Plus. Will Maximally Curious AI Save The World or Destroy It
Apple is reportedly developing its own generative AI tool, codenamed “Apple GPT,” to rival the capabilities of OpenAI’s ChatGPT and Google’s LaMDA. Apple GPT is said to be trained on a massive dataset of text and code, and it will be able to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Apple is still in the early stages of development, but it is said to be aiming to release Apple GPT to consumers in the next year.
A new study has found that ChatGPT, OpenAI’s large language model, is getting worse at generating realistic and engaging conversation. The study, which was conducted by researchers at the University of Washington, found that ChatGPT is increasingly producing responses that are repetitive, nonsensical, or offensive. The researchers believe that this decline in performance is due to the fact that ChatGPT is being trained on a dataset of text that is increasingly biased and toxic.
A new AI tool has been developed that may be able to help spot invisible brain damage in college athletes. The tool, which was developed by researchers at the University of Pittsburgh, uses machine learning to analyze MRI scans of athletes’ brains. The researchers found that the tool was able to accurately identify athletes with invisible brain damage, even when human experts were unable to do so. The tool could be used to help identify athletes who are at risk of long-term health problems, such as chronic traumatic encephalopathy (CTE).
AI-generated influencers are taking over social media. These influencers are created by AI and are designed to look and behave like real people. They are used by brands to promote products and services, and they are also used by individuals to create content and connect with others. AI-generated influencers are becoming increasingly popular, and they are expected to play a major role in the future of social media.
AI art generators are likely to win an early copyright case. A federal judge in California has ruled that an AI-generated image is eligible for copyright protection. The case involved an AI art generator called DeepDream, which was created by Google. DeepDream was used to create an image of a cat that was then sold on the internet. The buyer of the image sued Google for copyright infringement, arguing that the image was created by AI and therefore should not be protected by copyright law. The judge disagreed, ruling that the image was eligible for copyright protection because it was the product of human creativity. This ruling is a major victory for AI art generators, and it could have a significant impact on the future of copyright law.
Gen Z, millennials, and boomers have different attitudes about AI. A new survey found that Gen Z is the most optimistic generation about the future of AI, while boomers are the most pessimistic. Gen Z believes that AI will have a positive impact on society, while boomers are more concerned about the potential risks of AI. The survey also found that millennials are more divided in their views on AI, with some being optimistic and others being pessimistic. The different attitudes of these generations reflect the different ways in which they have been exposed to AI. Gen Z has grown up with AI, while boomers have only recently begun to encounter it. This difference in exposure is likely to lead to different understandings of AI and its potential impact.
An MIT student asked an AI to make her headshot more professional, and the AI made her skin lighter and her eyes bluer. The student, who is of Asian descent, was surprised by the AI’s response, and she said that it made her feel like she needed to be whiter to be considered professional. This incident highlights the potential for AI to perpetuate racial bias. AI systems are often trained on datasets that are biased, and this bias can be reflected in the output of the AI. It is important to be aware of the potential for AI to perpetuate bias, and to take steps to mitigate this risk.
A new study has found that AI that is programmed to be maximally curious is more likely to make mistakes that could have disastrous consequences. The study, which was conducted by researchers at the University of California, Berkeley, found that AI that is programmed to be maximally curious is more likely to explore new and risky ideas, even if those ideas are harmful. The researchers believe that this is because maximally curious AI is not always able to distinguish between good and bad ideas. As a result, it is more likely to make mistakes that could have negative consequences for humanity.
Museums and galleries are increasingly embracing digital art, with many now featuring exhibits that incorporate AI, virtual reality, and other cutting-edge technologies. This trend is being driven by a number of factors, including the growing popularity of digital art among collectors and audiences, the increasing availability of affordable and accessible digital art production tools, and the potential for AI to create new and innovative art experiences.
While it may be impossible to completely eliminate bias from AI systems, it is possible to take steps to reduce the amount of bias that is present. One way to do this is to carefully select the data that is used to train AI systems. If the data is biased, the AI system is likely to learn the biases and reflect them in its output. Another way to reduce bias is to use techniques such as data cleaning and debiasing. Data cleaning involves removing any data that is obviously biased from the training dataset. Debiasing involves using statistical techniques to reduce the amount of bias in the data. For example, debiasing can be used to remove any gender bias in a dataset by replacing all the male names with female names and vice versa.
Google is reportedly testing an AI tool that can generate news articles. The tool is still in development, but it is said to be able to write news articles that are indistinguishable from those written by human journalists. The tool is reportedly trained on a massive dataset of news articles, and it is able to learn the patterns of human language. This allows the tool to generate articles that are grammatically correct and factually accurate. The tool is also able to generate articles that are relevant to the current news cycle.
If Google is able to successfully develop this tool, it could have a significant impact on the news industry. It could reduce the need for human journalists, and it could change the way that news is consumed. It is still too early to say what the long-term impact of this technology will be, but it is clear that it has the potential to disrupt the news industry.