Podcast Summary
Google's New AI Chat Model: Gemini Advanced: Google's new AI chat model, Gemini Advanced, boasts advanced capabilities and competes with ChatGPT. MidJourney expands access to its AI image generator and considers banning political images, while the FTC bans AI robocalls.
Google has recently released an advanced version of their AI chat model called Google Gemini Advanced. Jordan Wilson from Everyday AI discusses seven key things to know about this new release, which includes its potential as a ChatGPT competitor and its super advanced capabilities. However, the naming mechanism of Google's AI products, with versions labeled as Ultra and Advanced, can be confusing. Before diving into Google Gemini Advanced, the Everyday AI team starts with AI news. MidJourney, a popular AI image generator, is expanding access to its alpha website and considering banning political images to prevent the spread of disinformation. The FTC has also banned AI robocalls. Everyday AI is a valuable resource for those interested in generative AI, offering a free daily newsletter and extensive learning materials on their website.
FCC Bans AI-Generated Robocalls, OpenAI Developing Autonomous Agent Software: The FCC now has the power to fine companies for AI-generated robocalls and block their service providers. OpenAI is creating agent software that can autonomously complete tasks, potentially revolutionizing business automation.
The Federal Communications Commission (FCC) in the US has made a historic decision to outlaw AI-generated robocalls under the Telephone Consumer Protection Act. This ruling empowers the FCC to fine companies and even block their service providers, giving call recipients the right to take legal action and potentially recover up to $1,500 in damages per unwanted call. Simultaneously, OpenAI is reportedly working on a new product that could revolutionize business automation. They're developing agent software that can autonomously complete tasks by taking control of a user's device or performing actions on the web. This product, which could fill gaps in enterprise apps where APIs are not currently available, could significantly impact various industries and faces competition from other tech giants. While Gemini is not a chatbot killer, it's essential to stay informed about these game-changing advancements in AI.
Google Renames and Upgrades Its Large Language Model to Google Gemini: Google has updated its language model, now called Google Gemini, with free and paid versions, including a more capable AI model called Ultra for complex tasks. It will be integrated with Google's productivity tools like Gmail and Docs.
Google has updated its large language model, previously known as Google Bard, and renamed it Google Gemini. There are now free and paid versions available, with the paid version, Google Gemini advanced, using a more capable AI model called Ultra. Google claims this model offers state-of-the-art performance for complex tasks and will be integrated with platforms like Gmail and Docs in the future. However, the naming and branding changes can be confusing, with free Google Gemini using the Pro model and Google Gemini advanced using the Ultra model. It's important to note that the marketing language used by Google may not accurately reflect the capabilities or limitations of the new models. Overall, while Google Gemini is not expected to replace ChatGPT or other large language models, it does offer improved performance for complex tasks and integration with Google's suite of productivity tools.
Google's new feature Gemini Advanced acts as a personal tutor for advanced coding scenarios but with limited availability: Google's Gemini Advanced, a new feature, functions as a personal tutor for complex coding scenarios, but its accessibility is restricted and eligibility criteria are not clear.
While Gemini Advanced, a new feature from Google, has the potential to act as a personal tutor or sounding board for advanced coding scenarios, it's not yet available to all Workspace users. The eligibility criteria are not straightforward, and users may need to have a Ph.D. and navigate through multiple clicks to find out if they're eligible. Additionally, it's currently not available in some countries for work accounts or for users under a certain age. For those who do have access, Gemini Advanced offers more personality than other large language models, making the interaction more enjoyable. However, its availability is limited, and users may find it more challenging to access than other Google products.
Understanding Google Gemini: A Confusing Process: Google Gemini's availability and features have been unclear to many users, leading to frustration and difficulty accessing the product. Google should improve communication and make the process more transparent for all users.
The process of accessing and understanding the availability and features of Google's new language model, Google Gemini, has been confusing and difficult for many users, particularly those using Google Workspace accounts. Users have reported having to click through multiple layers of menus and settings to even find out if they have access to the product, and the lack of clear communication from Google about the requirements for access has added to the frustration. Additionally, the identity of the product itself seems unclear, with some users reporting that certain features or products with the name "Gemini Advanced" do not actually exist. This lack of transparency and clarity can hinder productivity and adoption of new tools, especially in a business context where time and efficiency are crucial. Google, known for its user-friendly interfaces, should strive to make the process of accessing and understanding new products more straightforward and accessible to all users.
Discussion on Gemini Advance's limitations: Despite its advanced capabilities, Gemini Advance failed to accurately discuss its own features and capabilities, highlighting the need for clear system prompts and effective Internet querying to ensure accurate information.
