AI-Designed World’s First Robot Reproduces, Qlik Extends Advanced Machine Learning Capabilities and more!

AI Created World's First Living Robot that can Reproduce

(Burlington) Xenobots are the world's first AI-designed biological robots that can self-heal and self-replicate. Xenobots are commonly referred to as "machines" by researchers, despite the fact that they lack any mechanical components. Science may be evolving faster than our framework for discussing and even imagining this new category of machine life. 

In 1948, Hungarian-American mathematician John von Neumann introduced the concept of an autonomous robot capable of reproducing itself from raw resources. Once a theory, Neumann’s vision has finally become a reality, with just a major twist: the self-replicating robot isn’t made of aluminum, plastic, spur gears, or sprockets. The parent robot and its offspring, a new lineage of organisms known as Xenobots, are completely biological.

Under Big Data Regulations, China Set to Impose Security Check on Hong Kong IPOs

(Shanghai) – China's Ministry of Industry and Information Technology (MIIT) called for enhanced cross-border security management of big data until 2025, as per the five-year plan published on Tuesday. The strategy, which builds on China's 14th Five-Year Plan, is released at a time when the government is advancing its regulatory framework for data and technology. It reaffirms data as a "factor of production" and a "national strategic resource." The strategy includes six essential responsibilities, such as boosting data "marketization," increasing processing power, and taking the lead in defining global technological standards. It also advocated for improved management of cross-border data flows and more support for open source efforts.

Qlik Expands its Advanced Machine Learning Capabilities in the Cloud with Qlik's Active Intelligence PlatformTM

(Bangalore) Qlik extended its partnership with Amazon Web Services (AWS) today by releasing an advanced analytics connection for Amazon SageMaker and also connectivity with Amazon SageMaker Autopilot. These interfaces will expand the range of advanced analytics capabilities currently available in Qlik Cloud, allowing for easy interaction with Amazon's powerful machine learning capabilities, all through Qlik's Active Intelligence PlatformTM.

Qlik's addition is a step towards its vision of Active Intelligence. Advanced machine learning capabilities will generate greater predictive and prescriptive analytics through which enterprises can seize each business moment. As per the official sources, Amazon SageMaker users will now be able to make use of their products directly on the Qlik SaaS platform, opening up even more potential for them. 

Siemens Collaborates on Digital Mobility Transformation with Hyundai Motor Company and Kia Corporation

(PLANO, Texas) – Siemens, Hyundai Motor Company, and Kia Corporation (Hyundai and Kia) established a new technological alliance today to drive their digital transformation and a new mobility future. Hyundai and Kia have chosen Siemens as their preferred bidder and strategic partner to supply next-generation engineering and product data management using NXTM software and the Teamcenter® portfolio from Siemens' Xcelerator range of integrated software, services, and development platforms. Hyundai and Kia researched and appraised many options, including incumbent solutions, and chose Siemens' software, which incorporates the world's most comprehensive digital twin. Hyundai and Kia will work with Siemens, a vital valued partner, to shape the future of mobility.

Artificial Intelligence may aid in Refractive Surgery Diagnosis

(NEW ORLEANS) – Artificial intelligence could be employed as a refractive surgery diagnostic tool, according to a speaker at the American Academy of Ophthalmology's Refractive Surgery Subspecialty Day. "A robust [machine learning] process generally includes feature engineering, selecting the most appropriate algorithm, optimizing its parameters, selecting the most predictive features, and understanding the interconnection and patterns between both existing and created selective variables," said Marcony R. Santhiago, M.D., Ph.D. "As a result, independent of the cutoff point associated with each of the variables, a better identification of individuals at higher risk becomes achievable." Santhiago and colleagues were able to achieve 100% sensitivity for detecting early keratoconus using the AI model.