Top Tweets for #AI_Lab
Student_Innovation_Shines : We are happy to share that our students' project has secured funding of INR 1 Lakhs from the Department of
Telecommunications (DoT).
#scis_uoh
#UoH
#DoT
#student_project
#funding
#Student_Innovation_Shines
#5G_lab
#AI_lab
@Department21600

#እኛ_የሚያጨበጭብልን_ካድሬ_አንፈልግም!
የ1ኛው ክፍለ ዘመን ብልፅግና ሰሙኑን በፕሮፓጋንዳ የተጠመደበት እኛ ሌላ ዓለም ውስጥ መግባታችንን አለማወቁ እጅግ ኋላቀር ስብስብ መሆኑንም መረዳት ይቻላል!😁 ጭራሽ የተማሪዎች #AI_Lab. ገብቶ መደስኮር🤣

India can’t be left behind in AI. @Krutrim has accelerated efforts to develop world class AI. As first step, our cloud now has DeepSeek models live, hosted on Indian servers. Pricing lowest in the world https://t.co/p112B9Dez9
Details on our AI lab, SOTA model and research progress, open source drops on 4th Feb!
Zapraszam do odsłuchania nowego odcinka SGcHat w paśmie #AI_Lab z udziałem prof. Bogdana Mroza z Katedry Badań Zachowań Konsumentów, który w rozmowie z prof. Tymoteuszem Doligalskim (AI_Lab | SGH) mówił o trendach konsumenckich w analogowo-cyfrowym tyglu.
https://t.co/y6vGd7QbY7

#MIT's Improbable #AI_Lab introduces HuGE, a groundbreaking approach to #robot_training. Leveraging nonexpert human feedback globally, it accelerates learning, enabling robots to master tasks independently and efficiently. Discover more: https://t.co/IVXBn1teqX

Aligning Large Language Models through Synthetic Feedback
propose a novel framework for alignment learning with almost no human labor and no dependency on pre-aligned LLMs. First, we perform reward modeling (RM) with synthetic feedback by contrasting responses from vanilla LLMs with various sizes and prompts. Then, we use the RM for simulating high-quality demonstrations to train a supervised policy and for further optimizing the model with reinforcement learning. Our resulting model, Aligned Language Model with Synthetic Training dataset (ALMoST), outperforms open-sourced models, including Alpaca, Dolly, and OpenAssistant, which are trained on the outputs of InstructGPT or human-annotated instructions. Our 7B-sized model outperforms the 12-13B models in the A/B tests using GPT-4 as the judge with about 75% winning rate on average
paper page: https://t.co/fzU7q3urHV

[1/9] How to be a scalable video-language model in terms of video length?🤔 🎞️
We propose a 🌟Semi-Parametric Video-Grounded Text Generation🌟 as the answer, treating a video as an external data store and employing cross-modal retrieval.
📜 https://t.co/rxpNOt8LGX
![SungdongKim4's tweet photo. [1/9] How to be a scalable video-language model in terms of video length?🤔 🎞️
We propose a 🌟Semi-Parametric Video-Grounded Text Generation🌟 as the answer, treating a video as an external data store and employing cross-modal retrieval.
📜 https://t.co/rxpNOt8LGX https://t.co/opi6nWnfjs](https://pbs.twimg.com/media/Fnw-wqmaQAU79EA.png)
Can We Find Strong Lottery Tickets in Generative Models? (AAAI'23, Oral)
Abs: Yes.😃The discovered subnet can perform similarly or better than the trained dense model even when only 10% of the weights remain!
Project page: https://t.co/YtMXMYvgQb
Paper: https://t.co/6BDcGjm0mm

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