We're hiring! I'm searching for a Tech Lead for the area of the Documents processing automatisation in the sphere of the FinTech (International Business). We expect senior skills in the OCR and NLP ML tasks, understanding the enterprize architecture, and willing to code, not only to manage. It's a remote full-time position. #вакансия #тимлид #техлид #ml #ds #nlp #ocr #textrecognotion
Varvara Novozhilova’s Post
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Great guide to use MJ, simple and clear. (In Russian) https://lnkd.in/eM7HzDHq
⚡️Midjourney от А до Я ⚡️Запрос, стиль, правки и другие возможности
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It’s like viruses vs antiviruses. Both tech lines will be actively developed within several next years (maybe even decades). We have some solutions, helping to test whether the image is artificial or not. We’ll get something similar for the videos checking soon. This software isn’t perfect, so they’re going to fight for some time. The thing is, antivirus protection os really strong nowadays, but small not really perfect viruses are still getting to their aims sometimes. For the reason of the lack of education of some users in this sphere. That’s what important to improve in ourselves and people around us. #ai #deepfake #education
This is eye-opening. We are getting closer to a world where nothing can be trusted online: I recently came across DeepFacelive. It's a tool that can perform real-time face-swapping during live broadcasts and video calls. • Video calls: Change your face in real-time during a video call or use a pre-recorded video • Live-streaming: Adjust your facial expressions or entire appearance • Facial animator: Control static facial images and manipulate them through your own face We've seen another example pop up in April 2024 with Microsoft's hyper-realistic talking head AI: VASA-1. It can generate lifelike talking faces of virtual characters all from a single static image and audio clip. My takeaways: • Proof of authenticity will be an absolute must to solve what is coming • I believe real-world interaction is more important than ever • Zoom meetings are about to get a whole lot more interesting If you enjoy insights like this, follow me Alex Banks for more on AI.
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Simple thought about using ChatGPT. We all know it's really helpful, weather it's obvious, that it's not always that helpful. So, when it is and when it's not? My theory is: - it's not the best choice if you know nothing at all about the topic, as LLM could give you wrong information, for example using the wrong default context when you didn't noticed, that there could even be several contexts, which are important. - it's not that helpful, if you are the top-master of the topic, you asking about. You know it better, deeper, and closer to your own very determinated opinion. For sure. But it still helps to type for you, at least (but you'll definitely review and change the result a little) - So, it's the most helpful when you kinda know the topic, and understand the main context variations more or less, but you're not the expert in it. In this case you will quite likely recognise the bullshit, but the LLM for sure knows much more, especially, it you're get acquainted with the prompt engineering tips and tricks. #ChatGPT #simpletips
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Seems to be useful for those who start their path on the road of the prompt engineering.
Google has published a 45-page guide to prompt-engineering, generally sharpened for dozens of different use-cases in different roles. The basic recommendations are pretty basic, but still very valuable. Things to consider in a prompt: - Persona: Who you are - Task: What you need the LLM to do (write, summarize, change tone, etc.) - Context: As much context as possible. This could be a written description or a link to an existing document in Google Drive. - Format: Paragraphs, talking points, specifying character limits, etc. More tips from Google: - Break the assignment into parts. - Specify limitations. - Assign a role. - Ask for feedback. - Consider tone. - Say it in a different way. Examples from different roles (you can find many more in the PDF): Customer Service Draft templates for three different types of customer communication. Create a template for apology emails, order confirmation messages, and thank you notes for loyal customers. Keep each template to one paragraph and use a friendly tone. Executives I’m the COO of a mid-sized company. I am hosting a quarterly town hall meeting with the entire company. There has been a lot of positive progress and momentum this quarter, but I am worried that multiple teams have low morale due to some unforeseen setbacks. I want to brainstorm and practice how I will respond to potentially tough questions. Help me write challenging questions that employees may ask at the upcoming town hall about our earnings, leadership changes, and vision of the company. Generate potential answers for each question that use a confident but firm tone. HR Write a list of 20 open-ended interview questions for [open role URL] that I can use to screen candidates. Marketing Create compelling copy for a landing page promoting a new [ebook/webinar/free trial and details] designed for an executive target audience. Highlight key benefits and encourage conversions with persuasive calls to action. Project Management Summarize this call transcript in a short paragraph. In bullet points, highlight the action items, decisions made, and owners for each item based off of [call transcript]. Sales Draft a customized script for me to follow during my sales call with a prospect. The call will happen over a video call and is set to last 30 minutes. Make sure to add the following in the script: How [insert company products/solutions] can help address potential customer’s pain points, how [company]’s delivery system guarantees seamless and timely delivery, competitive pricing and volume-discount table, and space for a customer reference in the [customer’s industry] industry. I highly suggest checking if your usecases are in there and trying them - https://lnkd.in/ddj4rJRq
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#video #sora #adobe Adobe announced the integration of Sora (and other models, there’s no full list, but Sora, Runaway and Pika labs have been mentioned) into Premiere before the end of the year. powered by Adobe FireFly. you can on the go - extend the video - generate the necessary parts of the selected area, describing the scene that you want to get with the prompt - automatically select and remove objects from the video (I really think this feature will likely work worse than in the video teaser) - change clothes - remove brand marks and more Adobe will transparently show which part of the video has been augmented, and which is completely generated. I liked this article on the topic, there is also a video with the functionality https://lnkd.in/d2Bz-j5r What do you think? Would you buy premiere especially for this features?
