I don't have a GPU that'll run it, so I have no idea what it's like, but it deserves more attention for the effort. Boost for visibility if that's your thing?
Introduction to forecasting with ARIMA and seasonal ARIMA with Python 🚀👇🏼
This short tutorial by Joaquín Amat Rodrigo and Javier Escobar Ortiz provides an introduction to forecasting with ARIMA models using Python 🐍. This includes using different flavors of ARIMA methods from the statsmodels, pmdarima, skforecast, and statsForecast libraries.
That's the paper that introduced the #Transformer architecture, dispensing with recurrence and convolutions to achieve much faster training times and higher performance in a language task.
If you had the feeling that the online discussion about COVID-19 vaccines was biased depending on the actors, you are right.
Using #MachineLearning and #NetworkScience we have shown that being a human or a bot, verified or unverified (according to previous Twitter rules) and political leaning were relevant factors for choosing the words in posts and, accordingly, the corresponding emotions to trigger.
A genuine computational social science study, led by Anna Bertani for her Msc thesis, now published also in collaboration with Riccardo Gallotti and Pierluigi Sacco
I have run out of severance and now I'm running out of savings. It's do or die now, folks. Job offers, job leads, job hunting advice...please send them all my way, and/or boost for reach. Freelancing is on the table, too. Details about me and what I'm looking for, to follow.
I'm very excited to announce that the Statistics Globe online course on "Principal Component Analysis (PCA): From Theory to Application in R" has just started.
(1/2) Moirai - Salesforce's Foundation Forecasting Model 🚀
Salesforce recently released Moirari - a new #Python 🐍 library with a foundation model for time series forecasting applications. According to the release blog - the model comes with universal forecasting capabilities and can handle multiple scenarios and different frequencies.
The below course by Dhaval Patel is a beginner-level course for Deep Learning in Python with Tensorflow 2.0 and Kares. The course covers the foundations of neural network and deep learning, which includes the following topics: 🧵👇🏼
Wait, are people getting money just for pairing random #scifi concepts with #AI? Well, let me tell you my amazing idea for using an Oscillation Overthruster to bring #MachineLearning to the eighth dimension!
the ask envision on the @letsenvision app is cool, I loaded a 50 page pdf and it just do a RAG on it and answers my questions comprehensively, people should use it more, I hope in future I can load entire folders of document on desktop to do rag #machineLearning#AI#blind#disability
AI already uses as much energy as a small country. It’s only the beginning.
AI will make bitcoin's environmental devastation look like a picnic.
"If ChatGPT were integrated into the 9 billion searches done each day, the IEA says, the electricity demand would increase by 10 terawatt-hours a year — the amount consumed by about 1.5 million European Union residents."
There's a reason why some, in software behemoth companies, are interested in biological neural circuit architectures: the latter are extremely energy efficient.
At the same time, there's a subset of machine learning practitioners that dismiss neuroscience and neuroscientists as being entirely off track when it comes to understanding how neural networks compute.
This contraposition is quite the interesting dynamic to observe. Says more about the individual people than about the field, as is often the case.
(1/2)Statistical Inference via Data Science - New Edition 📚👇🏼
The Statistical Inference via Data Science by Chester Ismay and Prof. Albert Y. Kim recently released a new edition. This book focuses on the data analysis workflow and how to answer questions with data. This includes the following topics:
✅ Data wrangling
✅ Data visualization
✅ Simple and multivariate regression analysis
✅ Sampling and bootstrap
✅ Hypothesis testing
Well, you'd think #AI and #generativeAI like #DALL·E wouldn't be a problem for #fanfiction and #fanart, where you can't own the IP or sell it, but you'd be wrong. People posing as fan artists and LoRa's and artist style stealing are all in the article. The fandom is #MLP. There are links to other related issues.
Every couple of days I get approached on Discord by AI scam artists. And I am sure it will get worse.
It's sad. I've bought fan art from real artists that are so good, I've suggested they branch out and find a commercial outlet. I've commissioned them for cover art.
If this trend continues and AI kills all human artists off, creativity will stagnate. No further innovative styles, just ad nauseum repetition of what we've seen posed differently or put on different backgrounds.
It is a very human behavior to go with what requires the least amount of work to produce results. It's how rap took over the world and exists in every language. Every. Language. Even Bushman. It requires no training or instrument. Yes, I like some rap songs, I'm not ragging on the form, but everyone can do it and the musically inclined can produce passible songs. Maybe it is democratizing versus rock & roll or jazz, etm., but it is also often monochromatic and repetitive.
When #AI and #generativeAI stop producing monsters and hallucinations, I face it, it will become widely used. /The reason that companies like #Apple are interested in #machinelearning and #ai, is it will push the computing envelope—and sales./ Having to pay for renders, and, worse, having to wait for them, competing with hundreds or thousands for a shared computing resource, is not sustainable. Super-GPUs and ML chips are the future of home computing so you can use your AI tools at home.
Here we go again: The boom in artificial intelligence (AI) and quantum computing will drive a spike in energy use, the National Grid has predicted. Data centre power use 'to surge six-fold in 10 years' https://www.bbc.com/news/technology-68664182 all this power usage for shity LLM/AI to write poems, pictures, videos etc from stolen data to train AI. #artificialintelligence#machinelearning