers how to see // prev: @awscloud
Seattle
Joined November 2008
Don't wanna be here?
Send us removal request.
Explore trending content on Musk Viewer
#母の日
• 337969 Tweets
#นาฏราชครั้งที่15
• 309964 Tweets
WIN AT NATARAJA AWARDS
• 119280 Tweets
Feliz Dia
• 117976 Tweets
テンハッピーローズ
• 109104 Tweets
Mães
• 84346 Tweets
#光る君へ
• 71957 Tweets
カーネーション
• 54573 Tweets
MC NUNEW EP1
• 49618 Tweets
Cibeles
• 44500 Tweets
#やまラスト
• 37877 Tweets
新ビジュ
• 35582 Tweets
DONBELLE BOX OFFICE LEGACY
• 31905 Tweets
Ohm X Nataraja Awards
• 17094 Tweets
#光る君ヘ
• 16011 Tweets
GENCelebrate Music With BINI
• 12262 Tweets
清少納言
• 10366 Tweets
Pinned Tweet
this is a real, non-cherry-picked sample from my lnqa visual question answering dataset
4
0
55
wait so car keys don’t use asymmetric cryptography? you can unlock a car by just replaying the RF signals the key emits? my $20 raspberry pi zero has better security than my $20k car?
143
177
4K
> doesn't say please and thank you to ChatGPT
🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩🚩
89
268
2K
Releasing moondream2 - a small, open-source, vision language model designed to run efficiently on edge devices. Clocking in at 1.8B parameters, moondream requires less than 5GB of memory to run in 16 bit precision.
75
210
2K
“you should perhaps consider joining us”
while also having the most dysfunctional recruiting organization i’ve had the misfortune of interacting with
openai is the most talented and nicest group of people i have ever seen in one place
working on the hardest, most interesting, and most important problems
with all the key resources in place
extremely focused on making AGI
you should perhaps considering joining us
2K
1K
23K
15
13
1K
when she realizes your app runs a local vision language model instead of calling the GPT-4V api
16
40
963
Announcing moondream1: a tiny 1.6B parameter vision language model that punches above its weight
31
121
919
work has been interesting lately
got dinged for scheduling an all-hands meeting because the phrase “all-hands” is ableist (not a joke, DM for proof)
then my GPU instance order was rejected because there’s no capacity (my job is training ML models)
50
18
884
the fifth law of thermodynamics states that mark zuckerberg always wins.
15
48
884
friday was my last day at AWS. I had a great 9 years and learned a lot but I’m excited to join the rest of society in complaining about AWS instead of defending it
27
16
842
1,857,482,608 floating point numbers. 3.72 GB. Training this model cost more than my house.
Excited to share it with everyone next week. :)
21
31
819
looking into buying hardware so i can run mixtral locally and cancel my $20/mo ChatGPT subscription. looks like i can expect to break even in 83 years
16
24
752
it's time to build *
* an analytics pipeline for an internal tool that will be deprecated in six months at your dystopian corporate job
9
44
727
ChatGPT refuses to solve CAPTCHA images, but luckily it's super easy to fine-tune moondream to do it. I just released a notebook showing how to do this.
18
50
715
@notmybagman
sorry but i will not be taking any complaints about ChatGPT's cooling water usage while we're still subsidizing cotton farming in the Arizona desert
17
5
591
me explaining to my parents that I quit my sr management faang job to train open source models and shitpost on the internet
6
19
555
there is a company out there that spent $1.4B training a model you’ve never heard of because it was so bad. they had 16 people working on just the tokenizer.
18
21
545
Implemented inference for the Mixtral 8x7B model. Requires ~100GB of VRAM, so you can definitely run it on an 8x3090 or 8x4090 instance.
(GitHub link in thread)
15
29
449
if you are using LoRA: divide the A matrix learning rate by 8 and multiply the B matrix learning rate by 8. you can thank me later
12
44
445
i am going to make a GUI that looks like this to monitor my data processing pipelines
46
12
419
Created a Huggingface Space for moondream1 to make it easier to try out!
33
55
374
Releasing moondream0 today - a small vision language model based on SigLIP, Phi-1.5 and the LLaVa training dataset. This demo shows the model running purely on CPU using ~8GB of RAM.
19
55
372
can someone who is good with money help me balance my budget? i am currently funemployed and need to bring my burn rate down.
Rent ($1,800/mo) - $21,600
8xA100-40GB ($11/hr) - $96,624
Food ($600/mo) - $7,200
Annual Total - $125,424
45
10
362
it is with a heavy heart that i’m announcing shutting down all of my AI projects. will be focusing exclusively on linear algebra and stochastic differential equations going forward.
