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- ❤️🔥Valentine’s Special: AI Causes Trouble In Paradise
❤️🔥Valentine’s Special: AI Causes Trouble In Paradise
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Today we will discuss-
👨🏻💻Nvidia CEO calls for sovereign AI infra
😧AI chatbots make wild Super Bowl claims
💘McAfee study reveals AI's impact on online dating
🤩9 amazing AI tools you might not have heard of
All this and more - Let's dive in!
👩🍳What’s cooking in the newsroom?
Nvidia CEO Huang urges nations to develop independent AI infrastructure
💁🏻♂️News - During the World Government Summit in Dubai on 12 February, Nvidia CEO Jensen Huang said that every country should build its own artificial intelligence infrastructure.
He stressed that doing so is important for both economic growth and protecting each country's culture, cautioning against allowing others to control the technology.
🤓 Important takeaways from Huang's speech -
Huang, whose company's market value has soared to $1.73 trillion because of its leading position in high-end AI chips, stated that Nvidia is making AI more accessible by rapidly improving AI computing efficiency.
The CEO pointed out that some entities are spreading fear and misinformation about this new technology, hoping to discourage others from taking action and convince people to rely on them to handle it.
Additionally, he addressed concerns about AI dangers, suggesting that similar worries have been effectively managed in other industries like automobiles and aviation.
In his closing remarks, he urged listeners to take proactive steps, underlining that the future success of various industries hinges on embracing AI in a world that is becoming increasingly dependent on this technology.
Google and Microsoft chatbots cause chaos with made-up Super Bowl misinformation
🤖News - In another instance of AI misinformation, Google's Gemini chatbot, previously known as Bard, provided false information by claiming that the 2024 Super Bowl had already taken place on 10 February, 2024.
According to a Reddit thread, the GenAI model responded to questions about Super Bowl LVIII, complete with made-up statistics about the game.
🫣What did the chatbot say? Gemini displayed a preference for the San Francisco 49ers, stating that they defeated the Kansas City Chiefs with a score of 34-28 in the Super Bowl.
However, it wasn't alone. Microsoft's Copilot chatbot also leaned towards this narrative, claiming that the 49ers emerged victorious with a final score of 24-21, and even provided false citations to back up the claim.
😅In conclusion - While the situation may seem trivial and may possibly be resolved by now, it highlights significant limitations of current GenAI models.
Moreover, the fact that the chatbots couldn't have been more wrong (sorry, San Francisco fans) serves as a stark reminder to double-check statements from GenAI bots, as they don't comprehend concepts of true and false like humans do.
Study: Indians embrace tech for love, but crave authenticity
👩❤️👨News - According to a recent ‘Modern Love’ study by McAfee, 77% of Indians have come across bot profiles or AI-generated images on dating apps.
The study, which polled 7,000 people across seven countries, including India, reveals how AI is increasingly shaping online dating.
⭐Interesting points to note -
26% of respondents had unknowingly conversed with AI-generated bots instead of real people.
65% of Indians admitted to having used AI tools, like ChatGPT, to improve their profiles or create messages in online dating.
As Valentine’s Day approaches, 56% of Indians were considering using AI to compose messages for their romantic interests, highlighting a growing trend in seeking AI assistance for relationship communication.
However, 60% of recipients expressed mixed feelings, acknowledging the possibility of feeling hurt or offended upon learning that their Valentine’s messages were written by machines.
💔 Bottom line - While AI offers limitless possibilities, it also brings challenges, including the risk of feeling disconnected in an increasingly automated dating environment.
👩🏼💻What else is happening?
😸Technical jargon simplified
Natural Language Generation (NLG) - It is a process that makes machines write or speak in a way that sounds like humans. It's used for things like creating reports, product descriptions, or personalized messages automatically.
Backpropagation - It is a way to teach a computer how to do something by telling it what it did wrong and how it could fix the mistakes.
Entity Extraction - It is the process by which computers identify and categorize specific pieces of information, such as names, dates, locations, or other relevant data, from text or speech. It is used by search engines to understand queries, and chatbots to interact with humans.
👩🏼🚒Discover mind-blowing AI tools
Gummy Search - Allows users to find, organize, and search communities on Reddit
Artisse - An innovative AI-powered photography app that allows users to create personalized and hyper-realistic self-photos
DraftsAI - An AI-powered SEO engine that helps users grow their website's organic traffic
Unreal Speech - A text-to-speech tool that offers a cost-effective solution for converting text into spoken audio
Avaturn - Allows developers to create realistic and customizable 3D avatars for their metaverse, game, or app
Raplyrics - A website that uses Artificial Intelligence to generate unique and original rap music punchlines
Frederick - An AI-powered tool designed to help startups validate their ideas
Personamo - A tool that allows users to control their feed algorithms and customize their news feeds
JustFive - A fitness app that offers quick and efficient five minutes daily workouts
💡Prompt engineering tips
Experiment with prompt formats - The way you phrase your prompt can affect the results you get. Try different formats, such as questions, statements, or instructions, to see what works best for your specific needs.
Give examples - Offering examples within your prompts can affect the results you get. For instance, if you're seeking a captivating slogan for a fast-food brand like McDonald's, you could ask ChatGPT to "help me create a memorable slogan, like 'I'm lovin' it.'"
Limit unnecessary details - Avoid overloading the model with unnecessary details. While context is significant, it is also important to not overwhelm the model with excessive background information that might divert its focus.
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