AI Newsletter #86 - Record label drops AI-created rapper following ‘gross stereotypes’ backlash

Welcome to Nural's newsletter focusing on how AI is being used to tackle global grand challenges.

Packed inside we have

  • Capitol Records drops its artificial-intelligence-created rapper after just one week following ‘gross stereotypes’ backlash
  • DeepMind advancing conservation with AI-based facial recognition of turtles
  • and deep-learning analysis of the success of breast reconstruction in breast cancer patients

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Marcel Hedman


Key Recent Developments


Capitol Records forced to drop its artificial-intelligence-created rapper after just one week following ‘gross stereotypes’ backlash

AI rapper FN Meka dropped by Capitol over racial stereotyping
Capitol Music Group faced a backlash for signing the artificial intelligence musician.

What: "Artist FN Meka became the world’s first augmented-reality music artist to be signed to a major record label [Capitol Records] earlier this month, releasing his first single “Florida Water” on August 12. Meka already has over 500,000 monthly listeners on Spotify and over 10 million followers on TikTok"

However, following the release of new music, FN Meka faced backlash for trivializing elements of black culture including repeated use of the N word and images of the AI generated artist being beaten by police officers, despite the team containing no black members.

Key Takeaway: A repeated theme with AI use is where does liability start? Can you truly treat an AI system as its own entity? It seems increasingly clear that a team must remain accountable for the outputs of any model. Hiding behind the veil of an AI generated entity does not absolve you from the effects created by that system, in a similar way to traditional software.


DeepMind advancing conservation with AI-based facial recognition of turtles

Advancing conservation with AI-based facial recognition of turtles
We came across Zindi – a dedicated partner with complementary goals – who are the largest community of African data scientists and host competitions that focus on solving Africa’s most pressing problems. Our Science team’s Diversity, Equity, and Inclusion (DE&I) team worked with Zindi to identify a…

What: AI has demonstrated strong value in wildlife conservation efforts and often focuses on using audio based tracking to identify wild animals. In this vein, DeepMind have recently partnered with Zindi, the largest community of African data scientists. They launched a competition to identify turtles using their unique scale patterns as opposed to a traditional tag technique. Traditional tags face erosion and often fall into the ocean and so a facial recognition based technique offers safety and climate benefits.

Key Takeaways: Tracking of turtles is particularly important as they are known as an indicator species. These are classes of organisms whose behaviour helps scientists understand the underlying welfare of their ecosystem.

The success of this project has immediate implications for ecosystem monitoring and is a great example of cross-border collaboration, with submissions received from 13 different African nations.


Feasibility of anomaly score detected with deep learning in irradiated breast cancer patients with reconstruction

Feasibility of anomaly score detected with deep learning in irradiated breast cancer patients with reconstruction - npj Digital Medicine
npj Digital Medicine - Feasibility of anomaly score detected with deep learning in irradiated breast cancer patients with reconstruction

What: For cancer patients, breast reconstruction is widely used following a mastectomy due to both health benefits, which can come from early detection of any further cancer, alongside the increased quality of life and mental wellbeing.

However, patients often require radiation therapy following treatment which often leads to capsular contracture or deformity of the reconstructed breast. Therefore, researchers have implemented a deep learning GAN algorithm to evaluate the link between abnormalities following surgery and any further links to clinical factors.

Key Takeaways: This machine learning based approach offers reduced discomfort for patients compared to existing methods and can lead to increased learnings due to the continuous and longitudinal nature of tracking that can be done through time.


AI Ethics

🚀 Undeclared pools in France uncovered by AI technology

🚀 Assessment of Apple Watch Series 6 pulse oximetry and electrocardiograms in a pediatric population [paper]

🚀 California winemakers are using A.I. to combat climate change challenges

🚀 An artificial intelligence system trained on words and sentences alone will never approximate human understanding.

Other interesting reads

🚀 Google begins rolling out its AI Test Kitchen machine learning app

🚀 Deploy a Language AI App startup idea Easily with Cohere and Streamlit

🚀 Why You Should Use Pre-Trained Models Versus Building Your Own

🚀 Audio-Visual Segmentation: Segmenting images to the corresponding sounds generated [paper]


Cool companies found this week

Metaverse

Ready Player Me - Cross-game Avatar Platform for the Metaverse who have recently raised $60m in series B funding.

Climate

Luma chain - Computer vision based tracking for the meat industry supply chain.


and Finally

Extract from Audio-Visual segmentation paper

AI/ML must knows

Foundation Models - any model trained on broad data at scale that can be fine-tuned to a wide range of downstream tasks. Examples include BERT and GPT-3. (See also Transfer Learning)
Few shot learning - Supervised learning using only a small dataset to master the task.
Transfer Learning - Reusing parts or all of a model designed for one task on a new task with the aim of reducing training time and improving performance.
Generative adversarial network - Generative models that create new data instances that resemble your training data. They can be used to generate fake images.
Deep Learning - Deep learning is a form of machine learning based on artificial neural networks.

Best,

Marcel Hedman
Nural Research Founder
www.nural.cc

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