#neural network image

[aylen-san]

Wonders of Valinor

Tonight, the stars shine with a special clarity.

It is the echo of the ancient Trees of Valinor,

their light reflected through the depths of time.

I remember how Laurelin poured golden light,

and how Telperion sang in silver silence,

and the whole world paused to listen.

Though those days may never return,

in every heart where kindness and courage dwell,

Valinor still shines.

May your dreams be as gentle

as the breath of the western wind,

and your morning as bright

as the song I will sing again.

[aiweirdness]

AI versus a giraffe with no spots

On July 31, 2023, a giraffe with no spots was born at Brights Zoo in Tennessee.

Image recognition algorithms are trained on a variety of images from around the internet, and/or on a few standard image datasets. But there likely haven't been any spotless giraffes in their training data, since the last one to be born was probably in 1972 in Tokyo. How do they do when faced with photos of the spotless giraffe?

Here's Multi-Modal In-Context Learning:

And InstructBLIP, which was more eloquent but also added lots of spurious detail.

More examples at AiWeirdness.com

Are these crummy image recognition models? Not unusually so. As far as I can tell with a brief poke around, MMICL and InstructBLIP are modern models (as of Aug 2023), fairly high up on the leaderboards of models answering questions about images. Their demonstration pages (and InstructBLIP's paper) are full of examples of the models providing complete and sensible-looking answers about images.

Then why are they so bad at Giraffe With No Spots?

I can think of three main factors here:

AI does best on images it's seen before. We know AI is good at memorizing stuff; it might even be that some of the images in the examples and benchmarks are in the training datasets these algorithms used. Giraffe With No Spots may be especially difficult not only because the giraffe is unusual, but because it's new to the internet.

AI tends to sand away the unusual. It's trained to answer with the most likely answer to your question, which is not necessarily the most correct answer.

The papers and demonstration sites are showcasing their best work. Whereas I am zeroing in on their worst work, because it's entertaining and because it's a cautionary tale about putting too much faith in AI image recognition.

[ai-innova7ions]

Neturbiz Enterprises - AI Innov7ions

Our mission is to provide details about AI-powered platforms across different technologies, each of which offer unique set of features. The AI industry encompasses a broad range of technologies designed to simulate human intelligence. These include machine learning, natural language processing, robotics, computer vision, and more. Companies and research institutions are continuously advancing AI capabilities, from creating sophisticated algorithms to developing powerful hardware. The AI industry, characterized by the development and deployment of artificial intelligence technologies, has a profound impact on our daily lives, reshaping various aspects of how we live, work, and interact.

[dzamie]

Detecting AI-generated research papers through "tortured phrases"

So, a recent paper found and discusses a new way to figure out if a "research paper" is, in fact, phony AI-generated nonsense. How, you may ask? The same way teachers and professors detect if you just copied your paper from online and threw a thesaurus at it!

It looks for “tortured phrases”; that is, phrases which resemble standard field-specific jargon, but seemingly mangled by a thesaurus. Here's some examples (transcript below the cut):

profound neural organization - deep neural network

(fake | counterfeit) neural organization - artificial neural network

versatile organization - mobile network

organization (ambush | assault) - network attack

organization association - network connection

(enormous | huge | immense | colossal) information - big data

information (stockroom | distribution center) - data warehouse

(counterfeit | human-made) consciousness - artificial intelligence (AI)

elite figuring - high performance computing

haze figuring - fog/mist/cloud computing

designs preparing unit - graphics processing unit (GPU)

focal preparing unit - central processing unit (CPU)

work process motor - workflow engine

facial acknowledgement - face recognition

discourse acknowledgement - voice recognition

mean square (mistake | blunder) - mean square error

mean (outright | supreme) (mistake | blunder) - mean absolute error

(motion | flag | indicator | sign | signal) to (clamor | commotion | noise) - signal to noise

worldwide parameters - global parameters

(arbitrary | irregular) get right of passage to - random access

(arbitrary | irregular) (backwoods | timberland | lush territory) - random forest

(arbitrary | irregular) esteem - random value

subterranean insect (state | province | area | region | settlement) - ant colony

underground creepy crawly (state | province | area | region | settlement) - ant colony

leftover vitality - remaining energy

territorial normal vitality - local average energy

motor vitality - kinetic energy

(credulous | innocent | gullible) Bayes - naïve Bayes

individual computerized collaborator - personal digital assistant (PDA)

[bphnx]

