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Where are the Chinese going to get the energy for this?Not too long ago, China announced an ambitious…


Where are the Chinese going to get the energy for this?

Not too long ago, China announced an ambitious and promising space program. This program included plans for the creation of their own multi-module fully manned orbital space station as well as the construction of reusable space transport systems for manned flights to the moon.

SpaceX is hoping to attempt to fly its in-development spacecraft Starship to orbit for the first time in July, according to company president Gwynne Shotwell shared the timeline at the International Space Development conference during a virtual speaking engagement.

Starship has been in development for the past several years, and it has been making shorter test flights, but remaining within Earth’s atmosphere, since last year. Its most recent flight also included its first fully successful landing, which is a key ingredient in the development of the Starship launch system, which is designed to be SpaceX’s first that is fully reusable.

July (aka next month) is an ambitious timeline for making the first orbital flight attempt of Starship, but in May SpaceX filed its planned course for the flight, which would lift off from the company’s Starship development site in south Texas near Brownsville (known as ‘Starbase’) and then eventually return to Earth with a splash down in the Pacific Ocean somewhere off the cost of Hawaii.

I doubt they were the first to use artificial intelligence in war. But it does discuss the AI technologies used in the recent conflict.

They used AI technology to identify targets for air strikes, specifically to counter the extensive tunnel network of their opponents.


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Generational shifts in the workforce are creating a loss of operational expertise. Veteran workers with years of institutional knowledge are retiring, replaced by younger employees fresh out of school, taught on technologies and concepts that don’t match the reality of many organizations’ workflows and systems. This dilemma is fueling the need for automated knowledge sharing and intelligence-rich applications that can close the skills gap.

Industrial organizations are accumulating massive volumes of data but deriving business value from only a small slice of it. Transient repositories like data lakes often become opaque and unstructured data swamps. Organizations are switching their focus from mass data accumulation to strategic industrial data management, homing in on data integration, mobility, and accessibility—with the goal of using AI-enabled technologies to unlock value hidden in these unoptimized and underutilized sets of industrial data. The rise of the digital executive (chief technology officer, chief data officer, and chief information officer) as a driver of industrial digital transformation has been a key influence on this trend.

According to recent Occupational Safety and Health Administration data, workers at Amazon fulfillment centers were seriously injured about twice as often as employees in other warehouses. To improve workplace safety, Amazon has been increasing its investment in robotic helpers to reduce injuries among its employees. With access granted for the first time ever, “Sunday Morning” correspondent David Pogue visited the company’s secret technology facility near Seattle to observe some of the most advanced warehouse robots yet developed, and to experience how high-tech tools are being used to aid human workers.

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An outstanding idea, because for one there has been a video/ TV show/ movie, etc… showing every conceivable action a human can do; and secondly the AI could watch all of these at super high speeds.


Predicting what someone is about to do next based on their body language comes naturally to humans but not so for computers. When we meet another person, they might greet us with a hello, handshake, or even a fist bump. We may not know which gesture will be used, but we can read the situation and respond appropriately.

In a new study, Columbia Engineering researchers unveil a vision technique for giving a more intuitive sense for what will happen next by leveraging higher-level associations between people, animals, and objects.

“Our algorithm is a step toward machines being able to make better predictions about , and thus better coordinate their actions with ours,” said Carl Vondrick, assistant professor of computer science at Columbia, who directed the study, which was presented at the International Conference on Computer Vision and Pattern Recognition on June 24, 2021. “Our results open a number of possibilities for human-robot collaboration, autonomous vehicles, and assistive technology.”