A recent article in VentureBeat argues that generative AI will not replace programmers anytime soon. The article cites several reasons for this, including the fact that generative AI is still in its early stages of development and is not yet capable of handling complex tasks. Additionally, programmers are still needed to create and maintain the infrastructure that generative AI relies on.
A new article in The Guardian explores how AI is being used to revolutionize Corbusier’s architecture. Corbusier was a 20th-century architect who is known for his minimalist designs. AI architects now use machine learning to create new and innovative Corbusier-inspired buildings.
A new poll conducted by the Los Angeles Times found that a majority of actors and writers are worried about the impact of AI on their jobs. The poll also found that a significant number of people in other professions are also worried about AI. These findings suggest that AI could have a major impact on the job market in the years to come.
A new article in Reuters explores the potential economic impact of AI. The article argues that AI could have both positive and negative effects on the economy. On the one hand, AI could lead to increased productivity and economic growth. On the other hand, AI could also lead to job losses and inequality.
A new study published in SciTech Daily warns that doctors are not prepared for the AI transformation of medicine. The study found that most doctors do not have the skills or knowledge necessary to use AI effectively. This could lead to patient safety risks and missed diagnoses.
An AI system developed by NASA has found the first possibly dangerous asteroid. The asteroid, named 2023 GL6, is about 100 meters in diameter and has a 1 in 1,000 chance of impacting Earth in 2028. The AI system is still under development, but it has
AI algorithms can now predict the price of a house by analyzing visuals from sources like Google Street View. This AI technology has the potential to transform the real estate market, but there are concerns about its limitations and biases. While agents currently rely on visual inspections to assess a property, AI could offer a faster and more accurate alternative. MIT’s Senseable City Lab trained a deep learning model using pictures of 20,000 houses in Boston to predict changes in their values. The algorithm was able to accurately predict price changes when combined with other variables like structural information and neighborhood amenities. The researchers also found that visual AI can predict a neighborhood’s profile, such as poverty, crime, and public health. However, there are risks associated with algorithmic real estate, including the possibility of perpetuating biases against certain groups and the potential for predictions to influence market behavior. To effectively use visual AI, regulation and experimentation will be necessary, while also ensuring that human judgment is still valued—the potential to revolutionize the way we track and monitor asteroids.