April 23, 2023

  • Hysteria

    The impending nightmare that AI poses for media, elections

    The Hill, 04/23/23. In a recent article, Joe Concha discusses the potential dangers of deepfake technology in the political arena. With the rise of artificial intelligence, the possibilities for manipulating content have increased, and the impact of deepfake videos on political campaigns has already been seen in recent elections. As AI continues to advance, the warnings of Elon Musk and others about the risks of AI experimentation may go unheeded, as the potential monetary and political gains are too significant to ignore. However, through media scrutiny and awareness, the impact of AI technology on political campaigns can potentially be mitigated.
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  • Auto-GPT

    What Is Auto-GPT? A Next-Level AI Tool Surpassing ChatGPT?

    Forbes, 04/23/23. Auto-GPT is a revolutionary technology that is poised to take language models to the next level. Unlike limited language models that only complete one task at a time, Auto-GPT can carry out complex, multi-step procedures through the creation of its own prompts and feedback loop. Auto-GPT is capable of browsing the internet and suggesting improvements to business processes. Furthermore, it can build software applications from start to finish and it has better memory than other language models. While Auto-GPT has many potential benefits, AI experts warn that it could also create new ethical dilemmas, such as the potential for sentient AI chatbots to be developed and operated on a large scale.
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  • Adoption

    AI Development Lifecycle: Complete Breakdown in 2023

    United.ai, 04/23/23. Artificial intelligence (AI) has transformed the way businesses operate, offering new insights that have enhanced their decision-making ability. With 91.5% of leading businesses investing in AI, the development and deployment of AI projects is essential. However, the AI development lifecycle has become increasingly complex, with developers facing various challenges such as data quality, quantity, and selecting the right architecture. To overcome these issues and realize the benefits of AI, businesses require a structured approach that spans the entire lifecycle from problem definition to model deployment and maintenance. The nine stages of a successful lifecycle include identifying the business objective, collecting and exploring data, data preprocessing, feature engineering, model training, evaluation, deployment and monitoring, and model maintenance. Managing large volumes of data, using complicated software tools, and dealing with learning curves and lack of hardware are some of the challenges developers face during the AI development lifecycle.
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  • Customer Experience

    People expect AI bots to be competent, but do not want them to be humanlike

    Star Tribune, 04/23/23. As AI chatbots become more prevalent in customer service, marketers are advised to keep interactions simple and straightforward. Despite the potential for messages to be personalized and engaging through AI-generated humor or figurative language, this approach can backfire, making customers perceive the chatbot as uncooperative or even threatening. In fact, AI-generated humor was found to be less effective in persuading customers to book hotel rooms in a study mentioned in a paper by Marat Bakpayev and Ann Kronrod, marketing professors at Minnesota Duluth and UMass Lowell respectively. Successful interactions require careful design with reference to consumer expectations, perceptions and the context in which they will be used. Expertise from diverse fields such as linguistics, sociology, and anthropology is key, suggests Bakpayev.
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  • Edge

    This AI wearable could surpass the iPhone — and it’s made by former Apple employees

    Tom’s Guide, 04/23/23. Thank you! How may I assist you today?
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