Top Python libraries `22
by @tryolabs
link: https://tryolabs.com/blog/2022/12/26/top-python-libraries-2022
#python #tools
Dear all,
Our friends are organizing AI & Natural Language conference in Yerevan next year, 21-22 April 2023. Guys are open for collaboration, if you want to organize a workshop on a thriving topic or a challenge, please contact them. All the info is in their channel: http://t.me/ainlconf
Best Python Concurrency Guides
- https://superfastpython.com/multiprocessing-in-python/
- https://superfastpython.com/python-asyncio/
- https://superfastpython.com/multiprocessing-pool-python/
- https://superfastpython.com/threadpool-python/
They are a bit bloated and explain the same concepts 10 times, but they try to explain the most unexplored parts of Python in detail in plain language with examples.
You can just read examples and intro.
Good stuff.
ML track at YaTalks 2022
YaTalks, Yandex’s main conference for the IT community, will be held on December 3 and 4. More than 100 tech experts from around the globe will gather to discuss technology and life in today’s ever-changing world. In the program, there are tracks about backend, frontend, mobile development, and, of course, machine learning.
Speakers will discuss:
• what significant events have happened in the sphere of machine learning for the last 10 years;
• how neural network-driven translation works;
• how generative neural networks create pictures and whether they are able to replace illustrators;
• and many other topical issues.
This year YaTalks will be streamed simultaneously in two languages — Russian and English — using neural network-driven voice-over translation technologies. The conference is online, so you can join it from anywhere in the world.
Learn more and register on the website
Tips & Tricks on Image Generation
Generating images with AI tools is a skill, which can be improved and enhanced. So here is couple of articles, covering tips & tricks on how to generate better images with #midjourney. Most interesting one is #huggingface prompt generator, which uses #NLP model to generate sample prompts.
As an example, we tried to reproduce and improve our group avatar, following ideas in the articles. Prompt for an illustration to this post was generated with query ferrofluids in form of a brain, beautiful connections chaos, swirling black network --ar 3:4 --iw 9 --q 2 --s 1250
Midjourney Prompt Generator: https://huggingface.co/spaces/doevent/prompt-generator
List of Midjourney prompts: https://www.followchain.org/midjourney-prompts/
An advanced guide to writing prompts for Midjourney ( text-to-image): https://medium.com/mlearning-ai/an-advanced-guide-to-writing-prompts-for-midjourney-text-to-image-aa12a1e33b6
#visualization #gan #generation #generatinveart #aiart #artgentips
#events : ML-тренировка
Когда: 17 (четверг) ноября 2022, 19:00 - 21:30 (сбор с 18:00)
Место: офис Яндекса (Москва, улица Льва Толстого, 16) + онлайн
Язык - русский
В этот раз нас ждёт 3 доклада:
- призер только что завершившегося Yandex ML Cup,
- 2ое место хакатона AgroCode Hack по анализу спутниковых снимков для виноградников
- организатор ML соревнований в информационной безопасности
Подробная программа по ссылке ниже
Будем рады видеть всех очно и онлайн ;)
Регистрация обязательна
Amos: An Adam-style Optimizer with Adaptive Weight Decay towards Model-Oriented Scale
Amos is a new optimizer that we propose to pre-train large language models. It is more efficient and converges faster than AdamW: ≤ 51% memory for slot variables, and better valid loss within ≤ 70% training time!Amos is a new optimizer that we propose to pre-train large language models. It is more efficient and converges faster than AdamW: ≤ 51% memory for slot variables, and better valid loss within ≤ 70% training time!
ArXiV: https://arxiv.org/abs/2210.11693
#NLU #NLP #optimizer
State of AI Report 2022
TLDR: We are moving forward and effective international collaboration is the key to progress.
Major Themes:
* New independent research labs are rapidly open sourcing the closed source output of major labs
* Safety is gaining awareness among major AI research entities
* The China-US AI research gap has continued to widen
* AI-driven scientific research continues to lead to breakthroughs
Website: https://www.stateof.ai
#report #stateofai #AI
“Listing Embeddings for Similar Listing Recommendations and Real-time Personalization in Search”
From #Airbnb team
https://medium.com/airbnb-engineering/listing-embeddings-for-similar-listing-recommendations-and-real-time-personalization-in-search-601172f7603e
Unfortunately, discrimination against ML competition participants becomes more frequent. CrowdANALYTIX recently launched a competition that simply bans different countries from opportunity to participate, this time including Russia.
Spread the word so that we could make Data Science and ML more open, without obsolete discriminatory rules on competition platforms:
https://www.facebook.com/DataChallenges/photos/a.136318350296824.1073741827.136313013630691/182693245659334/?type=3&theater
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs.
Now mankind can generate content for social networks without taking photoes.
