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Artificial Intelligence Has an Emissions Problem - My TechDecisions

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Technology, artificial intelligence and automation are supposed to solve our biggest problems, not create new ones or exacerbate existing issues. Unbeknownst to many, big tech is actually putting a huge burden on the environment. In a study assessing the energy consumption required to train several common large AI models, Researchers at the University of Massachusetts Amherst said artificial intelligence emissions can be over 626,000 pounds of carbon dioxide, which is about 5 times as much the lifetime emissions of an average car. According to research firm IDC, spending on AI systems is exploding, with the figure expected to hit nearly $98 billion in 2023, more than 3.5 times the $37.5 billion being spent this year. The U.S. is expected to deliver more than half of that spending through the forecast, which will be led by the retail and banking industries, according to IDC.


Three Verticals Where Artificial Intelligence Technology Needs To Be Better - My TechDecisions

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Artificial intelligence technology is an incredible advancement and is paving the way for the future of big tech and the way humans live. Just this morning, my iPhone told me how long it would take to get to work without me even moving a finger. Thanks to my spam filter, I don't even see the very legit emails offering me a fast $15,000 personal loan or a $100 Visa gift card. Those artificial intelligence technology applications are small potatoes in the greater AI world, but tech companies are pushing the technology's limits and the field is rapidly advancing -- sometimes at the expense of society. Please do develop applications and technology that make our lives easier, but we should be smart about it and not release technology that has to constantly be updated before it actually works the way it was intended.


Avoiding AI Bias Requires Diverse Workers, Research - My TechDecisions

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Machine learning and artificial intelligence are by no means perfect, and it takes human intervention to constantly tweak algorithms. Those applications are essentially based on math problems and may never bee 100% accurate, so companies and software developers should think carefully before going down that road. At a recent conference, TWIMLcon: AI Platforms, panelists spoke about the ethics of artificial intelligence and the need for its human developers to take painstaking actions to ensure these applications work for everybody. Any one group or central team should not be the only to write code and fix fairness or the whole company. To do this, companies must have a diverse group of people working on these applications.


What are Industrial Machine Learning Systems and How Are They Changing Industries? - My TechDecisions

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The question that seems to get asked more often than not is to talk about how many industrial applications we can name for machine learning. Industrial machine learning is not a device you can plug into a production line and make the production line operate better than it did before. Machine learning is a process that needs inputs from many devices to feed data to it so that data can be collected, evaluated, and used to develop knowledge about how a production line produces the products and parts it does. That knowledge can then be used to determine how production line can have a higher throughput of parts, operate at a lower cost, and run more reliably. In that way, industrial machine learning transforms an industrial operation into a system of systems that can get products to market faster at a lower cost so the company that owns it can remain competitive in its market and keep their customers happy by delivering the products they want.


Machine Learning Overview: Everything You Need to Know - My TechDecisions

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In recent years machine learning is gaining more and more popularity, but what exactly is it? The name "machine learning" initially originated from famous gaming researcher Arthur Lee Samuel. Samuel is the first person to bring self-learning programs into society. This remarkable discovery shortly laid the foundation for machine learning algorithms. In later years, rising popularity in artificial intelligence give birth to many innovations in the field of Computers and Automation.


Investor Sues Company Over Artificial Intelligence Advice - My TechDecisions

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Decision makers are becoming more wary about certain uses of AI, including trusting solutions to make money for them. When things go wrong and losses are up, it's tough to know who's responsible – the machine, or the person behind the machine. Bloomberg reports on a recent example of this, where an investor is suing for damages after losing money based on the decisions made by a money management solution. According to Bloomberg, back in 2017, investor Samathur Li Kin-kan bought into a money management AI solution that another investor, Raffaele Costa, planned on using to mange the money made by his company, Tyndaris. "The idea of a fully automated money manager inspired Li instantly," driving him to invest in the solution to grow his own money – $2.5 billion- $250 million worth.


Investor Sues Company Over Artificial Intelligence Advice - My TechDecisions

#artificialintelligence

Decision makers are becoming more wary about certain uses of AI, including trusting solutions to make money for them. When things go wrong and losses are up, it's tough to know who's responsible – the machine, or the person behind the machine. Bloomberg reports on a recent example of this, where an investor is suing for damages after losing money based on the decisions made by a money management solution. According to Bloomberg, back in 2017, investor Samathur Li Kin-kan bought into a money management AI solution that another investor, Raffaele Costa, planned on using to mange the money made by his company, Tyndaris. "The idea of a fully automated money manager inspired Li instantly," driving him to invest in the solution to grow his own money – $2.5 billion- $250 million worth.