Data Science Insider: June 18th, 2021

In this week’s Super Data Science newsletter: A CIO’s Guide to Building a Data Science Team. Facebook AI Aims to Identify Deepfake Images and Trace Their Creators. China Unleash AI Fighter Jets Capable of Shooting Down Real Pilots. AI Could Halve Law Jobs in 30 Years. Researchers Use DL to Add High-Quality Motion to Still Photos. Cheers, - The SuperDataScience Team P.S. Have friends and colleagues who could benefit from these weekly updates? Send them to [this link]( to subscribe to the Data Science Insider. --------------------------------------------------------------- [A CIO’s Guide to Building a Data Science Team]( brief: This article by eWeek is written by Scott McClellan, Head of Data Science at NVIDIA, and designed for CIOs who may be struggling to understand the value that data analysts, data engineers, data scientists, ML engineers, and DL engineers can bring to their businesses and what makes each role distinct from the other. The article highlights the fact that businesses generally understand that data scientists and AI developers are key to successful growth and are imperative for maintaining an edge in the tech industry. However, it also acknowledges that with an increasing abundance of data to deal with, many companies are struggling to understand what the various experts can bring to their data science teams. As such, the article breaks down each role, explaining what can be expected from a data analyst or engineer whilst maintaining a clear understanding of how the real world may differ from the ideal. Why this is important: Although this article is aimed at CIOs, it would be useful for any early-career data specialist who is looking for a greater understanding of what each role entails and how they fit into a real-world company. [Click here to find out!]( [FB AI to Identify Deepfake Images and Trace Their Creators]( brief: Facebook has developed an AI that it claims can detect deepfake images and even reverse-engineer them to figure out how they were made and perhaps trace their creators. Facebook’s new AI looks at similarities among a collection of deepfakes to see if they have a shared origin, looking for unique patterns such as small speckles of noise or slight oddities in the colour spectrum of an image. By identifying the minor fingerprints in an image, Facebook’s AI is able to discern details of how the neural network that created the image was designed, such as how large the model is or how it was trained. The AI was trained on a database of 100,000 deepfake images generated by 100 different generative models. Some of those images were used to train the model, while others were held back and presented to the model as images of unknown origin. Why this is important: This advancement is a big step forward for fingerprinting but it is worth noting that, for now, the AI only works on images that have been fully artificially generated, while many deepfakes are videos created by pasting one face onto someone else’s body. [Click here to read on!]( [China Unleash AI Fighter Jets Capable of Shooting Down Real Pilots]( In brief: Chinese fighter jets piloted by AI are becoming better than humans and routinely defeat pilots in dogfights, the country's military has claimed. Fang Guoyu, a pilot and aerial combat champion, was recently 'shot down' by one of the craft during a simulated dogfight, according to state-run media. “This is not the first time the renowned Fang was shot down by the AI, and Fang is not the only ace the AI has defeated,” PLA Daily reported. China is in the midst of an overhaul of its military that has seen the country upgrade its tanks, missile systems, troop equipment, and fighter jets. Among the new systems being developed is advanced AI. At the moment, the AI is only being used in training missions - a process which commanders say trains the computers to defeat real-life combatants and forces the pilots to come up with new tactics to beat the machines. Why this is important: As Fang says: 'At first, it was not difficult to win against the AI. But by studying data, each engagement became a chance for it to improve.” [Click here to discover more!]( [AI Could Halve Law Jobs in 30 Years]( In brief: UK Lawyers have predicted that AI will halve the numbers working in law within 30 years. A Law Society of England and Wales report forecasts that lawyers will need to take “performance-enhancing medication” to keep up with machines that will take over work done by junior professionals. “The legal profession is not immune to a savage reduction in full-time employees,” said the report. In models of the structure of the profession over the next 30 years, researchers said that the most “disruptive” predicted that by 2050 there would be 50% fewer jobs. The profession has grown considerably since 1990 but the report predicts that the coronavirus pandemic and technology will reverse that trend. The report notes that the number of private practice firms in England and Wales has fallen by 10% since 2009 to 9,339 in 2019. It also finds that high street firms are most at risk of failing. Why this is important: The report is particularly worrying news for smaller law firms as it predicts that larger firms will fill the gaps left by small firms as they can “fund and scale technology.” This is a trend that reflects what we’ve seen across a wide variety of other industries. [Click here to see the full picture!]( [Using DL to Add High-Quality Motion to Still Photos]( In brief: Researchers at the University of Washington have developed a new DL method that essentially creates high-quality cinemagraphs automatically. The team says the method can animate any flowing material, including water, smoke, fire, and clouds. Estimating motion required the researchers to train a neural network with thousands of videos of waterfalls, rivers, oceans, and other materials with fluid motion. The training process asked the neural network to guess the motion of the video when only given the first frame. The neural network then compared its prediction with the actual video and learned to identify clues, such as ripples in a stream, to help predict what happens next. Researchers created something they call “symmetric splattering” that predicts the future and past for an image, combining them into a single animation. The team has shared several examples of different fluids moving using the new DL algorithm. Why this is important: The current method results in images that have a better expression of motion and reduced perception of when the animation loop, compared to cinemagraphs. However, it does not quite understand how to predict reflections on moving water or how water might distort objects below the surface. These issues, however, are also the same ones that plagued early cinemagraphs. The difference here, however, appears to be a much more believable state of motion of water than can be created with software tools like Flixel. [Click here to find out more!]( [SuperDataScience podcast]( In this week's [SuperDataScience Podcast](, Maureen Teyssier joins to discuss the fascinating work Reonomy does in commercial real estate and her views and tips on building a great data science team. --------------------------------------------------------------- What is the Data Science Insider? 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