AI News, The Artificial Intelligence Index: AI Hiring, Data, Trends artificial intelligence

Is Artificial Intelligence Dead?

The hiring rate has been increasing for not only advanced economies but also for many emerging markets.

The AI hiring rate is the percentage of LinkedIn members who had any AI skills on their profile and added a new employer to their profile in the same month the new job began, divided by the total number of LinkedIn members in the country.

Countries are included if they met the conditions: Countries meeting these conditions are: United States, Netherlands, Ireland, Denmark, Australia, United Kingdom, Luxembourg, Canada, Singapore, Belgium, New Zealand, Norway, Sweden, United Arab Emirates, France, Portugal, Switzerland, Chile, Spain, Italy, Hong Kong (SAR), Finland, Israel, Costa Rica, Brazil The following chart shows which sectors are having a growing share of AI jobs in the US.

Artificial intelligence in heavy industry

Artificial intelligence, in modern terms, generally refers to computer systems that mimic human cognitive functions.

While this type of general artificial intelligence has not been achieved yet, most contemporary artificial intelligence projects are currently better understood as types of machine-learning algorithms, that can be integrated with existing data to understand, categorize, and adapt sets of data without the need for explicit programming.[1]

AI-driven systems can discover patterns and trends, discover inefficiencies, and predict future outcomes based on historical trends, which ultimately enables informed decision-making.[1]

While the application of artificial intelligence in heavy industry is still in its early stages, applications are likely to include optimization of asset management and operational performance, as well as identifying efficiencies and decreasing downtime.[1]

Businesses can expand their production capabilities and meet higher demands for products from global customers due to boosted production from this round-the-clock work performance.[3]

Logically speaking, with fewer humans and more robots performing activities associated with risk, the number of workplace accidents should dramatically decrease.[3]

They can be programmed to navigate the most efficient route and reduce idle time, which could result in less fossil fuel consumption and greenhouse gas (GHG) emissions.[4]

AI helps machines gather and extract data, identify patterns, adapt to new trends through machine intelligence, learning, and speech recognition.[2]

It also helps to make quick data-driven decisions, advance process effectiveness, minimize operational costs, facilitate product development, and enable extensive scalability.[2]

The software in the cars falsely activated emission controls of nitrogen oxide gases (NOx gases) when they were undergoing a sample test.[6]

Further studies have shown that additional emissions could cause over 1,200 premature deaths in Europe and result in $2.4 million worth of lost productivity., a startup formed by Andrew Ng, developed machine-vision tools that detect microscopic defects in products at resolutions well beyond the human vision.

In the automotive industry, a sector with a particularly high degree of automation, Japan had the highest density of industrial robots in the world at 1,414 per 10,000 employees.[8]

Designers or engineers specify design goals (as well as material parameters, manufacturing methods, and cost constraints) into the generative design software.[7]

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