Welcome to Nural's newsletter where we explore how AI is being used to tackle global grand challenges.
As always in the newsletter you will find a compilation of articles, news and cool companies all focusing on using AI to tackle global grand challenges.
Packed inside we have
- Autonomous robots seeming to have killed in war without human intervention
- Deepfake maps and how it affects our trust in satellite map data
- Google researchers using language models to bring in a whole new type of search engine
- and more...
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Key Recent Developments
Have autonomous robots started killing in war without human intervention?
What: "Over the past week, a number of publications tentatively declared, based on a UN report from the Libyan civil war, that killer robots may have hunted down humans autonomously for the first time." In reality, it is a lot less clear cut and determined than it seems...
Key Takeaway: It's important to note that "autonomous weapons as a concept are not all that new. Landmines are essentially simple autonomous weapons — you step on them and they blow up." However, the introduction of AI into this mix does pose new challenges. Should an AI system have the power to take a life without human intervention?
Transitioning to Tesla Vision - Removing radar from self driving cars
What: Tesla announced their Model 3 and Model Y car lines will remove radar and transition to completely relying on computer vision when driving autonomously. This represents a move other car manufacturers have not made with most using a combination of radar, lidar and computer vision.
Key Takeaway: This move by Tesla represents a huge confirmation of the level that computer vision has reached. However, dropping the use of radar in these autonomous vehicles raises serious questions regarding safety especially as computer vision has notoriously failed in unique edge cases in the past.
1.4 petabyte database of a small sample of human brain tissue
What: 'Google in collaboration with the Lichtman Laboratory at Harvard University, have released the “H01” dataset, a 1.4 petabyte rendering of a small sample of human brain tissue, along with a companion paper, “A connectomic study of a petascale fragment of human cerebral cortex.”'
Key Takeaway: This large scale dataset has profound implications on the future of machine learning work on studying the human brain. It is also another example of large innovation in this field coming from the major tech companies. They seem to be the only players with the resources to bring about this scale of innovation...
Other interesting reads
🚀 Language models like GPT-3 could herald a new type of search engine (Google Researchers)
Cool companies I have come across this week
Molecule One - AI powered drug feasibility screening/ drug discovery.
Orora - Wildfire detection and monitoring from space.
AI/ML must knows
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.
Tensorflow/keras/pytorch - Widely used machine learning frameworks
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.
Nural Research Founder
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