Hela

Ultron

Mysterio

Venom

Doctor Doom

Red Skull

Green Goblin

Model: Dreamshaper XL 1.0

[hawkpartys]

What are your go-to resources for raptor identification?

the inaturalist dms of people smarter than me honestly

i'm infamously terrible about guides, i learn mostly from looking at just, massive quantities of images of the species, asking a lot of questions to people who went to school for this, and occasionally online guides

(mostly found by googling "[x] species field marks")

uhhhm raptors of europe and the middle east by dick forsman is a pretty helpful book. there are a ton of handy online guides for north american accipitriformes, but the resources start getting iffy once you venture into central/east asia and africa. im gonna summon kestrel because they are way better about this

@inaturalist-unofficial

[d0nutzgg]

Tonight I am hunting down venomous and nonvenomous snake pictures that are under the creative commons of specific breeds in order to create one of the most advanced, in depth datasets of different venomous and nonvenomous snakes as well as a test set that will include snakes from both sides of all species. I love snakes a lot and really, all reptiles. It is definitely tedious work, as I have to make sure each picture is cleared before I can use it (ethically), but I am making a lot of progress! I have species such as the King Cobra, Inland Taipan, and Eyelash Pit Viper among just a few! Wikimedia Commons has been a huge help!

I'm super excited.

Hope your nights are going good. I am still not feeling good but jamming + virtual snake hunting is keeping me busy!

[vestaignis]

Милое привидение в лесу. Cute ghost in the forest.

[augerer]

coming out on tumblr as someone whose taught "AI bootcamp" courses to middle school students AMA. . . .

[jillsarif]

[stablediffusion]

Fictional character Mona, ask away :)

Created with Stable Diffusion--a brand new open source AI by Stability AI.

Give us a follow on Twitter: @StableDiffusion

h/t MyKogInHerMaw

[aylen-san]

[aiweirdness]

I discovered I can make chatgpt hallucinate tumblr memes:

This is hilarious and also I have just confirmed that GPT-4 does this too.

Bard even adds dates and user names and timelines, as well as typical usage suggestions. Its descriptions were boring and wordy so I will summarize with a timeline:

I think this one was my favorite:

Finding whatever you ask for, even if it doesn't exist, isn't ideal behavior for chatbots that people are using to retrieve and summarize information. It's like weaponized confirmation bias.

more at aiweirdness.com

[lloreleya]

Новая нейросеть, которая может визуализировать ваш промт - https://ideogram.ai/

Я протестировала её, и осталась приятно удивлена. Она отлично справляется с запросами в фотореализме и можно что-то выбрать в художественных жанрах. С аниме получилось довольно туго (третья картинка), прорисовка мелких деталей вообще страдает. Bing с такими вещами справляется на порядок лучше. С другой стороны, настолько фотореалистичных букетов мне Бинг не рисовал))) Говорят, что она прекрасно интегрирует в изображение текст (чего не делают другие ИИ), без искажений и ошибок. Но я не пробовала ещё.

Промт можно вводить на русском языке, но я подозреваю, что его автоперевод может искажать смысл, так что для лучшего результата стоит всё-таки воспользоваться качественным переводчиком или собственными знаниями))

В бесплатном доступе примерно 5 запросов в сутки (10 кредитов, каждый запрос может стоить 2 кредита или больше, в зависимости от параметров). Каждый запрос генерирует по 4 картинки. Нейросеть однозначно перспективная и стоит внимания (если не скатится в сугубо платную подписку)

[dzamie]

Apparently Valve is now removing games with AI art, unless the creator can prove they have the licenses for all the training data (note: this is basically impossible unless you baked it yourself, which then makes it look like shit)

Image text:

After reviewing, we have identified intellectual property in [Game Name Here] which appears to belongs to one or more third parties. In particular, [Game Name Here] contains art assets generated by artificial intelligence that appears to be relying on copyrighted material owned by third parties. As the legal ownership of such Al-generated art is unclear, we cannot ship your game while it contains these Al-generated assets, unless you can affirmatively confirm that you own the rights to all of the IP used in the data set that trained the Al to create the assets in your game. We are failing your build and will give you one (1) opportunity to remove all content that you do not have the rights to from your build. If you fail to remove all such content, we will not be able to ship your game on Steam, and this app will be banned.

[fishyartist]

Idk I just think maybe if u assume every person disagreeing with you is a npc or a robot u might just be stupid or something. Learn more ok?