TheSequence Scope: PyTorch 1.5 is Here
Initially published as 'This Week in AI', a newsletter about the AI news, and the latest developments in ML research and technology
From the Editor: PyTorch 1.5 is Here
PyTorch has established itself as one of the top two frameworks for deep learning developments. Initially incubated by Facebook, PyTorch rapidly developed a reputation from being an incredibly flexible framework for rapid experimentation and prototyping gaining thousands of fans within the deep learning community. For instance, AI powerhouse OpenAI announced that it was standardizing on PyTorch as the default framework to power its deep learning research work. Outside Facebook, this is arguably the biggest endorsement for PyTorch within the deep learning world.
This week Facebook announced the release of PyTorch 1.5. The new version focuses on providing tools and frameworks to make PyTorch workflows production-ready. The most notable aspect of this release has been the collaboration between AWS and Facebook in two projects: TorchServe for model serving and Torch-Elastic Kubernetes for distributed training. This release contributes greatly to make PyTorch a more viable option for many enterprises starting in their machine learning journey.
Now let’s take a look at the core developments in AI research and technology this week.
AI Research:
Specification Gaming
DeepMind published an analysis of how reinforcement learning agents can game their target tasks producing undesired outcomes.
>Read more in this blog post from the DeepMind team
Evolutionary Meta-Learning
Google AI researchers published a paper proposing a new meta-learning method based on evolutionary strategies.
>Read more in this blog post from Google AI
Quant-Noise
Facebook AI researchers published a paper introducing Quant-Noise, a new method for compressing neural networks without affecting their performance.
>Read more in this blog post from Facebook Research
Cool AI Tech Releases:
PyTorch 1.5
Facebook released PyTorch 1.5 which includes several projects like TorchServe and TorchElastic that are based on the collaboration between Facebook and AWS.
>Read more in this blog post from the PyTorch team
TensorFlow Profiler
Google open-sourced the TensorFlow profiler, a new set of tools that you can use to measure the training performance and resource consumption of TensorFlow models.
>Read more in a blog post from the TensorFlow team
Apache SINGA 3.0
Apache SINGA is one of the most popular deep learning projects incubated in Asia. The distributed deep learning library just released version 3.0.
>Read more in this announcement from the SINGA team
AI in the Real World:
Greener AI
Researchers from MIT unveiled a method that can reduce the carbon footprint used to train and operate AI models.
>Read more in this coverage from MIT News
CometML’s New Funding Round
CometML is one of our favorite platforms for machine learning management and they just raised a new round of funding.
>Read more in this coverage from TechCrunch
Peak AI Raises $12 Million
Enterprise AI startup Peak AI announced a new $12 million funding round to help enterprises adopt AI solutions.
>Read more in this coverage from VentureBeat
“This Week in AI” is a newsletter curated by industry insiders and the Invector Labs team, every week it brings you the latest developments in AI research and technology.
From July 14th the newsletter will change its name and format to develop ideas of systematic AI education.
To stay up-to-date and know more about TheSequence, please consider to ➡️