Podcast Summary
The Importance of Real-Time Internet Connection for Large Language Models: Staying connected to the Internet in real-time is crucial for large language models to provide accurate and up-to-date information, making them valuable tools for knowledge workers.
Large language models, such as those offered by Microsoft, OpenAI, and Google, are marketed as being connected to the Internet, allowing them to provide real-time information. This feature is crucial for individuals and businesses looking to stay informed and competitive. Jordan Wilson, the host of Everyday AI, discussed this topic on a recent episode, explaining that these models are integrated with the companies' search engines (Bing for ChatGPT, Google for Google Gemini, and Microsoft's own for Copilot). By doing this comparison, Wilson aimed to demonstrate the importance of being connected to the Internet in real-time when using large language models, as it can lead to more accurate and up-to-date information. This connection is essential for knowledge workers, as it enables them to stay informed and productive in their day-to-day tasks. However, some may be hesitant to adopt these models due to concerns about potential inaccuracies or "hallucinations." Addressing this concern, Wilson emphasized that being connected to the Internet in real-time can help mitigate these issues and improve the overall output of the models. Therefore, the takeaway is that the Internet connection of these large language models is a significant advantage, making them valuable tools for individuals and businesses looking to stay informed and competitive in today's digital landscape.
Understanding the limitations of generative models with internet access: Generative models like ChatGPT can produce new content based on prompts but have limitations, such as varying results, outdated knowledge cutoff, and apparent vs actual internet connectivity.
Large language models like ChatGPT are generative, meaning they produce new content based on given prompts, and the results can vary. They are not deterministic. This is important to remember when using these models for information retrieval, especially when using features like "Browse with Bing" in ChatGPT Plus. The knowledge cutoff, which determines the latest information the model has access to, is also a factor. OpenAI recently updated the cutoff from April 2023 to December 2023. For industries with rapid change, using an outdated knowledge cutoff could lead to inaccurate information. Moreover, the ability to connect these models to the internet to retrieve information is crucial, making them almost like a mini Retrieval-Augmented Generation (RAG) system. However, there's a difference between models with internet access and those that only appear to have it. For instance, "Browse with Bing" in ChatGPT might not always take users to the intended URL, instead querying the words in the URL and returning the closest match. In contrast, a paid version feature like "Web Reader GPT" allows users to visit a specific URL directly. It's essential to be aware of these differences and understand the limitations of these models to ensure accurate and up-to-date information. The distinction between apparent and actual internet connectivity is crucial for users to make informed decisions and trust the outputs they receive.
Comparing Microsoft Copilot, Bing, and Google Gemini's performance: Microsoft Copilot, a free GPT-based AI model, performs similarly to paid versions of Bing and Google Gemini, but their results may differ due to the free vs. paid plans and recent updates.
During a discussion on various AI models and their capabilities, it was noted that Microsoft Copilot, which uses the GPT technology, performed similarly to paid versions of other models like Bing and Google Gemini. However, it's important to keep in mind that Microsoft Copilot is the only free version being used, while the others are on a paid plan. Additionally, Bing, which is in its default mode, recently underwent an update and now sources and cites information more accurately. The discussion involved giving each model the same task, asking them to describe a podcast called "Everyday AI," and evaluating their responses based on accuracy. The models varied in their responses, with some providing correct answers and others requiring further improvement. Overall, the conversation emphasized the importance of being connected to a large language model and the potential benefits of using paid versions for more accurate and reliable results.
Effective communication with AI models requires priming, prompting, and polishing: Improve interaction with AI models like ChatGPT and Microsoft Copilot by priming correctly, prompting effectively, and polishing responses.
Effective communication with AI models like ChatGPT and Microsoft Copilot relies on proper priming, prompting, and polishing. Lindy, an educational consultant, discovered this after taking the PPP (Priming, Prompting, Polishing) course and realizing she had been priming incorrectly. The course helped her improve her interaction with these models. Both ChatGPT and Microsoft Copilot provided valuable responses, with the latter even scraping testimonials from their website. However, in a test, none of the models correctly identified the number of episodes in the Everyday AI podcast by Jordan Wilson. While ChatGPT came close with 246 episodes, and the default mode and web reader models failed, Google Gemini acknowledged the challenge of providing an exact episode count. Overall, the importance of priming, prompting, and polishing in communicating with AI models cannot be overstated. If you're interested in learning more, sign up for the free PPP course at podpp.com.
