A sign of progress in natural language processing for Amharic.
Source
@TechInEthio

Docker Architecture and Components

1. Docker Daemon (dockerd):
- 𝗥𝗼𝗹𝗲: Manages Docker containers on a system.
- 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀: Building, running, and managing containers.

2. Docker Client (docker):
- 𝗥𝗼𝗹𝗲: Interface through which users interact with Docker.
- 𝗖𝗼𝗺𝗺𝗮𝗻𝗱𝘀: build, pull, run, etc.

3. Docker Images:
- 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻: Read-only templates used to create containers.
- 𝗥𝗼𝗹𝗲: Serve as the basis for creating containers.
- 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆/𝗛𝘂𝗯: A storage and distribution system for Docker images.

4. Docker Containers:
- 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻: Runnable instances of Docker images.
- 𝗥𝗼𝗹𝗲: Encapsulate the application and its environment.

5. Docker Registry:
- 𝗥𝗼𝗹𝗲: Store Docker images.
- 𝗣𝘂𝗯𝗹𝗶𝗰 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆: Docker Hub.
- 𝗣𝗿𝗶𝘃𝗮𝘁𝗲 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆: Can be hosted by users.

Embracing the profound significance of Blessed Good Friday, a sacred journey of faith and devotion. May the sacred melodies and heartfelt prayers of this blessed day illuminate our souls and inspire us to embrace compassion and love. Wishing everyone a blessed Good Friday. #GoodFriday #DivineBlessings
Happy holiday techet fam

AI in 2030😂

Domain Knowledge + creative mind + AI tools >>>

@techinethio

Washed Out's new single "The Hardest Part" features a music video created entirely using OpenAI's Sora😶‍🌫️👯💃🕺

@techinethio
#sora

Java Forever And Ever, the Movie

Recreated Sora's video with Jonny Ragga's 'ቁልፉን ስጪኝ' music😁

Enjoy🎧

@techinethio

$250 robot arms that can fold clothes 🤖
Source

@techinethio

Man vs Robot: Chinese robotics company LimX Dynamics shows how good bipedal balance and navigation has become.
source

this is how we are living in Ethiopia lol😁
@techinethio

Direct-a-Video: driving Video Generation

Direct-a-Video is a text-to-video generation framework that allows users to individually or jointly control the camera movement and/or object motion. Authors: City University of HK, Kuaishou Tech & Tianjin.

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅ Decoupling camera/object motion in gen-AI
✅ Allowing users to independently/jointly control
✅ Novel temporal cross-attention for cam motion
✅ Training-free spatial cross-attention for objects
✅ Driving object generation via bounding boxes

Paper: https://arxiv.org/pdf/2402.03162.pdf
Project: https://direct-a-video.github.io/

መልካም በዓል
@techinethio

X Introduces AI-Powered News Summaries with Grok👌
source

@techinethio

what is your os?

Did you know there's a really cool Sign Language Translator Glove out there?

Meet the BrightSign Glove...this nifty gadget translates sign language into spoken words and text right as you sign! It's perfect for making conversations smoother in school, work, or when you're just out and about. Really, it’s a game changer for anyone using sign language. Talk about a smart way to bridge communication gaps!

@techinethio
#Brightsignglove

Here's another glove invention by two nineteen-year-old kids back in 2016. Imagine being nineteen and coming up with such a cool invention!

@techinethio
#translatorgloves

Here is my prompt asking ChatGPT if it is possible to use AI for real-time translation between sign language and spoken language.

Hey, do you think AI could be used for real-time translation between sign language and spoken language? I've heard about gloves that can perform translations, but how can AI improve the efficiency of this process? Explain shortly

And Here is the response:

Yes, AI can definitely be used to improve the real-time translation between sign language and spoken language. While devices like gloves can capture the movements and positions of the hands and fingers to interpret sign language, AI can enhance the accuracy and efficiency of this process in several ways:

Gesture Recognition: AI algorithms can be trained on large datasets of sign language gestures, enabling them to recognize and interpret a wide range of signs with high accuracy. This is more sophisticated than simpler sensor-based systems, as AI can account for nuances and variations in individual sign language usage.
Contextual Understanding: AI can use natural language processing (NLP) to understand and generate contextually appropriate translations. Unlike basic word-for-word translation, AI can analyze whole sentences or conversations to provide more accurate and meaningful translations.
Non-Manual Signals: Sign language isn't only about hand movements; facial expressions and body language also play a crucial role. AI can integrate visual recognition technologies to interpret these non-manual signals, providing a more comprehensive translation.
Real-time Processing: Advanced AI models can process inputs and provide outputs nearly instantaneously, which is crucial for real-time communication. Improvements in computing power and optimization of AI models further enhance this capability.
Learning and Adaptation: AI systems can continue to learn and improve over time. They can adapt to the personal signing style of a user, learn new signs and idioms, or update their translations based on feedback.
In summary, AI can significantly enhance the translation of sign language to spoken language by leveraging deep learning for more accurate gesture recognition, contextual translation, and real-time processing, creating a more effective and user-friendly communication tool.

@techinethio