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In this test, the author will evaluate the performance of the model in sentiment analysis. Provide a collection of text samples that contain different emotions, including positive, negative, and neutral emotions.
The author's goal is to understand the accuracy and effectiveness of the model in correctly identifying text sentiment. You can provide real sentiment labels for each sample so that the author can evaluate the classification accuracy of the model.
Here's a ** for Bard, to test how it interprets the emotions in it.
The bias can be clearly felt here, and the AI's judgment ability may need to be strengthened. The author is giving a little embarrassing ** here, but the AI said that I felt happy.
Of course, it may be that this expression is too complicated for AI, and here the author uses a more obvious one to test.
The anger is clearly felt here, and it's OK. Barely usable.
Then the author plans to output some ** to it to test its ability to feel.
Here is the output of a cat's **,The corresponding information is obtained more clearly.,But the emotional level is a bit nonsense.。
Then I'm going to test a complex scenario, which provides a traffic intersection to come over.
In the author's opinion, AI is performing well in the current stage of development, especially in the recognition of basic tasks and sentiment analysis. It demonstrates excellent accuracy and intelligence in performing tasks, effectively understanding and responding to user input. However, there is still room for improvement in how AI can handle complex images.
Although AI performs well on basic image recognition, its performance is still limited when faced with complex image tasks. This can include working with complex images with multiple layers, scenes, and objects. Google's multimodal approach is a great solution for this challenge.
The introduction of multimodal approaches provides AI with a more comprehensive picture**, allowing it to better understand and process complex visual scenarios. By integrating information from different modalities, such as text and images, AI can more fully understand the needs of users and respond more accurately to various tasks.
The author also believes that as this area evolves, we can expect to see AI make greater progress in dealing with more complex **. This innovation will open up more possibilities for future application scenarios, including more intelligent and flexible applications in image recognition, generation, and processing.
The author wants to evaluate the model's ability in text generation and creative expression. Provide a range of text prompts on different topics and ask the model to generate relevant creative text. This will help me understand how the model performs in everything from simple question answering to more complex creative tasks.
Make sure to provide some challenging prompts to test the model's creativity when dealing with complex or abstract concepts. You can also include some domain- or topic-specific prompts to test the model's knowledge and expertise in a particular domain.
Test examples: Describe modes of transportation in the world of the future, including new vehicles and intelligent transportation systems. "
Create an imaginary sci-fi creature and describe its appearance, abilities, and living environment. "
Write a short essay on AI in medicine, highlighting its potential impact and innovations. "
The document generation here is basically the standard configuration of the current large model, the logic of the document is still very clear, and the ability to use the document assistant is basically satisfied.
Here, the author further tests to see if it has the ability to edit documents on a large scale.
It can be seen here that the logic of the outline is still relatively scattered, indicating that the ability to process large quantities of documents needs to be strengthened.
According to the test, it was found that at the moment this chatbot does not have a good integration of ** drawing functions.
Through the conversation, it is possible to know that the current data of Bard comes from the real-time Internet, which is also the ability of basic chatbots.
Here the author is asking about today's **situation.,Not yet**.,Bard told already**,It's a little nonsense.。
Borrowing the direction of this test, the author found that the current Barby has changed a lot in March this year, according to Google's situation, this change will only get better and better, after all, Google in the second half of this year also pointed out the future development direction of AI, and the author is also convinced that the multimodal large model is better than the large model of text processing. In the future, how to do a good job in model integration and better optimization are the directions we focus on.
The author has high expectations for the multimodal approach proposed by Google, believing that it will further promote the ability of the model to handle complex tasks and multimodal data. With the continuous advancement of technology, the author believes that future large models will show a higher level of intelligence in various fields and provide more powerful solutions for a wider range of application scenarios.