Tag: artificial intelligence

Siemens Australia is set to attend Hannover Messe 2023, the world’s largest industrial trade fair in Germany, to showcase Australia’s groundbreaking innovations. 

The South Australian Government has unveiled a new statewide innovation model to strategically integrate the state's burgeoning innovation regions as it prepares to capitalise on the opportunities afforded by AUKUS.

The National Reconstruction Fund (NRF) Bill will be critical in addressing financial sector blind spots when it comes to investing in key industries such as manufacturing for scale and transformation, Innes Willox, Australian Industry Group chief executive said in a passage.

Nightingale Intelligent Systems, a provider of advanced security drones, announced an exclusive multiyear distribution agreement with public safety technology firm Arvensys Group in an effort to supply artificially intelligent security drones to Australia and New Zealand.

Additive manufacturing company Titomic Limited said its glass mould coating system delivered to Vetropack in Austria has passed TUV Austria’s site acceptance test. 

Monash University is calling on Indigenous STEM students across Australia to become NASA’s newest interns at its Jet Propulsion Laboratory (JPL) in Pasadena, California 

Drone manufacturing company Nightingale Intelligent Systems has ventured into a partnership with Amazon Web Services (AWS) to integrate the Blackbird Security Drone sensor data with AWS systems to create a highly advanced data analytics platform for intrusion detection, navigation, and life-safety use cases. 

Monash University has partnered with Israel-based Sheba Medical Centre to create more equitable healthcare models and medtech manufacturing opportunities in Victoria. 

The National AI Centre and Minister for Industry and Science Ed Husic, in collaboration with Australia’s national science agency, CSIRO, have unveiled the Responsible Artificial Intelligence Network today, Thursday. 

A research team led by the US Department of Energy’s (DOE) Argonne National Laboratory and the University of Virginia (UVA) has developed various imaging and machine-learning techniques to detect and predict the formation of pores in 3D-printed metals in real time with near-perfect accuracy.