Github: https://github.com/NVIDIA/pix2pixHD
Arxiv: https://arxiv.org/pdf/1711.11585.pdf
AI index report, demonstrating hype around AI techonologies: https://aiindex.org/2017-report.pdf
Читать полностью…#DeepLearning predicts when patients die with Average Precision 0.69 (that’s high).
Andrew Ng announced new project in his twitter: ML to help prioritize palliative (end-of-life) care. Model uses an 18-layer Deep Neural Network that inputs the EHR data of a patient, and outputs the probability of death in the next 3-12 months.
The trained model achieves an AUROC score of 0.93 and an Average Precision score of 0.69 on cross validation.
Site: https://stanfordmlgroup.github.io/projects/improving-palliative-care/
Arxiv: https://arxiv.org/abs/1711.06402
#project #DSinthewild #casestudy
StarGAN — a novel and scalable approach that can perform image-to-image translations for multiple domains using only a single model.
GitHub: https://github.com/yunjey/StarGAN
Arxiv: https://arxiv.org/abs/1711.09020
#deeplearning #gan #cv
Realtime object detection by Google.
https://research.googleblog.com/2017/11/automl-for-large-scale-image.html
YouTube demo: https://www.youtube.com/watch?time_continue=70&v=ERglPgx8wFg
#deeplearning #google #caption #detection
Some might have wondered what application will #Midjourney and #ChatGPT have.
What products will creators to build with them?
Here is one of examples of such human-AI collaboration — short illustrated story on TikTok having millions of views.
https://vt.tiktok.com/ZS8MENP51/
#AI_tools
AI-assistant tool for a slides deck generation
Stumbled upon a new startup Tome, which allows to create a deck given a text prompt, i.e. AI-assistant tool in creator economy
.
Emerge of such a service was only a question of time given the advance of Midjourney, Dall-E and GPT-3.
Tools like this will drastically improve quality of the presentations and reduce time requried to create a good deck.
Website: https://beta.tome.app/
Example of a deck: https://tome.app/kir/unlocking-the-creative-economy-with-ai-assistant-tools-clbxrl6r808cd813csocuomwi
There is a claim that #ChatGPT is capable of writing a code based on a text input
Why does it matter: it potentially can lower the barrier for programmers and allow more tools for efficient software development to emerge.
Source: tweet
#GPT3 #NLU #NLP #codegeneration
Speaking about real #usecases of #gpt3, there is a wonderful application for improving business communication through the adoption of #nlp / #nlu tools
Читать полностью…🔥Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding
TLDR: Scientists kinda learned how to read thoughts. Paper on the reconstruction of the visual stimuli based on fMRI readings.
Website: https://mind-vis.github.io
Github: https://github.com/zjc062/mind-vis
#fMRI #visualstimulireconstruction #mindreading #dl
Reinforcement learning course from MIPT.
The course consists of:
- Theoretical and practical material for beginners and advanced users
- Classical approaches based on utility functions and strategy gradient, as well as modern trends in improving the efficiency of the study of the environment, interaction with planning, using memory and hierarchical approaches.
- The best of David Silver's lectures, Sutton and Barto's book, and OpenAI, DeepMind works and articles from 2019-2022.
Materials:
- PDF slides and video lectures on each topic, Colab master classes and video lectures in Russian.
Course: https://clck.ru/32a3c9
If you are interested in an internship at MIPT in the areas of Reinforcement Learning, Computer Vision, Robotics or Self Driving Cars, you can apply here: https://cogmodel.mipt.ru/internship
Nature has published an article with a #superresolution approach for #CT scans.
https://www.sciencedaily.com/releases/2018/03/180321155324.htm
#arxiv: https://arxiv.org/abs/1704.08841
Graph shows what people really mean when they use vague terminology describing the probability of an event.
Читать полностью…Another paper on automl: Neural Nets learning to design Neural Nets.
A reinforcement learning agent that learns to program new neural network architectures.
Same/better results as LSTMs but with funky nonlinearities (sine, SeLus, etc) and new connections that result in different activation patterns.
Arxiv: https://arxiv.org/abs/1712.07316
Post: https://einstein.ai/research/domain-specific-language-for-automated-rnn-architecture-search
Video displaying progress of GANs for photo generation. Now you can use neural networks to generate HD photo of a person who never existed.
https://www.youtube.com/watch?v=XOxxPcy5Gr4
#GAN #youtube
An article about the impossibility of intelligence explosion. There will be no singularity or significant breakthrough and humanity will die off becuase of sun explosion.
francois.chollet/the-impossibility-of-intelligence-explosion-5be4a9eda6ec" rel="nofollow">https://medium.com/@francois.chollet/the-impossibility-of-intelligence-explosion-5be4a9eda6ec
#CapsNet #tutorial on the YouTube
https://www.youtube.com/watch?v=pPN8d0E3900
#deeplearning