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ChatGPT appeared to go rogue on Tuesday evening as users reported the AI chatbot responding with incorrect answers and talking gibberish, as reported by 404Media.
Members of a ChatGPT subreddit shared their experiences with screenshots of extraordinary exchanges with the technology, responses either making no sense or answers to questions being way off the mark.
One screenshot showed this response to a question: “This is the work of service and any medical today to the data field.” It continued: “The 12th to the degree and the pool to the land to the top of the seam, with trade and feature, can spend the large and the all before it’s under the care.”
Meanwhile, another user explained that they asked ChatGPT for “a synonym for overgrown” and got the response: “A synonym for “overgrown” is “overgrown” is “overgrown” is “overgrown”…”
Other users claimed it gave totally incorrect answers to the basic questions, such as responding with “Tokyo, Japan” when asked to name the biggest city on earth that begins with an ‘A.’
OpenAI, the creators of ChatGPT, has confirmed it has fixed the issue in a message on its status page. Still, it’s another reminder that while we’re in the middle of an AI boom, the technology is not yet immune to going rogue or, quite simply, going wrong.
AI models like ChatGPT have a long way to go
This is just another example of AI technology proving it’s not yet capable of earning complete trust from its users, despite fears that Artificial Intelligence has the potential to replace humans in a variety of day-t0-day tasks, both at home and in the workplace.
There have already been several instances where lawyers have gotten in trouble for citing fictitious cases generated by AI. Just last month, Reuters reported that a New York lawyer was facing disciplinary action after they used ChatGPT for research in a medicinal malpractice lawsuit and failed to confirm that the case cited was valid.
Featured Image: Photo by Jonathan Kemper on Unsplash
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WhatsApp has introduced four new text formatting options, enhancing the way users can communicate and organize their messages. Starting today, WhatsApp users across Android, iOS and web platforms, including those utilizing the app’s Channels feature, can access bulleted and numbered lists, block quotes, and inline code formats. These additions complement the existing text formatting capabilities such as bold, italic, strikethrough, and monospace.
Enhanced messaging on WhatsApp with new formatting options
The introduction of these formatting options is aimed at improving readability and information organization within messages. For instance, users can now create bulleted lists to itemize information like shopping lists or agenda points, making it easier to digest large blocks of text. To create a bulleted list, users simply need to start their message with a “-” symbol followed by a space.
For content that requires a specific order, such as step-by-step instructions, the numbered list format is ideal. Users can initiate this format by typing one or two digits, followed by a period and a space, like “1. ” or “2. “. This feature is particularly useful for recipes, workflows, or any instructions that benefit from a clear sequence.
Block quotes have also been introduced to help users highlight significant portions of text within longer messages. By typing the “>” symbol followed by a space before the text, users can set apart quotes or important information, making it stand out for emphasis.
Lastly, the inline code format caters not only to coders who wish to share snippets of code but also to users looking to highlight specific pieces of text within their messages. This format can be activated by enclosing the text with the “`” symbol on both sides.
These new formatting options have been long-awaited by WhatsApp users seeking more sophisticated ways to structure and emphasize their messages. With the addition of bulleted and numbered lists, block quotes, and inline code, WhatsApp expands its functionality to support a wider range of messaging needs. These updates enhance clarity and organization in communication for personal, professional, and coding purposes.
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AI has been used to produce everything from images, movies, as well as chatbots. Now a former Google DeepMind engineer is said to be utilizing GenAI to create actual physical materials.
Orbital Materials uses new technologies and LLMs to develop novel green materials for clean water, air, and energy. Founded by Jonathan Godwin, he wrote in a blog post in 2023 that “dramatic innovation” was needed in the field of Material Sciences. He continued, “the global market for aviation fuel is projected to be ~$650bn in 2030, and we need a sustainable and, crucially, affordable alternative.”
He called the progress in AI for materials “breathtaking,” stating that the organization aims to take the principles from models like AlphaFold, ChatGPT, and Stable Diffusion and adapt them to their uses.
As a result, the company is said to have developed a foundational model for atoms that can generate materials for applications it has never seen before. Its first target is producing materials relating to carbon capture, sustainable aviation fuel and the removal of harmful chemicals from the environment.
However, according to Dezeen, long-term plans include working on materials for architecture and design, such as lightweight alloys for cars and smart concrete.
Orbital Materials’ AI model
Speaking to TechCrunch, Godwin said, “Technical decision-makers at chemistry and materials companies struggle to develop new products because traditional methods of discovering new advanced materials are too slow and expensive to meet this demand.
“[Yet] demand for new advanced materials  … is growing hugely as our economies become electrified and de-carbonized,” he added.
While there have already been projects related to materials research and development, Godwin claims that its proprietary AI model for materials science distinguishes it from others. The model, named Linus, is reportedly inspired by large language models and AlphaFold.
Godwin stated, “In these models, the really important thing is to get lots of different types of data: models like ChatGPT are trained on code, news articles, scientific text and encyclopedias. This diversity is one of the things that gives the models their remarkable capabilities.”
According to Godwin, Linus underwent training on an extensive dataset encompassing simulations and materials, spanning from batteries and semiconductors to catalysts and organic molecules.
The London-based startup has reportedly generated a cheap, more reliable filter for capturing carbon dioxide from the air, with more details expected to be announced later this year. In 2023, Orbital Materials raised a $4.8M seed round from Fly Ventures, Compound, Flying Fish Partners, Character, and Mustard Seed Maze.
Featured image: DALL·E
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