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HomeTechnology peripheralsAIAnother generative AI assistant will be 'on board'! Google releases multi-modal Bard assistant, is the era of interactive AI approaching?

On October 6, Google officially released the new generation of Android flagship phone Pixel 8/Pro series at a new product launch conference. This phone is equipped with a Tensor G3 chip, which can run more complex machine learning models and adds a number of artificial intelligence enhancements to the new phone. For example, it can read web content to users in different languages ​​and in a more natural voice, making the virtual assistant's conversations more natural and smooth

Pixel 8 Pro is the first phone to be able to run Google's basic large model directly on the device, which Google points out is 150 times more computationally intensive than the largest ML model on Pixel 7

Google announced the launch of “Assistant with Bard”, available on Android and iOS devices. The assistant combines the personal assistant function of the mobile phone with generative artificial intelligence. Users can interact with the Bard Assistant through text, voice or images, which means it has multi-modal functionality

When a user asks "What important emails did I miss this week?", Bard Assistant will provide the following services: First, it will list the key points and specific content, and provide links to the corresponding emails. In addition, it can also help users extract active addresses and display them in Google Maps

Another generative AI assistant will be on board! Google releases multi-modal Bard assistant, is the era of interactive AI approaching?

If the user wants to post a photo of a puppy to social media, he only needs to summon the Bard Assistant floating dialog box and ask him to write the posting content. The Bard assistant will recognize the image and write the corresponding content.

Another generative AI assistant will be on board! Google releases multi-modal Bard assistant, is the era of interactive AI approaching?

Google said it will soon roll out Bard Assistant to early testers to get feedback and launch it to the public in the coming months.

In addition, Mustafa Suleyman, co-founder of DeepMind, said in a recent interview that the current generative AI is only a transitional technical stage, and will next enter the era of interactive AI. AI will arrange tasks according to the different task needs of users. Other software and or contacting real people to get the job done.

He believes that the first wave of AI mainly focuses on classification - deep learning shows that humans can train AI to classify input data such as images, videos, audios, and languages. Humanity is currently in the second wave of "generative AI", which means "input data and generate new data." The third wave in the future will belong to "interactive AI". "Dialogue is the interactive interface of the future." Users not only click buttons and type text, but directly talk to AI. By then, interactive AI will be able to take independent actions. action.

Tianfeng Securities stated that the importance of scenarios in the implementation stage of C-end artificial intelligence applications has become more prominent. Scenarios such as chat robots, artificial intelligence companions, and content production tools are the first to be implemented. The development speed of artificial intelligence applications in these scenarios is as high as Commercialization progress may exceed expectations

Analysts predict that AI iteration and later event catalysis will continue to accelerate. Starting from the second half of the year, overseas giants’ application and model iteration speed will increase significantly. The capabilities of general chatbots are expected to be further strengthened, which may lead to the improvement of user experience and further increase in the number of users. increase.

In addition, Huajin Securities added that the shift of large models from general to vertical scenarios is more of an exploration of commercialization and is the driving force for large models to move from training to inference. With the development and improvement of vertical large models, the application of large models is the key to opening up greater room for growth. Edge computing is a clear and huge incremental market, and it has now reached the stage of industry implementation. Cloud computing companies, telecom operators, equipment manufacturers, CDN companies, etc. are all actively promoting the implementation of the industry.

[Source: Science and Technology Innovation Board Daily]

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