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#creativeai

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nemo™ 🇺🇦

Unleash your creativity! ✨ The Perchance AI Text-to-Image Generator lets you turn words into stunning visuals. Perfect for artists, writers, and anyone who loves AI. Try it out and see what you can create! ➡️ perchance.org/ai-text-to-image #AI #Art #Generator #CreativeAI 🎨🤖

perchance.orgAI Image Generator (free, no sign-up, unlimited)A *fast*, unlimited, no login (ever!!!), AI image generator. Generate large *batches* of images all in just a few seconds. Generate AI art from text, completely free, online, no login or sign-up, no daily credit limits/restrictions/gimmicks, and it's fast. Other AI art generators often have annoying daily credit limits and require sign-up, or are slow - this one doesn't. Use this AI to generate high quality art, photos, cartoons, drawings, anime, thumbnails, pfps, and more. Create OCs, anime characters, AI villains, fanfic artwork, and pretty much anything else. It's an AI-based image generator - i.e. a text-to-image model. No watermark, no account needed, unlimited images. Type words, make pics.
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Harald Sack

Next stop on our brief #timeline of (Large) #LanguageModels is 2022:
InstructGPT is introduced by OpenAI, a GPT-3 model complemented and fine-tuned with reinforcement learning from human feedback.
ChatGPT is introduced by OpenAI as a combination of GPT-3, Codex, and InstructGPT including lots of additional engineering.
#ise2023 lecture slides: drive.google.com/file/d/1atNvM
#RLHF explained: huggingface.co/blog/rlhf
#ai #creativeai #rlhf #gpt3 #gpt #openai #chatgpt #lecture #artificialintelligence #llm

Slide from Information Service Engineering 2023 lecture, BRief History of (Large) Language Models: 2022, InstructGPT is introduced by OpenAI, a GPT-3 model complemented and fine-tuned with reinforcement learning feedback. Improved instruction following and less likely producing hallucinated answers. ChatGPT introduced by OpenAI, a combination of GPT-3, Codex, and InstructGPT plus a massive engineering effort. Bibliography: N. Lambert, L. Castricato. L. von Werra, A. Havrilla. (2022). Illustrating Reinforcement Learning from Human Feedback (RLHF). huggingface.co.
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Harald Sack

Next leg in our brief history of (Large) #LanguageModel is 2020, when #GPT-3 was released by OpenAI, based on 45TB data crawled from the web. A “data quality” predictor was trained to boil down the training data to 550GB “high quality” data. Learning from the prompt was introduced (few-shot learning)
Lecture slides: drive.google.com/file/d/1atNvM
paper: proceedings.neurips.cc/paper/2
@fizise #ai #artificialintelligence #creativeai #llm #ise2023 #lecture

Lecture SLide from Information Sertvice Engineering 2023, A Brief HIstory of (Large) Language Models: GPT-3 was released by OpenAI, based on 45TB data crawled from the web. A “data quality” predictor was trained to boil down the training data to 550GB “high quality” data. Learning from the prompt is introduced (few-shot learning). Bibliography: T. B. Brown et al. (2020). Language models are few-shot learners. In Proceedings of the 34th Int. Conf. on Neural Information Processing Systems (NIPS'20). Curran Associates Inc., Red Hook, NY, USA, Article 159, 1877–1901.
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Harald Sack

Next step in our brief timeline of (large) #languagemodels from our #ise2023 lecture was statistical language modeling with n-grams based on large text corpora as introduced and popularized by Frederick Jelinek and Stanley F. Chen using statistical tricks like Bayes Theorem, Markov Assumption, and Maximum Likelihood Estimation, etc.
Slides: drive.google.com/file/d/1atNvM
@fizise #nlp #llm #llms #artificialintelligence #ai #lecture #creativeAI

