Data Science Insider: March 4th, 2022

In This Week’s SuperDataScience Newsletter: Satellite Data Firm Asks for War Images to Help Ukraine. Graphcore Announces Supercomputer That’s Faster than a Brain. Researchers Build Neural Networks with Actual Neurons. Scheme Using AI Could Transform Cervical Cancer Screening. AI Model Can Detect Mental Health Conditions from Reddit Posts. 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. --------------------------------------------------------------- [Satellite Data Firm Asks for War Images to Help Ukraine]( brief: The Ukraine-based satellite data company EOS Data Analytics (EOSDA) has asked firms and space agencies which collect satellite imagery for data on Ukraine and Eastern Europe. In its plea, the company said that it will put data suppliers in touch with Ukraine's deputy prime minister Mykhailo Fedorov. Max Polyakov, the founder of EOSDA, said it would provide "actionable intelligence" to those actively resisting the Russian invasion. His request for "recent and real-time high-to-medium resolution optical and radar satellite imagery" is to assist in both military and humanitarian efforts in the region. SAR (Synthetic Aperture Radar) bounces microwave radar signals off the Earth's surface to detect physical properties and is one of two main types of satellite imagery. It can be used to capture and track small-scale movements on the surface of the Earth - so it would be able to detect troop movements. Optical imagery is also being asked for. Why this is important: In a statement, Polyakov said that "The economic, political, and humanitarian consequences of the war in Ukraine are already too high to stand on the sidelines". Data scientists working in this field who have these types of imagery may wish to come forward and offer assistance. [Click here to sign up!]( [Graphcore's Supercomputer to be Faster than a Brain]( brief: We may now be close to realising a long-time goal for the tech industry: building a supercomputer as powerful as the human brain. The UK AI-chip designer Graphcore has announced plans for an ultra-intelligent AI computer that could surpass the parameters of the human brain. The new computer is based on a recent breakthrough in AI chip technology and should be able to support AI with up to 500 trillion parameters, as well as calculate at more than 10 exaflops (10^19) calculations per second. It has been estimated that the human brain calculates at 1 exaflop. Named after Jack Good, an early computer pioneer who worked on developing the world’s first electronic computer, Colossus, Graphcore's computer is called the Good Computer. It has been announced the computer will be ready in two years and cost $120m, making it reasonably accessible for individual companies and universities. Why this is important: The computer uses a new type of silicon processor that Graphcore has developed with aims to overtake its rival, Nvidia. US-based Nvidia currently dominates the market for AI chips, but challengers like Graphcore, Cerebras, and SambaNova have emerged with chips specifically designed for AI calculations. [Click here to read on!]( [Researchers Build Neural Networks with Actual Neurons]( In brief: Cortical Labs has published research outlining a potentially revolutionary approach to neural networks (NN). Instead of relying solely on silicon, they are growing real biological neurons on electrode arrays, allowing them to be interfaced with digital systems. Their latest results have shown promise that these real biological neural networks can be made to learn. The team behind the project is investigating NN grown from both mouse and human cells, plated onto a high-density multielectrode array from Maxwell Biosystems. Once deposited and properly cultured in the lab, the cells formed what are called “densely-interconnected dendritic networks” across the surface of the electrode array. These could then be stimulated electronically and the responses of the neurons read back in turn. The final result was a system nicknamed DishBrain, which was put to the test in a simulated game environment reminiscent of the game Pong. Why this is important: The broad aim of the Australia-based Cortical Labs project is to harness biological neurons for their computational power in an attempt to create “synthetic biological intelligence”. The basic idea is that biological neurons are far more complex and capable than any neural networks simulated in software. So if we wish to create a viable intelligence from scratch, it makes more sense to use biological neurons rather than mess about with human-created simulations. [Click here to discover more!]( [Scheme Using AI Could Transform Cervical Cancer Screening]( In brief: A hospital is piloting technology using AI and advanced imaging to improve the early diagnosis of cervical cancer. Spokespeople from the University Hospital Monklands in Scotland claim it has become one of the first hospitals in the world to pilot the technology as part of their cervical screening programme. The pilot is using a digital cytology system called the GeniusTM Digital Diagnostics System, created by women’s health company Hologic. For the pilot programme, the system will create digital images of cervical smear slides from samples that have tested positive for Human Papilloma Virus (HPV). These images of test slides can then be rapidly reviewed using an advanced algorithm assessing cervical cells in the sample and providing the screener with an image gallery of the most diagnostically relevant cells. This can help medical experts diagnose and identify abnormalities more rapidly and accurately since they have fewer cells to analyse. Why this is important: Health experts say the new technology could be critical in ensuring early detection of pre-cancerous cells and cancer cells, potentially saving numerous lives. [Click here to see the full picture!]( [AI Model Can Detect Mental Health Conditions from Reddit Posts]( In brief: Scientists from Dartmouth College in Hanover, New Hampshire, have reportedly developed an AI model that can detect the mental health of a user by analysing their conversations on the social platform Reddit. Part of an emerging wave of screening tools that use computers to analyse social media posts and gain insight into people's mental states, the team selected Reddit to train their model as it has over 500 million active users, all regularly discussing a wide range of topics over a whole network of subreddits. They focused on looking for emotional intent, rather than at the actual content of the post, and found it performs better over time at discovering mental health issues. Previous studies searching for evidence of mental health conditions in social media posts have usually looked at the content, rather than intent. Why this is important: This sort of technology could one day be used to help in the diagnosis of mental health conditions or be put to use in moderating content on social media. [Click here to find out more!]( [Super Data Science podcast]( this week's [Super Data Science Podcast](, we are joined by Dr. Josh Starmer, the creative, musical genius behind the wildly popular YouTube channel StatQuest. Together, we're talking statistics, learning and communication secrets, and how he grew his YouTube channel to over 650,000 subscribers – take notes! --------------------------------------------------------------- What is the Data Science Insider? 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