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Data Mining: AI-Alerts

Can synthetic data help train your AI model?

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The saying "data is the new oil," was reportedly coined by British mathematician and marketing whiz Clive Humby in 2006. Data is the fuel powering modern AI models; without enough of it the performance of these systems will sputter and fail. And like oil, the resource is scarce and controlled by big businesses. What do you do if you're a small computer vision company? You can turn to fake data to train your models, and if you're lucky it might just work.

The Promise of AI in Gene and Cell Therapy Operations


There is no longer any doubt that artificial intelligence (AI) is advancing biological discovery and biomanufacturing operations. In biological discovery, AI systems such as AlphaFold and the Atomic Rotationally Equivariant Scorer are celebrated for their uncanny ability to predict tertiary structures for proteins and RNA molecules. In biomanufacturing, AI systems usually enjoy less fanfare. Yet they can provide valuable functions such as pattern recognition, real-time assessment of batch quality, multivariable control for continuous manufacturing, prediction/optimization of critical process parameters, and anomaly detection. Such functions are critical to the success of gene and cell therapy operations.

US Tax Agency Drops Facial Recognition Plan After Criticism

International Business Times

The US national tax authority announced Monday that it will stop using facial recognition software to verify taxpayers' identities when they create online accounts, following a chorus of privacy concerns. Internal Revenue Service officials had put forth the authentication system as a security measure following years of growing fears over online scams and identity theft, but the program ended up also prompting worries. The initiative involved identity verification company, which won a nearly $90 million contract to make taxpayers' accounts more secure. The IRS said "it will transition away from using a third-party service for facial recognition to help authenticate people creating new online accounts." "The IRS will quickly develop and bring online an additional authentication process that does not involve facial recognition," it said, as the agency faces staffing shortages and significant backlogs.

Microsoft Steps Up Data Platform and AI Ambitions


Microsoft unveils big-data-capable SQL Server 2019 and extended AI capabilities to power data-driven innovation. Microsoft CEO Satya Nadella set the tone at the September 24-27 Ignite events in Orlando by sharing at least half a dozen stories of leading companies innovating and pioneering new business models with the aid of artificial intelligence (AI). It was a crisp, one-hour presentation long on vision and surprisingly short on promotion or even mentions of the significant technology announcements that followed. Nadella warned the more than 30,000 attendees that the ability to innovate and drive new business models is as much or more about changing corporate cultures and business processes as it is about applying technology. And when the technology decisions are ready to be made, Nadella counselled executives to know which capabilities are commodities and which warrant custom development to drive differentiation.

Zephyr AI Launches its Big Data, Machine-Learning Approach to Aid Precision Medicine


Technology investment company and incubator Red Cell Partners announced today the launch of Zephyr AI, a company that leverages large data sets to inform both clinical care and the development of new targeted precision therapies. The management team of the new company consists of CEO Yisroel Brumer, formerly of the office of the Secretary of Defense; Executive Chairman Grant Verstandig, who most recently served Chief Digital Officer at UnitedHealth Group; and Chief Technology Officer Jeff Sherman, who was the machine learning architect at Rally Health, which was acquired in 2017 by UnitedHealth's Optum unit. According to a press release announcing its launch, Zephyr AI will look to improve patient outcomes while lowering costs by integrating "artificial intelligence with extensive datasets to upend traditional'guess and test' drug development and personalized medicine processes to unearth novel therapeutics, new applications for existing therapeutics, and advanced biomarkers for individualized treatments." The potential new company gave a hint at its direction earlier in the year via the publication of two papers by the founders in the journal Oncogene that detailed the company's technology and it's performance. "These findings demonstrate that Zephyr AI can already identify novel-use cases for existing therapeutics in cancer," company CTO Sherman.

'Dystopian world': Singapore patrol robots stoke fears of surveillance state

The Guardian

Singapore has trialled patrol robots that blast warnings at people engaging in "undesirable social behaviour", adding to an arsenal of surveillance technology in the tightly controlled city-state that is fuelling privacy concerns. From vast numbers of CCTV cameras to trials of lampposts kitted out with facial recognition tech, Singapore is seeing an explosion of tools to track its inhabitants. That includes a three-week trial in September, in which two robots were deployed to patrol a housing estate and a shopping centre. Officials have long pushed a vision of a hyper-efficient, tech-driven "smart nation", but activists say privacy is being sacrificed and people have little control over what happens to their data. Singapore is frequently criticised for curbing civil liberties and people are accustomed to tight controls, but there is still growing unease at intrusive tech.

