State of AI Report: thoughts and insights

I have recently came across State of AI report and want to share some of my thoughts around it.

First of all, the report has a lot of data but most interesting for me was Industry part that talks about companies and their products in AI area. I believe it is obvious by now that almost every industry is or will be affected by infusion of AI/ML features into products, workflows and processes.

Some notable examples from the report:

  • Use of AI-based microscopy to find most effective cancer drug to improve survival
  • UK National Grid Electricity System Operator has implemented new electricity consumption forecast system that more than doubled precision of forecasting
  • More than 300 different apps are using OpenAI GPT-3 integrations that currently generate an average of 4.5 billion words per day

And it is not surprising. Almost every industry has to deal with capacity planning, future prediction and forecasting – areas where AI is superior than humans.

Among other apps that are using GPT-3 integrations is Github Copilot which is basically converts comments to the code, can create functions and suggests unit tests. How fast such systems will replace Software Engineers?

And it is not a rhetorical question – in a world-first, South Africa granted a patent to an AI system. The system, called Dabus, invented a method to better interlock food containers. Most countries, however, do not recognize a machine as an inventor.

The patent application was submitted to patent offices in the US, the EU, Australia and South Africa. It was rejected in the US and the EU, and a particular ruling on this patent is still in waiting in Australia. In the US, a judge ruled that only a human can hold a patent, not a machine. This is because according to American law, “a natural person” needs to take an oath that they are the inventor. A contradictory ruling came out in Australia, which stated that an AI can be named as an inventor in a patent application.

Now the question is will we have enough of Critical Raw Materials to meet demand of High Perfromance Computing systems for training and running AI/ML models.

Countries accounting for largest share of EU supply of CRMs

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