Large language models can make significant errors: While helpful, large language models can make mistakes and their outputs should be cross-checked with reliable sources.
While large language models like ChatGPT and Microsoft Copilot can provide useful information and complete tasks, they are not infallible and can make significant errors. In the discussion, it was shown that both models had difficulties accurately determining the number of episodes in a podcast and listing the top 5 companies in the US by market cap. These errors could have serious consequences if the information was relied upon blindly. It's important to understand the limitations of these models and to cross-check their outputs with reliable sources. Additionally, the discussion highlighted the importance of staying informed about the latest market cap rankings as it can significantly impact investment decisions.
AI models find largest US companies by market cap: Google's Gemini and Microsoft's Copilot identified the five largest US companies by market cap, with Copilot providing additional price information.
During a test of various AI models' abilities to find information, both Google's Gemini and Microsoft's Copilot were successful in identifying the five largest companies in the United States by market cap. However, while Copilot provided the prices along with the names, Gemini did not. In the next tests, ChatGPT and Web Reader 1 were also able to correctly identify the most recent episodes from specific pages. Gemini, however, encountered difficulties in directly accessing the page due to dynamic content. Overall, all models passed the tests, but Copilot provided slightly more comprehensive results.
AI models struggle to extract information from PDFs: None of Google, Google Gemini, Microsoft Copilot, or the default browse with Bing were able to accurately extract specific information from a PDF file during the test.
While various search engines and AI models have their strengths, none of them were able to accurately extract specific information from a PDF file during the test. Google, Google Gemini, Microsoft Copilot, and the default browse with Bing all failed to some extent. Google, being the most disappointing as it claimed to be internet connected but couldn't access the web page linked to the PDF. The test involved asking the models to identify the favorite food of a person named Jordan mentioned on page 23 of a 41-page PDF. The default browse with Bing could not access external links directly, while Google and Microsoft Copilot attempted to derive information in different ways, with Copilot providing an incorrect answer. The GPT version of ChatGPT was the only one that was able to successfully read and understand the information from the PDF when given access.
Study finds web-connected large language models outperform offline ones: A study showed that a web-connected ChatGPT outperformed other large language models due to access to up-to-date information, highlighting the importance of internet connectivity for these models' effectiveness.
In a recent unofficial study, it was found that some large language models perform better than others when connected to the Internet. The study compared the performance of ChatGPT, Google Gemini, Microsoft Copilot, and a web reader version of ChatGPT. The results showed that the web reader version of ChatGPT, which has access to up-to-date information from the Internet, outperformed the other models with a score of 4 out of 5. In contrast, the default modes of ChatGPT and Google Gemini scored 2 out of 5, and Microsoft Copilot scored 3 out of 5. The importance of having access to up-to-date information for large language models cannot be overstated, as they are becoming increasingly integrated into various aspects of our daily lives and work. In the coming weeks, months, quarters, and years, we can expect to see more and more announcements about the integration of large language models into our desktops, operating systems, and other business applications. Therefore, understanding how these models work and the importance of having access to up-to-date information is crucial for individuals and organizations that want to stay competitive and make the most of these powerful tools.
Exploring AI limitations and potential risks: AI models like ChattGPT, Gemini, and Copilot can sometimes generate incorrect or outdated information, leading to mistakes. Implement safeguards like fact-checking and up-to-date information to decrease occurrences. Users should be aware of limitations and not rely solely on AI output without verification.
While we're seeing incredible advancements in AI technology, it's crucial to understand the limitations and potential risks. In today's discussion, we explored how AI models like ChattGPT, Gemini, and Copilot can sometimes generate incorrect or outdated information, leading to "hallucinations" or embarrassing mistakes. The hosts emphasized the importance of implementing safeguards such as fact-checking and providing access to up-to-date information to decrease the likelihood of such occurrences. They also highlighted the need for users to be aware of these limitations and not rely solely on AI output without verification. If you found this information valuable, please share it with your network. Don't forget to sign up for the free daily newsletter on everydayai.com for more AI insights. Remember, while AI is a powerful tool, it's essential to use it responsibly and with a critical mindset. Stay informed and keep pushing the boundaries of what AI can do – we'll see you next time! If you enjoyed today's episode, please subscribe and leave a rating. Your support helps us continue bringing you daily AI insights. For more AI magic, visit everydayai.com and sign up for our daily newsletter. Break some barriers, and we'll see you next time!
