COVID-19 has triggered one of the most disruptive periods on record for air travel and the International Air Transport Association (IATA) has estimated that airlines will lose at least $314 billion due to the outbreak. As the industry looks to adapt to this new Covid-era, not only will airlines need to take a serious look at their overheads, but the standard of safety will need to remain the number one priority. With pilots and their training accounting for one of the biggest costs, airlines will need to re-think their pilot training strategy which is likely to include a need to outsource and decentralise to maximize efficiency. This resultant strain highlights the need for regulators to make changes to the training process. For example, there will need to be more reliance on e-learning in the initial cadet training and the acceptance of integrated technology in simulator training will also be important.
Etihad Airways is to resume trials of a special food waste detection system that utilises artificial intelligence to track unconsumed Economy class meals across Etihad's flights. After the COVID-19 pandemic stopped the trial in its tracks earlier this year, the airline has once again restarted the programme in collaboration with Singapore startup Lumitics. According to the food technology company, Etihad should expect to start seeing results within the first few months of operation. Already in use by several airlines, including Singapore Airlines, the system uses a combination of image recognition and AI to differentiate and identify the types and quantity of unconsumed meals based on the design of the meal foils. While many airlines already have some sort of system in place to identify and count food waste, these processes are normally slow and labour intensive.
Frost & Sullivan's recent study, Analysis of the Global Airline IT Market, Forecast to 2025, finds that the increasing expectations of passengers are compelling airlines to embrace digital enablers. Impacted by the COVID-19 pandemic, the airline IT market is estimated to generate a revenue of US$20.74 billion by 2025, compared to US$21.20 billion in 2019. As per the original forecast, by 2025, the market was estimated to reach US$25.1 billion from US$21.20 billion in 2019. "Despite the adverse impact of COVID-19 on the industry, airlines are increasingly focusing on adopting next-generation digital solutions such as mobility, machine learning (ML), big data analytics, and artificial intelligence (AI) to identify cost-saving and revenue-generating opportunities," said Abhilash Varkey Abraham, aerospace & defense research analyst at Frost & Sullivan, in a prepared statement. "Additionally, a few major airlines have already committed to migrating their entire IT infrastructure to the cloud over the next three to five years and this trend is likely to continue and grow, mainly among low-cost carriers."
What if I told a story here, how would that story start?" Thus, the summarization prompt: "My second grader asked me what this passage means: …" When a given prompt isn't working and GPT-3 keeps pivoting into other modes of completion, that may mean that one hasn't constrained it enough by imitating a correct output, and one needs to go further; writing the first few words or sentence of the target output may be necessary.
Thermal-imaging cameras and swab tests for coronavirus are not "clinically valuable" in airports, according to a panel of aviation health experts. About one in every three infectious people would be missed, they say. Air systems and low humidity on planes already reduces virus spread through the cabin. But passengers should wear face coverings at all times, board and disembark one row at a time and be seated apart from others if possible. And those seated at the back should be the first on and last off.
Rolnick, David, Donti, Priya L., Kaack, Lynn H., Kochanski, Kelly, Lacoste, Alexandre, Sankaran, Kris, Ross, Andrew Slavin, Milojevic-Dupont, Nikola, Jaques, Natasha, Waldman-Brown, Anna, Luccioni, Alexandra, Maharaj, Tegan, Sherwin, Evan D., Mukkavilli, S. Karthik, Kording, Konrad P., Gomes, Carla, Ng, Andrew Y., Hassabis, Demis, Platt, John C., Creutzig, Felix, Chayes, Jennifer, Bengio, Yoshua
Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.