Artificial intelligence is on full display at an exposition in Washington, DC, where one of the main focuses is how to incorporate AI into weapons systems. Organisers say the technology will lead to a better future, but critics are warning of the dangers that come with the high-tech advances.

Over the past few months, artificial intelligence has managed to create award-winning art, pass the bar exam and even diagnose illnesses better than some doctors. But as AI grows more sophisticated and popular, the voices warning against the potential dangers are growing louder. Geoff Bennett discussed the concerns with Seth Dorbin of the Responsible AI Institute.

OpenAI has been known for its mission to develop and promote artificial intelligence in a safe and ethical manner. However, the organization recently announced that it will no longer be open sourcing its AI code. This decision has raised concerns about the potential dangers of limiting access to AI research and development. One of the biggest dangers of not open sourcing AI code is the potential for decreased transparency and accountability. Open sourcing code allows other researchers to verify the accuracy and safety of AI models, which can lead to improvements and prevent the deployment of harmful systems. Without open sourcing, there is less transparency and accountability for the development of AI models, which could lead to unintended consequences and the deployment of unsafe AI systems.

AI can be unsettling for most people. Off the top of their head, many people think about robots taking over the human population or self-destructive devices. When coupled with construction, an industry that is notable for being slow to embrace technology; then you have reached a standstill as said industry is reluctant to change. On one corner is AI; a bit of an unknown element but one that is also dynamic and capable of many things. On the other, there is the construction sector; a dwindling industry frequently faced with challenges that threaten workers' safety, productivity, and resources.

Large language models like ChatGPT can generate coherent, believable text. How does this impact education and teaching? Strictly speaking, ChatGPT – artificial intelligence that generates texts in response to input prompts – is not even the beginning, but merely an intermediate stage in natural language processing (NLP), which has been observed for about ten years. ChatGPT also can't do anything fundamentally new that earlier tools couldn't. It differs only in the quality of the generated output, the focus on interactivity (input of questions and AI-generated answers) and, above all, in its captivating simplicity: a URL, a registration, a single simple empty text field and the infinity of text generation is open to you, which moreover (depending on the question, mostly) provides meaningful and well-founded results, since it accesses a corpus of about 1 trillion words (from 6 million Wikipedia articles and millions of books and websites). It should be noted that the training dataset consists almost exclusively of English-language texts, but AI-assisted translation also comes into play when communicating with users.

GPT-3 language models are being abused to do much more than write college essays, according to WithSecure researchers. The security shop's latest report [PDF] details how researchers used prompt engineering to produce spear-phishing emails, social media harassment, fake news stories and other types of content that would prove useful to cybercriminals looking to improve their online scams or simply sew chaos, albeit with mixed results in some cases. And, spoiler alert, yes, a robot did help write the report. "In addition to providing responses, GPT-3 was employed to help with definitions for the text of the commentary of this article," WithSecure's Andrew Patel and Jason Sattler wrote. For the research, the duo conducted a series of experiments to determine how changing the input to the language model affected the text output.

ChatGPT is a language model developed by OpenAI, an artificial intelligence (AI) research laboratory founded in late 2015 by Elon Musk (yes, him again) and Sam Altman. It is designed to be able to generate natural language text in response to user inputs. The model is based on the GPT-3 architecture, which uses a combination of deep learning and natural language processing techniques to generate text that is similar to human-generated language. On the positive side, ChatGPT has shown impressive capabilities in generating text that is coherent and relatively natural-sounding. In tests, the model has been able to generate responses to user inputs that are relevant and on-topic, and in some cases it has even been able to engage in complex conversations that span multiple topics.

Our world is experiencing a digital transformation. From the smart thermostat in our homes to vehicles equipped with driver assistance to the voice assistants that answer our every question, we have a wealth of data available, and artificial intelligence (AI) is using it to reimagine how we live and work. As technology continues to advance, businesses are understanding the value of AI-based systems. Between 2015 and 2019, the number of enterprises using AI grew by 270%. But without humans on the manufacturing floor, these applications wouldn't exist.

AI technology can be difficult to understand and use, especially for young aspirants who are new to it. An AI program for young aspirants will help them learn about and use AI technology more effortlessly. AI technology is constantly evolving and changing, and young aspirants who have expertise in it now will be better prepared to become innovators in the future. An AI program inspires and helps young aspirants to lead AI technology and with good expertise, they can also innovate bigger things in the future. AI technology can be used to solve a variety of problems.

The investigation of factors contributing at making humans trust Autonomous Vehicles (AVs) will play a fundamental role in the adoption of such technology. The user's ability to form a mental model of the AV, which is crucial to establish trust, depends on effective user-vehicle communication; thus, the importance of Human-Machine Interaction (HMI) is poised to increase. In this work, we propose a methodology to validate the user experience in AVs based on continuous, objective information gathered from physiological signals, while the user is immersed in a Virtual Reality-based driving simulation. We applied this methodology to the design of a head-up display interface delivering visual cues about the vehicle' sensory and planning systems. Through this approach, we obtained qualitative and quantitative evidence that a complete picture of the vehicle's surrounding, despite the higher cognitive load, is conducive to a less stressful experience. Moreover, after having been exposed to a more informative interface, users involved in the study were also more willing to test a real AV. The proposed methodology could be extended by adjusting the simulation environment, the HMI and/or the vehicle's Artificial Intelligence modules to dig into other aspects of the user experience.