The large language model, in this case, Gemini Advance, failed to provide accurate and relevant information about its own platform during a discussion. The model appeared to be unaware of its capabilities and even hallucinated information during the conversation. This issue is significant because the primary use of such models is to assist users with specific tasks and provide accurate information. Furthermore, the model's inability to use the Internet effectively to retrieve up-to-date information was a major drawback. This is particularly concerning since competitors like ChatGPT were able to provide more accurate and comprehensive responses. The solution to this issue lies in ensuring that the model has a clear and concise system prompt that reminds it of its capabilities, what it can do, and what it's meant to assist with. Additionally, improving the model's ability to query the Internet effectively would help ensure that it provides accurate and up-to-date information to users. Overall, the discussion highlights the importance of ensuring that large language models are well-equipped to handle tasks and provide accurate information, particularly when they are being used for professional purposes. The failure of a model to do so can lead to confusion, inefficiency, and even significant errors.
Google's Gemini AI model faces challenges with real-time events and accuracy: Google's Gemini AI model needs improvements in real-time data, transparency, and accuracy to provide reliable information.
While Google's new AI model, Gemini, shows promise, it currently struggles with real-time events and providing accurate information. During a comparison with ChatGPT, it was clear that Gemini lacked transparency and provided false information regarding the teams playing in the Super Bowl and the winners of the US primary election in New Hampshire. These errors highlight the need for improved QA processes and a stronger focus on real-time data and situational awareness. While Google's Gemini may hold great potential, it's essential to remember that facts are crucial, and accuracy is key.
Gemini's struggles with real-time events and reasoning: Gemini, despite Google search integration, fails to provide accurate real-time event information and struggles with simple queries involving jokes. Some users suggest it may be more about ad revenue than enhancing AI.
Despite Gemini's integration with Google search, which is known for its superior capabilities, Gemini is currently struggling with real-time events and reasoning and logic. This was evident in several examples discussed, where Gemini failed to provide accurate information about recent events or answer simple queries involving jokes. Additionally, some users have suggested that Gemini's integration with Google search may be more of a marketing ploy to generate ad revenue rather than enhancing its AI capabilities. Overall, while Gemini has some advantages, particularly in areas like coding, it is not yet living up to the expectations of being a chatbot killer or providing significant improvements over existing AI models like ChatGPT.
Comparing AI models: Gemini vs ChatGPT: Despite advancements, large language models like Gemini and ChatGPT have issues with accuracy and proper word understanding. Google and Gemini are working on digital watermarks to combat AI-generated misinformation, but more collaboration and development is needed.
Accurate information and proper word understanding are crucial aspects when working with large language models. These elements control the model's ability to provide relevant and meaningful responses. During a comparison between ChatGPT and Gemini, it was noted that both models had some issues. Gemini failed to provide complete jokes, while ChatGPT only gave the punchlines or setup. However, ChatGPT technically also failed by not providing the correct answers to some riddles. Another important consideration is the application of digital watermarks to AI-generated content, such as images, to prevent misinformation and deep fakes. Google and Gemini have taken steps in this direction, and it is a positive move towards addressing the issue of AI-generated content on social media platforms. Moreover, it is essential to acknowledge that while these models have made significant strides, they are not yet at par with industry leaders like DALL-E and Midjourney. The development of effective watermarking systems and collaboration between social media platforms and AI companies are necessary to combat the spread of AI-generated misinformation. In conclusion, the ability to provide accurate information and proper word understanding are essential for large language models to function effectively. While there have been advancements in this field, there is still a long way to go in terms of developing effective watermarking systems and preventing the spread of AI-generated misinformation.
Google's Gemini app outperforms GPT 4 on language understanding benchmark: Google's new Gemini app offers advanced language understanding capabilities, surpassing GPT 4 on a benchmark test before its public release, but initial rollout was criticized for misleading users about real-time interaction and human-like reasoning.
Google's new Gemini app, available on both Android and iOS, is a significant improvement over existing smart assistants like Siri and Alexa due to its superior language understanding capabilities, as demonstrated by its outperformance of GPT 4 on the Massive Multitask Language Understanding (MMLU) benchmark before its public release. However, Google's initial rollout of Gemini was criticized for being misleading, as it gave the impression of real-time interaction and human-like reasoning, which was not the case. Despite some initial hiccups, the integration of Gemini into Google apps is a step forward in making our digital assistants more intelligent and capable of understanding complex queries in real life situations.
Google Gemini Ultra: Initial Testing Suggests Limited Use Cases: Despite initial hype, Google Gemini Ultra's limitations in handling real-time events and integration with work tools make it questionable if it can surpass ChatGPT. Speaker sees no current use case and invites listeners for updates.
The new Google Gemini Ultra model, which was initially touted as being significantly ahead of competitors, may not be a ChatGPT killer based on initial testing. The speaker has signed up for a free trial and will continue to test the new model, but currently sees no use case for it due to limitations in handling real-time events and integration with Google Workspace. The speaker also notes that the model's performance in Google search and coding is good, but not superior to ChatGPT. The lack of practical applications and compatibility with work tools raises questions about the utility of the new model. The speaker invites listeners to keep tuned for updates and encourages them to sign up for Everyday AI's daily newsletter for more in-depth analysis.
