📣 Meta AI:
🫥 Make-a-video: The text-to-video generation without text-video data
🫥 Paper: https://makeavideo.studio/Make-A-Video.pdf
🫥 Project page: makeavideo.studio
An effective method that extends a diffusion-based T2I model to T2V through a spatiotemporally factorized diffusion model.
🫥 Make-a-video: The text-to-video generation without text-video data
🫥 Paper: https://makeavideo.studio/Make-A-Video.pdf
🫥 Project page: makeavideo.studio
An effective method that extends a diffusion-based T2I model to T2V through a spatiotemporally factorized diffusion model.
📣📣An AI used medical notes to teach itself to spot disease on chest x-rays
🫥🫥A team of researchers from Harvard Medical School trained the CheXzero model on a publicly available data set of more than 377,000 chest x-rays and more than 227,000 corresponding clinical reports. This taught it to associate certain types of images with their existing notes, rather than learning from structured data that had been manually labeled for the task.
Paper:
https://www.nature.com/articles/s41551-022-00936-9
News link:
https://www-technologyreview-com.cdn.ampproject.org/c/s/www.technologyreview.com/2022/09/15/1059541/ai-medical-notes-teach-itself-spot-disease-chest-x-rays/amp/
🫥🫥A team of researchers from Harvard Medical School trained the CheXzero model on a publicly available data set of more than 377,000 chest x-rays and more than 227,000 corresponding clinical reports. This taught it to associate certain types of images with their existing notes, rather than learning from structured data that had been manually labeled for the task.
Paper:
https://www.nature.com/articles/s41551-022-00936-9
News link:
https://www-technologyreview-com.cdn.ampproject.org/c/s/www.technologyreview.com/2022/09/15/1059541/ai-medical-notes-teach-itself-spot-disease-chest-x-rays/amp/
📣CLIP: The Most Influential AI Model From OpenAI — And How To Use It
🍀 CLIP stands for Constastive Language-Image Pretraining
🍀 CLIP is an open source, multi-modal, zero-shot model.
🍀 Given an image and text descriptions, the model can predict the most relevant text description for that image, without optimizing for a particular task.
🍀CLIP is trained using a staggering amount of 400 million image-text pairs. For comparison, the ImageNet dataset contains 1.2 million images.
🍀The final tuned CLIP model was trained on 256 V100 GPUs for two weeks. For an on-demand training on AWS Sagemaker, this would cost at least 200k dollars!
🍀 The model uses a minibatch of 32,768 images for training.
🍀 CLIP stands for Constastive Language-Image Pretraining
🍀 CLIP is an open source, multi-modal, zero-shot model.
🍀 Given an image and text descriptions, the model can predict the most relevant text description for that image, without optimizing for a particular task.
🍀CLIP is trained using a staggering amount of 400 million image-text pairs. For comparison, the ImageNet dataset contains 1.2 million images.
🍀The final tuned CLIP model was trained on 256 V100 GPUs for two weeks. For an on-demand training on AWS Sagemaker, this would cost at least 200k dollars!
🍀 The model uses a minibatch of 32,768 images for training.
📣📣Daft :
A fast, ergonomic and scalable open-source dataframe library: built for Python and Complex Data/Machine Learning workloads.
🫥Install
pip install getdaft.
🫥Why Daft ?
Processing Complex Data such as images/audio/pointclouds often requires accelerated compute for geometric or machine learning algorithms.
🫥Official Link
https://getdaft.io/
A fast, ergonomic and scalable open-source dataframe library: built for Python and Complex Data/Machine Learning workloads.
🫥Install
pip install getdaft.
🫥Why Daft ?
Processing Complex Data such as images/audio/pointclouds often requires accelerated compute for geometric or machine learning algorithms.
🫥Official Link
https://getdaft.io/
📣📣Tesla AI day updates
- Optimus bot revealed
- Dojo supercomputer
- Self-driving architecture upgrades
🫥 They introduced a prototype of their humanoid robot - Optimus. Only a concept last year - and now a reality. The progress was incredibly fast!
🫥 Optimus Specs
•Mass: 73kg
•Battery: Full day of work (2.3 kWh)
•Leveraging autopilot hardware & software
•Processing vision data
•Split-second decisions (multi-sensory inputs)
•Wireless connectivity & audio support (communication)
•Hardware security features
•Cost: ~$20K
🫥 Using language models to predict lanes is quite exciting!
- Optimus bot revealed
- Dojo supercomputer
- Self-driving architecture upgrades
🫥 They introduced a prototype of their humanoid robot - Optimus. Only a concept last year - and now a reality. The progress was incredibly fast!