10
17
354
@realfastman
and now you have to leave your car unlocked so they don’t break the windows, so i guess it still doesn’t matter
5
0
346
mouser has ~1500 of the coral micro dev boards in stock now - comes with a camera, mic, and edge TPU.
i got one for… uh, no reason in particular 😉
20
8
299
Cool paper - shows how to transfer knowledge from a teacher model to a student that is already pre-trained and may even outperform the teacher without loss of performance.
Overcomes shortcomings of traditional distillation techniques that assume the student is untrained.
3
35
300
as a red blooded, freedom loving american i know which model i'm going to use in my apps
12
17
293
ever felt an emptiness in the pit of your stomach? that could only go away if you had a dataset with 1.5M question/answer pairs about images? if so, i'm here to help.
13
15
294
@sergeykarayev
The average politician age charts look pretty correlated except offset by ~10 years.
0
8
267
we just got moondream running with llama.cpp! so quantized/GGUF versions should be out early next week hopefully!
12
23
265
> wake up
> new 2.7B model, nice
> wait it's actually 14B, 2.7B is "activated" but i still need all 14B in VRAM
> benchmarks compare it to a 7B model
> ???
what is the use-case for small/medium scale MoE models? why wouldn't you use a dense model instead? (serious question)
27
7
266
i have developed a new architecture that beats transformers on language modeling. i'm not going to release code, weights, or even a demo. you'll just have to trust me i uploaded a PDF to arxiv
11
8
280
[on first date]
her: so, what are you passionate about?
me: i’m writing a 6,000 word essay on how MoE models are going through a hype cycle. they’re useful when serving at scale but open source research should focus on bringing back ReLU because — wait, where are you going?
10
11
249
I’ve been going through programming subreddits lately (looking for places to shill my AI code review product), and am starting to realize the future is not evenly distributed when it comes to AI-assisted programming.
Huge gap in the willingness to seriously try out new tools.
31
7
243
New moondream release out today! Mainly focused on improved OCR and captioning. If you're using moondream for image captioning definitely worth checking this one out!
14
15
245
pleased to announce that while everything else was going on, i successfully upgraded CUDA drivers from 11.4 to 12.2 today
12
4
241
Some notes on LLaVA-1.6:
1/ To increase image resolution without retraining the vision encoder, they feed in five crops of the image. This improves performance, but comes with additional computational cost due to increased image tokens (from 576 to 2144).
5
18
237
Just released a new revision of moondream2!
✅ Improved benchmark scores and instruction following
✅ Batch inference
✅ Support Flash Attention 2.0 for the text model
11
20
228
Mistral's stated goal for this model (according to their pitch deck) was to beat ChatGPT 3.5 by a large margin.
3
8
214
seeing moondream trending on github is the only thing that brings me out of my seasonal affective disorder fugue. thank you all for the support!
new improved version should be out later today!
10
11
209
moondream finetuning can run on a free colab notebook! try it out and show me your finetunes!
ChatGPT refuses to solve CAPTCHA images, but luckily it's super easy to fine-tune moondream to do it. I just released a notebook showing how to do this.
18
50
715
7
17
204
working on a mamba mixture of experts diffusion qlora 1.58bit model trained using jax, rust, go, triton, dpo, and rag
24
5
204
people who ask how a scrappy startup can win if a big company decides to compete with you understand nothing about startups and big companies, and are fundamentally unserious
6
6
194
I hate the phrase “trivial to build” - it’s always said by someone who builds nothing. Building is hard. Building is expensive. Building is impossible. Anything that’s built is a miracle.
8
19
186
my brain is broken. my first reaction to this was “that’s a nice loss curve”
(in unrelated news, i am now a $GOOG shareholder)
14
3
188
the fact that VCs think it’s clever to ask for your secret sauce in the first call when you know they're invested in a competitor is really the core of the innovation economy
8
6
190
@chinesegon
skeptical that anyone can live off investment returns with just $2M. assuming 8% returns and ignoring inflation that's $160K/yr. doesn't even cover my doordash bill. :(
10
1
177
it’s a good thing i can use moondream to build a fully local AI surveillance system that can notify me if someone tries to steal my car
7
4
179
i believe people are fundamentally good, and that AI tools should simply do what their users request instead of returning condescending responses about what's right or wrong
17
15
179
just to clarify, moondream2 is actually open source. apache 2.0. no weird non-standard licensing terms.
you can do whatever you want with it. it's probably already pre-approved by your company's legal department.
6
12
172
any seattle friends interested in building this drone and seeing if we can get it to fly with just vision input, instead of the usual accelerometer/gyro PID controller?
