Machine Learning Up to Date #15
Here's ML UTD #15 from the LifeWithData blog! We help you separate the signal from the noise in today's hectic front lines of software engineering and machine learning.
LifeWithData strives to deliver curated machine learning & software engineering updates that point the reader to key developments without superfluous details. This enables frequent, concise updates across the industry without information overload.
Application
- Face-mask Recognition Has Arrived — For Better or Worse
- Apache Arrow: the Hidden Champion of Data Analytics
- Google Claims its AI is Better at Recognizing Breaking News and Misinformation
Theory
Face-mask Recognition Has Arrived — For Better or Worse ☝
Public shaming over not wearing a face mask started almost as soon as the COVID-19 pandemic itself. In February, some provinces and municipalities in China made it mandatory to wear masks when in public. News reports soon followed of residents and police chastising the non-compliant, a trend that’s now seen globally.
... keep reading
Apache Arrow: the Hidden Champion of Data Analytics ☝
In today’s open-source software stack you can find many indispensable dependencies in the form of software libraries. They are logging frameworks, testing frameworks, HTTP libraries, or code style checkers. But it doesn’t happen often that a new library emerges which changes the way we think about computing.
... keep reading
The Rundown
Google Claims its AI is Better at Recognizing Breaking News and Misinformation ☝
Google [says](https://blog.google/products/search/our-latest-investments-information-quality-search-and-news) it’s using AI and machine learning techniques to more quickly detect breaking news around crises like natural disasters. That’s according to Pandu Nayak, vice president of search at Google, who revealed that the company’s systems now take minutes to recognize breaking news as opposed to 40 minutes a few years ago.
... keep reading
The Rundown
The Generative Age ☝
AI can already create photorealistic [faces](https://thispersondoesnotexist.com/), [objects](https://www.cc.gatech.edu/~hays/7476/projects/Cusuh/), and [landscapes.](https://techcrunch.com/2019/03/18/nvidia-ai-turns-sketches-into-photorealistic-landscapes-in-seconds/) [Video](https://venturebeat.com/2019/07/19/deepminds-ai-learns-to-generate-realistic-videos-by-watching-youtube-clips/) [isn’t](https://venturebeat.com/2019/06/07/googles-ai-generates-videos-with-unprecedented-complexity/) far behind. We [can](https://www.descript.com/overdub?lyrebird=true) [already](https://www.youtube.com/watch?v=zwYiDraKtSA&feature=emb_logo) [recreate](https://clyp.it/2pb4bp05) [any](https://clyp.it/2pb4bp05) [voice](https://twitter.com/gwern/status/1086010478135050240). GPT-3 can already write [dialogue](https://arr.am/2020/08/11/ai-fan-fiction-or-barry-by-terry-pratchett-gpt-3/) and movie plots almost indistinguishable from ones written by humans. Even [generated music](https://openai.com/blog/jukebox/) is making fast progress. It’s only a matter of time until we’re generating entire movies and shows. It’s startling to realize that Hollywood movies that cost $300M to produce today might be generated for a few cents within our lifetimes.
... keep reading
The Rundown
Looking Inside the Black Box — How to Trick a Neural Network ☝
Neural networks get a bad reputation for being black boxes. And while it certainly takes creativity to understand their decision making, they are really not as opaque as people would have you believe. In this tutorial, I’ll show you how to use backpropagation to change the input as to classify it as whatever you would like.
... keep reading
The Rundown
Aligning AI With Shared Human Values ☝
We show how to assess a language model’s knowledge of basic concepts of morality. We introduce the ETHICS dataset, a new benchmark that spans concepts in justice, well-being, duties, virtues, and commonsense morality. Models predict widespread moral judgments about diverse text scenarios. This requires connecting physical and social world knowledge to value judgements, a capability that may enable us to steer chatbot outputs or eventually regularize open-ended reinforcement learning agents. With the ETHICS dataset, we find that current language models have a promising but incomplete understanding of basic ethical knowledge. Our work shows that progress can be made on machine ethics today, and it provides a steppingstone toward AI that is aligned with human values.
... keep reading
The Rundown