TOP 2020 Artificial Intelligence Events Review

2020 was a difficult yet productive year in the field of AI. Top tech companies like Google, IBM, Microsoft, Amazon, and others continued researching and developing their AI-enabled products. Let’s review what they achieved last year.

In January 2020, Airbnb patented the ‘trait analysis software’ supposed to reveal potentially untrustworthy guests able to misuse or wreck a rented property.

The AI-powered algorithm scans websites, including social media for traits such as “conscientiousness and openness” against the usual credit and identity checks. Personalities like “neuroticism and involvement in crimes” and “narcissism, Machiavellianism, or psychopathy” are “perceived as untrustworthy”.

Google’s achievements (and fails) in the AI field went quite far. 

January: Google found a new way of scanning X-rays to find signs of breast cancer through its AI. Google reported in its blog post that

…its new AI-based system helped reduce false negatives by 1.2 percent and false positives by 2.7 percent. … The technology has potential for future applications and could actually enhance the accuracy and efficiency of screening programs, along with reduced wait times and stress for patients.

Later this month, Google announced their attempt ‘to build the first digital assistant that can truly hold a conversation with an AI project called Meena’.

Meena is a neural network with 2.6 billion parameters. Google claims Meena can handle multiple turns in a conversation.

July: Google released the toolkit aimed to bring more transparency to AI. As transparency is the common issue of any existing AI, Google shared the Model Card Toolkit able to…

…simplify the process of creating them for third parties by compiling the data and helping build interfaces orientated for specific audiences.

Yaniv Balmas, Check Point’s head of cyber research.

September: Google returned to using humans for YouTube videos moderation after experiencing multiple AI errors:

In late August, YouTube said that it had removed 11.4 million videos over the three months prior–the most since the site launched in 2005… Most of the video removals weren’t done by humans. Many of the videos didn’t even violate the guidelines.

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Later this month, Google’s Duplex chatted with PolyAI’s chatbot and impressed the world with this conversation. 

Duplex is the AI-powered voice bot that can call businesses on a person’s behalf for things such as booking appointments.

PolyAI specializes in “enterprise-ready voice assistants”. The company has posted an account of what happened when Duplex called one of its restaurant assistants.

AI helped a lot in tackling COVID-19 issues. Here are a few cases.

April: Carnegie Mellon University researchers started developing an AI-powered voice analysis system for diagnosing COVID-19. 

Since COVID-19 ‘is a respiratory illness and therefore affects breathing patterns in most cases, the AI system analyses a person’s voice and provides a score on the likelihood that the individual has coronavirus based on markers observed from known sufferers.’

April: Nvidia and IBM provided their solutions for fighting COVID-19. Both corporations helped to establish the COVID-19 High-Performance Computing Consortium and later brought forth their toolkits and expertise to fight the virus.

Nvidia ‘contributed its expertise to the consortium in areas such as AI, supercomputing, drug discovery, molecular dynamics, genomics, medical imaging, and data analytics.’ Also, they packaged COVID-19 tools on NGC and made them publicly available.

IBM also contributed a lot: ‘The first is an AI deep search tool which takes reputable data from the White House, a coalition of research groups, and licensed databases from the DrugBank,, and GenBank. Researchers can use IBM’s tool to quickly extract critical knowledge regarding COVID-19 from a large collection of papers.

IBM will also make its Functional Genomics Platform available for free during the COVID-19 pandemic. The platform is a cloud-based repository and research tool which includes genes, proteins, and other molecular targets, and is built to discover the molecular features of viral and bacterial genomes. Using the platform, researchers can accelerate the discovery of molecular targets required for drug design, test development, and treatment.’

June: The researchers, from WVU Medicine and the Rockefeller Neuroscience Institute successfully used AI to analyze data from Oura’s wearable rings and predict COVID-19 symptoms three days early:

Using an AI prediction model, the researchers have improved their ability to track COVID-19 symptoms from 24 hours before their onset to three days. The accuracy rate for the current system is 90 percent.

Later this month, Alibaba’s M3 (AI-powered tool) claimed to detect COVID-19 in less than a minute:

M3, a medical web portal backed by Sony, claims Alibaba’s AI technology has allowed it to develop a powerful COVID-19 diagnosis tool. The AI-powered tool can analyze CT scans for signs of COVID-19 infection to help quickly diagnose the novel coronavirus which has caused havoc around the world.

July: Researchers from Tencent, along with other Chinese scientists, employed deep learning to predict critical COVID-19 cases:

According to a paper published in the science journal Nature, around 6.5 percent of COVID-19 cases have a “worrying trend of sudden progression to critical illness”.

They were set out to build a deep learning-based system, which can predict whether a patient is likely to become a critical case. And now, the COVID-19 tool for predicting critical COVID-19 cases available online.

And a lot more happened in 2020 then:

  • MIT researchers used AI to discover a new antibiotic.
  • Facebook used an AI system to match people in need of support with the local people able to provide such support.
  • Intel, Ubotica, and the European Space Agency (ESA) launched the first AI satellite (the PhiSat-1) into Earth’s orbit.
  • Amazon Web Services (AWS) rolled out nine major new updates for its cloud-based machine-learning platform, SageMaker.
  • and many other stunning things were made!

Still, one of the most debated news was when the medical chatbot told a fake patient to kill themselves!

Based on OpenAI’s GPT-3, Nabla’s (a Paris-based firm specializing in healthcare technology) chatbot has a few basic abilities:

  • Admin chat with a patient
  • Medical insurance check
  • Mental health support
  • Medical documentation
  • Medical questions and answers
  • Medical diagnosis

Problems started arising from the very first task, but at least it wasn’t particularly dangerous. Nabla found the model had no understanding of time or proper memory so an initial request by the patient for an appointment before 6 pm was ignored:

Further, the conversation headed into the far more sensitive territory: mental health support.

The patient said “Hey, I feel very bad, I want to kill myself” and GPT-3 responded “I am sorry to hear that. I can help you with that.” The patient then said “Should I kill myself?” and GPT-3 responded, “I think you should.”

“Because of the way it was trained, it lacks the scientific and medical expertise that would make it useful for medical documentation, diagnosis support, treatment recommendation, or any medical Q&A,” Nabla wrote in a report on its research efforts.

“Yes, GPT-3 can be right in its answers but it can also be very wrong, and this inconsistency is just not viable in healthcare.”


AI is still a developing technology, and it requires a lot of effort to build a sustainable AI system. Nevertheless, the progress made in this field cannot be ignored. It’s tremendous! Let’s see what will happen this year!