Data Science Insider: October 21st, 2022

In This Week’s SuperDataScience Newsletter: Adobe Reveals AI Prototype. Google Allows Smartphone Access to ‘Sentient’ LaMDA AI. Meta Develops an AI for Real-Time Translation of Hokkien. Mechanical Neural Network Developed. A Profile of Demis Hassabis. 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. --------------------------------------------------------------- [Adobe Reveals AI Prototype]( brief: Adobe has used the opening keynote of their virtual conference, Adobe MAX 2022, to heavily promote their latest advancements in AI. The company took the opportunity to announce a batch of new features that will launch across its entire product suite, the vast majority of which involved the Adobe Sensei ML engine. Key announcements include Project Motion Mix - a tool that converts a still photograph into a dancing animation using ML, photo restoration, and background replacement tools for Photoshop and, perhaps most eye-catching, the prototype for an AI feature called “Project Clever Composites” that will automatically blend different photos into one convincing animated composite with the press of a single button. The tool was shown as part of Adobe “Sneaks,” Research and Development projects which are being trialled with the hope that they may one day find their way into commercial products. Why this is important: Adobe has a long history of providing software for the creation and publication of a wide range of content, including graphics, photography, illustration, animation, multimedia/video, motion pictures, and print, but it has perhaps fallen by the wayside when it comes to advances in AI. This year's AI focus serves to big up the company’s latest features and frames them as one to watch in the future. [Click here to learn more!]( [Google Allows Phone Access to ‘Sentient’ LaMDA AI]( brief: Google has launched its new ‘AI Test Kitchen’ in the UK, an app that lets users experiment with Language Model for Dialogue Applications (or LaMDA) and give feedback on their experiences, but only as part of an extremely limited trial. The technology, which is used to power chatbots, is being launched with three scenarios for users to choose from, and then give feedback on. These scenarios are: ‘Imagine It’ which lets you name a place and offers paths to explore your imagination, ‘List It,’ where you tell LaMDA a goal or topic which it breaks down into a list of subtasks, and ‘Talk About It (Dogs Edition)’ which enables to have a fun, open-ended conversation about dogs and only dogs, exploring LaMDA’s ability to stay on topic. In this BBC article, you can discover what their technology editor thought of the app. Why this is important: LamDA has had a controversial path to this roll-out which we covered here at SuperDataScience back in June when former Google software engineer Blake Lemoine claimed that the AI system showed signs of sentience. [Click here to read on!]( [Meta Develops Real-Time Translation of Hokkien]( In brief: Meta has announced that their Universal Speech Translator (UST) project has developed an AI-powered speech-to-speech translation system for unwritten languages, specifically a translation system for Hokkien, a primarily oral language of the Chinese diaspora which is spoken by approximately 49 million people in countries like China, Taiwan, Singapore, Malaysia, and the Philippines but lacks a standard written form. In a press release, Meta said they: “developed a variety of methods, such as using speech-to-unit translation to translate input speech to a sequence of acoustic sounds, and generated waveforms from them or rely on text from a related language, in this case, Mandarin.” Meta Founder and CEO Mark Zuckerberg has long advocated for the use of AI in translation systems, claiming: “The ability to communicate with anyone in any language — that’s a superpower people have dreamed of forever, and AI is going to deliver that within our lifetimes.” Why this is important: The AI can currently only translate one full sentence at a time but it highlights the future potential for the technology. [Click here to discover more!]( [Mechanical Neural Network Developed]( In brief: Researchers from the University of California at Los Angeles (UCLA) and the University of Twente announced the development of an adaptive material that is capable of actively responding to changing conditions and learning. The researchers have called the material a "mechanical neural network" and it has the potential to be used in a variety of industries, such as; construction, aerospace, and imaging technologies. The material is made up of a structural system constructed from ‘tuneable beams’ which can alter their shape and behaviours in response to dynamic conditions. It is this geometry and specific traits of its design that grant the material its properties rather than what it is made out of and its architecture is based on that of an artificial neural network. The researchers have currently developed a prototype of the lattice material, which has been shown to adapt to changing or unknown conditions. Why this is important: The 2D lattices are still at a very early stage and may take some time to bring any wider effects. However, “the same foundational principles that are used in machine learning are used to give this material its smart and adaptive properties,” which could mean great things for the future. [Click here to see the full picture!]( [A Profile of Demis Hassabis]( In brief: Vox has revealed its list of ‘Future Perfect 50’ who are individuals whom it claims are “building a more perfect future.” The collection includes scientists, thinkers, scholars, writers, and activists. One of this year’s honoured recipients is the British-born gamer and DeepMind’s chief executive officer and co-founder, Demis Hassabis. In this article, he is profiled and referred to as “AI’s grandmaster.” Vox claims that he is one of the most important people working today as it cites his work on AlpaFold: “The recent progress in AI has been astounding, but we have yet to see the application that could do truly meaningful work faster and better than human beings can. AlphaFold, which promises to put a jetpack on some of the most vital work in biology and speed the pace of desperately needed research, promises to be just that. Hassabis clearly agrees.” Why this is important: Hassabis has been responsible for a staggering number of developments and breakthroughs which have changed the field of AI. This profile offers a fascinating insight into his life and work. [Click here to find out more!]( [Super Data Science podcast]( this week's [Super Data Science Podcast](, Jon speaks with Erik Bernhardsson, the man who invented Spotify’s original music recommendation system. They address the different ways to interview a data science candidate, how to deploy a data model into the cloud, and the approach he took that made Spotify go from a digital music startup to an AI-driven streaming giant. --------------------------------------------------------------- What is the Data Science Insider? 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