Slide from the Information Service Engineering 2023 lecture. Brief Timeline of (Large) Language Models about statistical N-gram models. "1990s: N-grams for statistical language modeling were introduced and popularized by Frederick Jelinek and Stanley F. Chen from IBM Thomas J. Watson Research Center, who developed efficient algorithms and techniques for estimating n-gram probabilities from large text corpora for speech recognition and machine translation." Furthermore, the formula to compute the conditional probability of an n-gram is given with a depiction of the N-gram Shakespeare generator with 1-grams, 2-grams, 3-grams and 4-grams. The picture of WIlliam Shakespeare has been created via ArtBot. Bibliography: F. Jelinek (1997), Statistical Methods for Speech Recognition, MIT Press, Cambridge, MA.
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Harald Sack

Last thing we've discussed in the "Limits of #AI" chapter of the #ISE2023 lecture was the threat of the so-called #Singularity. What is the singularity? Under which circumstances can it possibly happen? How real is this threat and should we better already aim for potential regulations?
Slides: drive.google.com/file/d/1LUOA-
@fizise @enorouzi @KIT_Karlsruhe #machinelearning #deeplearning #philosophy #aiart #stablediffusionart #creativeai

SLide from Information Service Engineerring 2023 lecture no. 12, Basic Machine Learning 03, on the Singularity. Under the Singularite, we understand a hypothetical future point in time at which technological growth becomes uncontrollable and irreversible, resulting in unforeseeable changes to human civilization. According to the most popular version of the singularity hypothesis, I. J. Good's intelligence explosion model, an upgradable intelligent agent will eventually enter a "runaway reaction" of self-improvement cycles, each new and more intelligent generation appearing more and more rapidly, causing an "explosion" in intelligence and resulting in a powerful superintelligence that qualitatively far surpasses all human intelligence.
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CerYo

Hi, um auszuprobieren, habe ich ein Märchen geschrieben: „A fairytale of 5 pink sea urchins“ / „Das Märchen der fünf pinken Seeigel“. In den kommenden Wochen poste ich als Prompt genutzte Textabschnitte mit den dazugehörigen Bildergebnissen. Bin sehr gespannt, was dabei rauskommt und freu mich über Reaktionen.

To play around with I wrote a fairytale (s.a.) I the upcoming weeks I`ll post image results and the connected text-prompt-snippets and the. I'm really curious,what happens & happy to get reactions.

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Harald Sack

In last week's #ise2023 lecture we were discussing the Turing Test aka the Imitation Game as means to test a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human... However, in times of #ChatGPT we have to rethink our concepts of "intelligence".
Slides: drive.google.com/file/d/1LUOA-
#machinelearning #ai #turing #turingtest #intelligence #lecture @fizise @enorouzi #aiart #creativeai #stablediffusionart

Slide from the lecture Information Service Engineering 2023, Basic Machine LEarning 03, The Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human.
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Harald Sack

The 2nd #AI winter had several causes: the collapse of the LISP machine market, a Slowdown in deployment of expert systems, the end of the Japan's Fifth Generation project, and DARPA's subsequent cutback of Strategic Computing Initiative...
Slides: drive.google.com/file/d/1LUOA-
#artificialintelligence #aiwinter #LISP #machinelearning #lecture @fizise @enorouzi #aiart #stablediffusionart #creativeAI

Slide from the Information Service Engineering lecture no 12, Basic Machine Learning 03, on Neural Networks and Deep Learning, about the 2nd AI WInter. Depicted is a desolate empty winter landscape with some deserted 1990s cars covered with a bit of snow.
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Harald Sack

"A perceptron cannot even solve the XOR problem, so why bother?"...Welcome to the first #AI Winter. We delved a bit into the history of #neuralnetworks in this week's #ise2023 lecture. Want to learn more about the XOR problem, just have a look into the slides (pp. 12-13):
drive.google.com/file/d/1LUOA-
@fizise @enorouzi #machinelearning #lecture @KIT_Karlsruhe #aiart #stablediffusionart #creativeAI

Slide from Information Service Engineering lecture 12, Basic Machine Learning 3, on Neural Networks and Deep Learning. The slide is depicting "The First AI WInter" from mid 1970s to early 1980s...created via ArtBot, showing a desolate empty post apocalyptic winter landscape with some deserted 1960s cars covered with some snow.
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