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    The Top Reasons Why Most AI Projects Fail

    Lakisha DavisBy Lakisha DavisOctober 18, 2021
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    The Top Reasons Why Most AI Projects Fail
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    You might think that artificial intelligence is only available to huge companies with huge budgets, but in reality it is not. It’s more affordable and more versatile than you might think.

    Artificial Intelligence (AI), if programmed and used properly, can help you increase sales, improve customer service, and run your business more efficiently.

    Lack of Data

    Data problems are one of the main reasons why artificial intelligence projects fall short of expectations. According to a report released by McKinsey last fall, two of the biggest problems limiting the use of artificial intelligence technologies are related to data.

    First, Mr. Cooper, many companies have difficulty getting properly labeled data to train machine learning algorithms. The data is not properly classified to mark it up, which can delay their work or even the project to failure. The second data problem is the lack of the right data for the project.

    “Companies often don’t have the data they need because it’s not mapped,” says Anand Rao, partner and global leader in artificial intelligence at PricewaterhouseCoopers.

    The National Audubon Society uses artificial intelligence to protect wild birds. So, in July, the organization published the results of an analysis of how climate change will affect 38 species of meadow birds.

    “If we don’t do anything to slow climate change, 42% of the ways grassland birds will be blocked are very vulnerable,” said Chad Wilsay, vice president of conservation research. “But if we can take action, we will reduce this figure to 8%.”

    Not all similar projects of the Audubon Society have been as successful. Last summer, the organization tried to use machine learning to count the number of brown pelicans and black water cutters on beaches. The pilot project is based on a set of images collected by a volunteer who launched a drone over an island off the coast of Texas.

    “We were interested in understanding how the hurricane that passed over the island affected the bird population,” says Wilsay.

    According to Wilsi, it took 2 thousand rubles. labeled images of brown pelicans. But there weren’t enough black water cutters. “For other computer vision applications, you can use what is available on the Internet,” he says. “But in this case, the images of the birds are very specific.”

    There are other photographs of birds that are at ground level, rather than drones looking straight down. And since this was a pilot study, the Audubon Society did not have the resources to continue collecting data and take more images.

    Artificial intelligence (AI) has become a really hot topic in the last few years. Scientists associate this with the rapid development of neural networks (one of the areas of research in the field of ai solutions development company), which, in turn, became possible with the advent of powerful computers.

    • Hawking: artificial intelligence is a threat to humanity
    • Is artificial intelligence threatening humans?

    “Since the early 2010s, influenced by the impressive success achieved by the use of multilayer neural networks (primarily convolutional and recurrent), this area has attracted serious attention from both scientists and engineers and from investors,” comments the author one of the Russian chess programs, machine learning specialist Sergey Markov.

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    Lakisha Davis

      Lakisha Davis is a tech enthusiast with a passion for innovation and digital transformation. With her extensive knowledge in software development and a keen interest in emerging tech trends, Lakisha strives to make technology accessible and understandable to everyone.

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