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A nice idea for the self study variant of the task. I’d give it a try. Does anyone know something similar to improve Spanish?
Podcast Producer ✸ Owner of Castpodcast studio for companies. We help our clients make B2B and B2C podcasts and create community with their podcasts.
Last week we launched a new project called Repeater 🚀 This is an application for Russian-speaking people who want to learn English and remember new words without pain. In the first version it's just a bot in Telegram, but we plan to create mobile apps. How does it work? You just text the bot a new word you came across in a book, article, movie, etc. and it will reply with a simple sentence containing that word. Every two hours the bot will send you different sentences. It needs to create a context for new word because you need to encounter new word several times before your brain remembers it. You can also look up the meaning of this word in English. Or you can translate it to Russian directly from the bot. I'll be happy if you try our bot. It's free. The next version will include other types of content like videos with words and pictures. Have fun! https://repeater.one ⚡️
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#avatar #heygen #video A couple of days ago I discussed with a friend the service https://lnkd.in/e6sF-V-W In a fairly large company with a legal entity in one of the EU countries (I cannot disclose the name), this service is used to create educational videos. Wherein - company filmed 10-minute base videos with teachers (real people) - Wrote the text of the training itself - Used generation of speech (with the concrete voice of a living person) and video (with the concrete face of a living person) — collected in the service. It is worth noting here that the experts did not always speak English, but the final outcome video did. - company added the montage and improvement by hand stage (this stage is usually needed between generation and production, to my mind). Result - company tested the result on the wives and mothers of living teachers — they did not recognize the generative content (!). - One minute of video generation cost about $4 (this is the net price for generation in the service, excluding payment for the work of people before and after). - it turned out very quickly and the company is happy with the outcome quality. I think this like processes will improve the process of training videos creation rather soon. Of course it’s not suitable for every teaching process (really not), but it’s an interesting solution for the corporative universities basic courses at least. More smaller companies will be able to afford educative videos for their employees with this process involved. What do you think?
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Too tired to add my own today, but it’s genius) I couldn’t skip sharing with you 🙌🏻🥰
Building AI/ML startup MVPs fast | Co-founder of Epoch8.co & AGIMA.AI – tech agencies for modern data projects
Machine Learning jargon buster: 5 machine learning concepts explained in emojis 1. Supervised Learning: 👩🏫📚 → 🤖🎯 A trainer (👩🏫) provides a model (🤖) with labeled examples (📚), so it can make predictions or classifications (🎯) on new, unseen examples. 2. Unsupervised Learning: 🤖👀 → 🍎🍌🍎🍌 → 🤖🤔 → (🍎🍎), (🍌🍌) A model (🤖) explores items (🍎🍌) without labels. It observes (👀) the item's features. On its own (🤔), it finds similar items (🍎🍎), (🍌🍌). 3. Deep Learning: 🤖(🧠🔗🧠)👀 → 🖼️📚🎶 → 🤖(🎨🗣️🎵) A model (🤖) has a digital brain (🧠) composed of interconnected nodes (🔗), resembling the neurons of the human brain. These nodes are structured into multiple layers (🧠🔗🧠) and collaborate to process information. This multi-layered digital brain (🧠🔗🧠) learns from images (🖼️), text (📚), and audio (🎶). It finds (👀) patterns in data and performs tasks like image recognition (🤖🎨), speech recognition (🤖🗣️), and music generation (🤖🎵). 4. Reinforcement learning: 🤖🎮 → 🚶♂️🕹️ → 🎯❓ → (✅🍬)(❌🚫) → 🤖🎯🏆 Robot (🤖) plays a game (🎮). The robot tries different paths and actions (🚶♂️🕹️) and receives feedback (🎯❓) in the form of rewards (✅🍬) or penalties (❌🚫). Through trial and error, the robot learns which actions lead to the best outcomes, ultimately achieving success (🎯🏆) in the game. 5. Transfer Learning: 🤖📚🐱 → 🤖🎓🐶 A model (🤖) shares knowledge (📚) from one domain (🐱) to another (🐶), using pre-existing expertise (🎓) to tackle new tasks. Add some yours? :)
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#PKUYuanGroup #sora #opensora The next version of OpenSora has appeared. They promise higher generation quality, longer videos can be generated (longer than 10 seconds), and the resolution has been increased from 512x512 to 1024x1024. - Github https://lnkd.in/eHagkiFD - Online demo (direct link) https://lnkd.in/eGDRHaue - now there is a very large queue for generation and sometimes it ends with an error, because there may not be enougth a processor quota for the request that's enough. (1 frame video generates)
GitHub - PKU-YuanGroup/Open-Sora-Plan: This project aim to reproduce Sora (Open AI T2V model), but we only have limited resource. We deeply wish the all open source community can contribute to this project.
github.com
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“When someone has written the cloth of spaghetti code and is trying to figure out what's where” by Denis Novozhilov via #mj
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