Post by account_disabled on Feb 17, 2024 9:21:14 GMT
The race in the field of artificial intelligence continues to intensify between Google and OpenAI. While OpenAI released GPT-4 a few months ago, Google introduced its "multimodal system" at the May 2023 Google IO conference: Gemini. This term, often associated with the Gemini constellation or the second space flight just before Apollo, stands for "Generalized Multimodal Intelligence Network" in Google's project. What do we know about Gemini? Google reportedly allowed several companies access to an early version of its Gemini system. Overview of what is filtered about this "multimodal system". “Imagine if the Hulk of the language models and Jarvis, Tony Stark's AI, had a child… Boom!” This is Gemini. " Online, tech fans are singing the praises of Google's generative AI system and making plenty of happy pop culture references. So how does the Gemini multimodal model work? What are its features? Does it deserve all the praise even before its release? The previous ChatGPT tends to convince us that nuance would be more appropriate: If OpenAI's generative model surpassed 100 million users by January 2023, its engagement stagnated in May and began to decline in June. Moreover, the OpenAI model is not risk-free and has even shown some signs of regression.
According to the Mountain View firm, Gemini is designed to be “multi-modal and highly efficient at integrating tools and APIs.” It is expected to "enable future innovations such as memory and planning." Gemini Development To develop this massive model, Gemini relies on the breadth and depth of data accumulated by Alphabet, especially through platforms such as YouTube, Google Books, Google Search and Google Scholar. It also makes latestdatabase.com use of state-of-the-art training chips called TPUv5, which is claimed to be the only chip worldwide that can run 16,384 chips together. Google's teams also trained the model using methods similar to those used in the development of AlphaGo, a game more complex than chess. Also, unlike Google's large spoken language model LaMDA, which was trained via supervised learning, Gemini was trained via reinforcement learning like GPT-3 and GPT-4. This machine learning technique involves an AI agent learning to perform.
a task through trial and error in a dynamic environment. According to The Information, several former members of the Google Brain and DeepMind teams are currently working on the project , including Google co-founder Sergey Brin . Additionally, according to the same source, Google may introduce Gemini as an update to Google Bard or by creating a new chatbot before using it to power various products such as Google Docs. Gemini may be released soon, possibly in response to OpenAI's GPT-4.5 release ahead of GPT-5, which is expected in early 2024. "Once refined and rigorously tested for security, Gemini, like the PaLM 2, will be available in different sizes and capacities," Google says, without providing further details. A Potentially Shortened User Journey Currently, Google SGE (Google's AI-enhanced search experience) is being tested in nearly a hundred countries. This version of Google offers AI-generated texts, resources, and a conversation module. For certain queries, this search engine may reduce the number of user queries. According to an example from Exposure Ninja, a user searching for information about “real estate attorney” for a move might make only four site visits instead of eight with a traditional search. User Search.png Source.
According to the Mountain View firm, Gemini is designed to be “multi-modal and highly efficient at integrating tools and APIs.” It is expected to "enable future innovations such as memory and planning." Gemini Development To develop this massive model, Gemini relies on the breadth and depth of data accumulated by Alphabet, especially through platforms such as YouTube, Google Books, Google Search and Google Scholar. It also makes latestdatabase.com use of state-of-the-art training chips called TPUv5, which is claimed to be the only chip worldwide that can run 16,384 chips together. Google's teams also trained the model using methods similar to those used in the development of AlphaGo, a game more complex than chess. Also, unlike Google's large spoken language model LaMDA, which was trained via supervised learning, Gemini was trained via reinforcement learning like GPT-3 and GPT-4. This machine learning technique involves an AI agent learning to perform.
a task through trial and error in a dynamic environment. According to The Information, several former members of the Google Brain and DeepMind teams are currently working on the project , including Google co-founder Sergey Brin . Additionally, according to the same source, Google may introduce Gemini as an update to Google Bard or by creating a new chatbot before using it to power various products such as Google Docs. Gemini may be released soon, possibly in response to OpenAI's GPT-4.5 release ahead of GPT-5, which is expected in early 2024. "Once refined and rigorously tested for security, Gemini, like the PaLM 2, will be available in different sizes and capacities," Google says, without providing further details. A Potentially Shortened User Journey Currently, Google SGE (Google's AI-enhanced search experience) is being tested in nearly a hundred countries. This version of Google offers AI-generated texts, resources, and a conversation module. For certain queries, this search engine may reduce the number of user queries. According to an example from Exposure Ninja, a user searching for information about “real estate attorney” for a move might make only four site visits instead of eight with a traditional search. User Search.png Source.