World robot conference in Beijing. The future is unfolding right now, and it won’t be long before we see robots walking alongside us, helping us, interacting with us - and I think everyone will want one.

GPU programming differs significantly from traditional CPU programming due to its parallel processing nature. While CPU programming often relies on sequential execution of instructions, GPU programming executes many threads simultaneously, making it faster for certain tasks.

Large Language Models(LLMs) are used in technologies like Chatbots. As AI develops further, it is crucial for us to understand how they work. 💪

Do you remember the days when we constantly refreshed our browsers just to see if new emails or messages had arrived? Back then, internet communication mostly relied on sending requests to servers and waiting for responses, leading to frequent manual refreshing or page reloads.😆

The essentials of user authentication in Node.js and Express in under two minutes! Discover how to keep your web applications secure, hash passwords, handle sessions and tokens, and more. Dive into the world of web security with this quick guide. #NodeJS #Express #Authentication

Like me, MKBHD says: I'm still gonna call it Twitter -> Musk: Nope, you won't. 🤷‍♂️🤷‍♂️😂😂.

Last month my youtube channel was found with keywords like text mining, latent semantic analysis, digital humanities, latent drichlet allocation and topic modeling. Interesting here is digital humanities, I don't have any particular video about it, but it is indeed the field😃👍

My talk about the technologies behind the tools like ChatGTP. #chatgpt #deeplearning #nlp and #nlu.Thank you to the legato team for hosting me and please check out also their seminar on Machine Learning

Just published my newest video about word2vec: Many others (fasttext, sequence2sequence, BERT) are coming.

RT @NetPreserve: 🆕 on the blog this #WebArchiveWednesday: a post from the @WARC_net AWAC2 Team on studying Women & the COVID-19 Crisis thro….

#warcnetchallenge: Run a topic modeling for more than 40G text from archieved web pages in 20/21. Pick a topic like "children health mental child support family parents anxiety families care people social kids resources stress home time violence young women" and see the domains

Interview about Generative Adversarial Networks in LUCET with @DominicHarion. Watch the full interview:

.For more information see my newest video on youtube about Document Term Matrix and Vector Space Model as Foundation for Word2Vec, Topic Modeling and other NLP Deep Learning Technologies

just uploaded my newest video about my favorite 5 tools/commands for handling large files under linux: list, head, tail, less and grep:.

Do I have everything in the right order to convey the newest Deep Learning Technologies for spoken(signal) and written language(text) assuming one technology depends on another? Or is it going too far and some parts are not really needed (or might be added)?

RT @EuroCC_Lux: "#Supercomputers are composed by different #architectures of computer resources:. #CPUs, processors roughly the same family….

My newest video: A Gentle Introduction to Topic Modelling, Latent Semantic Analysis and Latent Drichlet Allocation. Please like, comment, share and subscribe.

RT @unleasharchives: The AWAC2 team (@valerie_schafer @KarindeWild @inactinique @NielsBr @aasmanna @SophieGebeil @JSirajzade) is conducting….

Preparing a new video about Topic Modelling, like this one: Here is the question: How many topics does one need for more than a million documents, like it is the case for the CORD19 dataset?.