Welcome to our October 2021 monthly digest where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. In this edition we cover our latest focus issue, the concept of foundation models, 100 days of machine learning, Beethoven's 10th symphony, and more. Our latest focus series life on land (as part of our wider series on the UN sustainable development goals) was launched this month. We spoke to Lily Xu about her work in green security. Lily and her colleagues apply machine learning and game theory techniques to wildlife conservation.

Google has activated a safety feature that lets minors under 18 request that images of themselves be removed from search results, The Verge has reported. Google first announced the option back in August as part of a slate of new safety measures for kids, but it's now rolling out widely to users. Google said it will remove any images of minors "with the exception of case of compelling public interest or newsworthiness." The requests can be made by minors, their parents, guardians or other legal representatives. To do so, you'll need to supply the URLs you want removed, the name and age of the minor and the name of the person acting on their behalf.

As a result, you may send a photo to a deep neural network that has been trained to recognise dogs and cats and get an output that tells you whether the photo contains a dog or a cat. The network outputs the chance of the photo containing a dog or a cat (the two classes you trained it to identify) and the output sums to 100 per cent if the last network layer is a softmax layer. You get scores that you can interpret as probabilities of content belonging to each class, independently, when the last layer is a sigmoid-activated layer. The scores will not always add up to 100 per cent. Because its architecture outputs the entire image as being of a given class, a simple CNN can't duplicate the instances below.

First algorithm that anyone learned in machine learning was Linear Regression, an algorithm that was trying to fit "straight" line in the data.But that's not the case in practical life.

Music artists, composers and producers today swim in massive amounts of musical notes to test the barriers of what melodies, harmonies and symphonies they can create and what works best with their songs. Although the advances in technology have significantly simplified and streamlined the process, it is still a long and challenging one for everyone involved in music creation. However, a technological revolution may be about to chance music creation as we know it. A team of computer scientists were able to use AI to complete the unfinished 10th symphony, originally created over 250 years ago by Ludwig Van Beethoven. This project has provoked interesting discussions, such as whether the now completed symphony is what Beethoven was originally trying to create, and also raised the important question -- what can Artificial Intelligence (AI) and Machine learning (ML) do for music production in the music entertainment industry? The team at Brainpool have been pondering on the answer to the latter, so we took the time to test a few of the various readily available AI music demos and reflected on how they could help transform the music industry.

Artificial intelligence will be playing a big part in your online shopping escapades for the holidays. That's because roughly 81% of online retailers are tapping AI to boost their sales in time for the holiday rush. According to VentureBeat, these businesses have increased their artificial intelligence budgets to do just that. The businesses in question are classified as small to medium enterprises who might not be competitive with other online shopping giants like Amazon. With artificial intelligence, the businesses are tapping into its power to help manage their supply chain (which is already stretched thin due to the pandemic), protect against ecommerce fraud, and even increase their overall sales.

Are we ready to take to the skies without a human pilot? With advances in AI and data science, it is now conceivable to travel in self-driving automobiles. It is still too early to say "yes" to flying without a human pilot, but it may be achievable in the future. Before air travel becomes completely pilotless, years of certification and testing will be required. The good news is that airlines do use data science and machine learning to automate or speed up operations.

On October 14, 2021, the U.S. Food and Drug Administration ("FDA" or the "Agency") held a virtual workshop entitled, Transparency of Artificial Intelligence ("AI")/Machine Learning ("ML")-enabled Medical Devices. The workshop builds upon previous Agency efforts in the AI/ML space. Back in 2019, FDA issued a discussion paper and request for feedback called, Proposed Regulatory Framework for Modifications to AI/ML-Based Software as a Medical Device ("SaMD"). To support continued framework development and to increase collaboration and innovation between key stakeholders and specialists, FDA created the Digital Health Center of Excellence in 2020. And, in January 2021, FDA published an AI/ML Action Plan, based, in part, on stakeholder feedback to the 2019 discussion paper.

When customers in the London borough of Hackney shop in the new Amazon Fresh store, they no longer pay a checkout operator but simply walk out with their goods. Amazon describes "just walk out shopping" as an effortless consumer experience. The rise of automated stores during the pandemic is just the tip of the iceberg. Floor-cleaning robots have been introduced in hospitals, supermarkets and schools. Fast-food restaurants are employing burger-grilling robots and chatbots.

As the health and safety of our candidates and our employees come first, we're excited to provide virtual experiences for interviews and new hire on-boarding. Dataminr puts real-time AI and public data to work for our clients, generating relevant and actionable alerts for global corporations, public sector agencies, newsrooms, and NGOs. Our real-time alerts enable tens of thousands of users at hundreds of public and private sector organizations to learn first of breaking events around the world, develop effective risk mitigation strategies, and respond with confidence as crises unfold. Dataminr is making its mark for growth and innovation, recently earning recognition on the Deloitte Technology Fast 500, Forbes AI 50 and Forbes Cloud 100 lists. We also earned accolades for'Most Innovative Use of AI' from the 2020 AI & Machine Learning Awards.