Reports of the Association for the Advancement of Artificial Intelligence's 2020 Fall Symposium Series

Interactive AI Magazine

The Association for the Advancement of Artificial Intelligence's 2020 Fall Symposium Series was held virtually from November 11-14, 2020, and was collocated with three symposia postponed from March 2020 due to the COVID-19 Pandemic. There were five symposia in the fall program: AI for Social Good, Artificial Intelligence in Government and Public Sector, Conceptual Abstraction and Analogy in Natural and Artificial Intelligence, Physics-Guided AI to Accelerate Scientific Discovery, and Trust and Explainability in Artificial Intelligence for Human-Robot Interaction. Additionally, there were three symposia delayed from spring: AI Welcomes Systems Engineering: Towards the Science of Interdependence for Autonomous Human-Machine Teams, Deep Models and Artificial Intelligence for Defense Applications: Potentials, Theories, Practices, Tools, and Risks, and Towards Responsible AI in Surveillance, Media, and Security through Licensing. Recent developments in big data and computational power are revolutionizing several domains, opening up new opportunities and challenges. In this symposium, we highlighted two specific themes, namely humanitarian relief, and healthcare, where AI could be used for social good to achieve the United Nations (UN) sustainable development goals (SDGs) in those areas, which touch every aspect of human, social, and economic development. The talks at the symposium were focused on identifying the critical needs and pathways for responsible AI solutions to achieve SDGs, which demand holistic thinking on optimizing the trade-off between automation benefits and their potential side-effects, especially in a year that has upended societies globally due to the COVID-19 pandemic. Riding on the success of the AI for Social Good symposium that was held in Washington, DC, in November 2019, we organized the 2020 version of the symposium.

Using AI and machine learning to reduce government fraud


Artificial intelligence is being deployed in many different areas. Within higher education, it is used for college admissions and financial aid decisions. Health researchers employ it to scan the scientific literature for chemical compounds that may generate new medical treatments. E-commerce sites deploy algorithms to make product recommendations for consumers based on their areas of interest.1 But one of the most important growth areas lies in finance and operations. Both public and private sector organizations have large budgets to manage and it is important to operate efficiently and effectively. Accusations of budget inefficiencies or wasteful spending decrease public confidence and make it important to figure out how to manage resources in fair ways. To help with budgetary oversight, AI is being used for financial management and fraud detection. Advanced algorithms can spot abnormalities and outliers that can be referred to human investigators to determine if fraud actually has taken place. It is a way to use technology to improve budget audits, personnel performance, and organizational activities. Yet is it crucial to overcome several problems that plague public sector innovation: procurement obstacles, insufficiently trained workers, data limitations, a lack of technical standards, cultural barriers to organizational change, and making sure anti-fraud applications adhere to responsible AI principles.

Reports of the Workshops Held at the 2021 AAAI Conference on Artificial Intelligence

Interactive AI Magazine

The Workshop Program of the Association for the Advancement of Artificial Intelligence's Thirty-Fifth Conference on Artificial Intelligence was held virtually from February 8-9, 2021. There were twenty-six workshops in the program: Affective Content Analysis, AI for Behavior Change, AI for Urban Mobility, Artificial Intelligence Safety, Combating Online Hostile Posts in Regional Languages during Emergency Situations, Commonsense Knowledge Graphs, Content Authoring and Design, Deep Learning on Graphs: Methods and Applications, Designing AI for Telehealth, 9th Dialog System Technology Challenge, Explainable Agency in Artificial Intelligence, Graphs and More Complex Structures for Learning and Reasoning, 5th International Workshop on Health Intelligence, Hybrid Artificial Intelligence, Imagining Post-COVID Education with AI, Knowledge Discovery from Unstructured Data in Financial Services, Learning Network Architecture During Training, Meta-Learning and Co-Hosted Competition, ...

Apple overhauls Siri to address privacy concerns and improve performance

The Guardian

Apple will no longer send Siri requests to its servers, the company has announced, in a move to substantially speed up the voice assistant's operation and address privacy concerns. The new feature comes two years after the Guardian revealed that Apple staff regularly heard confidential details while carrying out quality control for the feature. Apple's worldwide developers conference (WWDC) was told on Monday that, from this autumn onwards, when new versions of the company's operating systems are released, Siri will process audio "on device" – meaning that, for the majority of queries, no recording will need to be uploaded to Apple's servers. "With on-device speech recognition, the audio of users' requests is processed right on their iPhone or iPad by default," an Apple spokesperson said. "This addresses one of the biggest privacy concerns for voice assistants, which is unwanted audio recording. For many requests, Siri processing is also moving on device, enabling requests to be processed without an internet connection, such as launching apps, setting timers and alarms, changing settings or controlling music."