🫥 Optimus Specs
•Mass: 73kg
•Battery: Full day of work (2.3 kWh)
•Leveraging autopilot hardware & software
•Processing vision data
•Split-second decisions (multi-sensory inputs)
•Wireless connectivity & audio support (communication)
•Hardware security features
•Cost: ~$20K
🫥 Using language models to predict lanes is quite exciting!
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🍀Check out this simple yet amazing application of Natural Language Processing (NLP)! Converting natural language text to a complex regular expression (Regex)!
🍀Definitely the work of a sequence to sequence transformer model behind the scenes, which can help generate a Regex pattern based on a natural language request. Simple and elegant and can help us do pattern matching much faster by getting ready-to-use Regexes.
Link https://www.autoregex.xyz/
🍀Definitely the work of a sequence to sequence transformer model behind the scenes, which can help generate a Regex pattern based on a natural language request. Simple and elegant and can help us do pattern matching much faster by getting ready-to-use Regexes.
Link https://www.autoregex.xyz/
All TensorFlow tools at one place:
🧠 To learn more about all of these amazing TensorFlow tools, check this out
https://www.tensorflow.org/resources/tools
🧠 To learn more about all of these amazing TensorFlow tools, check this out
https://www.tensorflow.org/resources/tools
AI content platform Jasper raises $125M at a $1.7B valuation
Jasper website : https://www.jasper.ai/
Source : https://techcrunch.com/2022/10/18/ai-content-platform-jasper-raises-125m-at-a-1-7b-valuation/
Jasper website : https://www.jasper.ai/
Source : https://techcrunch.com/2022/10/18/ai-content-platform-jasper-raises-125m-at-a-1-7b-valuation/
Skeleton Code for Data Cleaning 🧹
The Factory Method Pattern is one of the most useful design patterns when it comes to data cleaning, feature engineering, and the like.
In most cases, you will have a bunch of feature engineering to do and create functions for each step. Instead of listing them out and running them, you could add them together in a class and interface with the class instead.
The Factory Method Pattern is one of the most useful design patterns when it comes to data cleaning, feature engineering, and the like.
In most cases, you will have a bunch of feature engineering to do and create functions for each step. Instead of listing them out and running them, you could add them together in a class and interface with the class instead.
🔑🫥 From 11th October, Amazon EC2 offers an automated connection set-up solution between EC2 instance and RDS Database.
If done manually, establishing a connection between your application and database requires tasks such as setting up a VPC, security groups, and ingress/egress rules
Link : https://aws.amazon.com/about-aws/whats-new/2022/10/amazon-ec2-automated-connection-solution-ec2-instance-rds-database/
If done manually, establishing a connection between your application and database requires tasks such as setting up a VPC, security groups, and ingress/egress rules
Link : https://aws.amazon.com/about-aws/whats-new/2022/10/amazon-ec2-automated-connection-solution-ec2-instance-rds-database/
IDA LIB (Image Data Augmentation Library) is a Python library to optimize the task of Image Data Augmentation. This tool allows you to convert your input data into a larger and more diverse one in an efficient, fast and easy way.
Ida Lib allows a wide variety of operations to be performed in order to provide the greatest possible diversity to the input dataset.
The library is optimized to perform operations in the most efficient way possible, thus reducing the overload on other processes (such as the training process of a neural network). In addition, it allows the joint transformation of different types and combinations of data types in a flexible and correct way, including the processing of:
• Images
• Point's coordinates
• Masks
• Segmentation maps
• Heatmaps
Ida Lib allows a wide variety of operations to be performed in order to provide the greatest possible diversity to the input dataset.
The library is optimized to perform operations in the most efficient way possible, thus reducing the overload on other processes (such as the training process of a neural network). In addition, it allows the joint transformation of different types and combinations of data types in a flexible and correct way, including the processing of:
• Images
• Point's coordinates
• Masks
• Segmentation maps
• Heatmaps
*** Today announced Amazon Neptune Serverless, a new serverless option for Amazon Neptune that automatically scales to support unpredictable and business-critical graph database workloads. It leads to saving up to 90% compared to the cost of provisioning for peak capacity.
* AI NLP - MLOps
— Open-source framework for data-centric NLP
— Data Labeling + Data Curation + Inference Store
— Designed for MLOps & Feedback Loops
New website: https://www.argilla.io/
New docs: https://docs.argilla.io/
— Open-source framework for data-centric NLP
— Data Labeling + Data Curation + Inference Store
— Designed for MLOps & Feedback Loops
New website: https://www.argilla.io/
New docs: https://docs.argilla.io/