🥺👉👈
40
7
165
i have not been at peace ever since i dug into some of the examples in the VQAv2 validation set
7
9
162
anthropic: “We believe that companies that train the best 2025/26 models will be too far ahead for anyone to catch up in subsequent cycles.”
also anthropic:
10
7
160
a lot of ai companies today are started because someone wanted to train a big model. building a successful business seems secondary in a lot of cases
8
3
157
digging into the grok tokenizer... looks like it has vocab size 131072 and splits digits into individual tokens
6
8
157
told my friend I was gonna spend the day replicating some arxiv paper and she said "what a rich and fulfilling life you lead"
11
2
154
Why this works: for effective feature learning in neural networks using an Adam optimizer, learning rate needs to be inversely proportional to the width (a.k.a. model dimension) when your width is large.
(screenshot from Tensor Programs V)
if you are using LoRA: divide the A matrix learning rate by 8 and multiply the B matrix learning rate by 8. you can thank me later
12
44
445
3
19
153
@inflectionAI
did the user consent to this investigation? just curious what level of privacy i can expect when using Pi
15
4
149
you’d think this is the exact scenario where one would want a local model instead of calling OpenAI.
who wants their production line to grind to a halt because the factory’s internet connection was flaky?
With OpenAI, Figure 01 can now have full conversations with people
-OpenAI models provide high-level visual and language intelligence
-Figure neural networks deliver fast, low-level, dexterous robot actions
Everything in this video is a neural network:
1K
5K
17K
15
4
148
very little alpha in reading arxiv papers these days because the best insights are kept proprietary. luckily there's still tons of alpha in reading soviet papers from the 1970s
5
5
142
if your model costs $5-10B to train maybe you should consider writing some triton kernels or switching to jax.
4
2
144
/r/LocalLLaMA vibe check (the only benchmark I trust) looking good! ✅
5
5
142
never trust numbers in model names
claims to be 1.3B parameters? may actually have anywhere from 1.4B to 1.9B parameters
claims to take 384x384 images? the correct size is probably actually 378x378
8
6
142
seeing people demo chatgpt wrappers at ai meetups i got rejected from is a bit of a blackpill ngl
10
0
140
We can say right now, with a high degree of scientific certainty, moondream3 is going to be a lot smarter than moondream2 and moondream4 will be a lot smarter than moondream3, we are not near the top of this curve.
14
7
142
Really enjoying working through this book (Principles of Deep Learning Theory).
It’s hard work but the payoff is worth it.
7
10
135
went to an ai meetup today, all the questions were like “what’s the best way to get the gradient from the loss to the weights?” “how do i increase my network’s capacity?”
also saw
@santiagomedr
demo moondream running blazing fast on rust using
@huggingface
’s candle library
6
7
135
i would like to nominate a replacement
Just FYI, computer vision papers submitted to IEEE that include this image of Ms. Forsén will no longer be considered for publication
107
347
2K
3
5
135
dario amodei wants me to delete this tweet because it discloses a compute multiplier, but i will not be silenced 😡
instead i will tell you that scaling by a factor of 4 instead of 8 will likely work even better
if you are using LoRA: divide the A matrix learning rate by 8 and multiply the B matrix learning rate by 8. you can thank me later
12
44
445
6
6
135
fear not the person who has trained 10,000 models once, fear the person who has trained one model 10,000 times
4
8
134
yes, the diffusion model training run is going well. why do you ask?
12
1
145
the open air GPU rig with 5 3090s in my living room is more powerful than the worlds most powerful supercomputer 20 years ago
9
2
128
funny how gpt2 (1.5B parameters) was deemed too dangerous to release and today four years later i shipped a 1.6B param model that’s considered “tiny”
2
4
130
> go to SF because you’re only allowed to work on AI if you’re in SF
> RAG on the billboards
> RAG at every AI meetup
> someone broke into my car and left a flyer for their RAG company
> pay an extra 20% in taxes for the privilege
type of guy who thinks ai is going to change the world but won’t move to san francisco because he heard it’s dirty and dangerous
33
11
265
5
4
127
STOP SCALING YOUR ATTENTION LOGITS BY 1/√D, IT'S BEEN ALMOST TWO YEARS SINCE μP SHOWED US THAT IT SHOULD BE SCALED INSTEAD BY 1/D
5
3
128
Visualizing the expressive power of different MLP activation functions... interesting how SiLU seems to converge faster than GELU.
5
3
127
the xz vulnerability story is wild. they worked on the project for two years before injecting this attack. used sock puppets to pressure the previous maintainer into giving up control.
who has the resources to pull something like this off? what other projects may be compromised?
7
7
125
ceiling is being raised. cursor's copilot helped us write "superhuman code" for a critical feature. We can read this code, but VERY few engineers out there could write it from scratch.
8
5
123
if she doesn’t love you when you’re an lstm she doesn’t deserve you when you become a transformer
6
13
120
i am no longer eligible for the forbes 30 under 30 list, but it’s okay because my mom said she doesn’t want me on that list anyway
23
1
119