ChatGPT-Style AI Search Engines Could Cost Google, and Microsoft Billions in Computing Cost

ChatGPT-Style AI Search Engines Could Cost Google, and Microsoft Billions in Computing Cost

The previous look of the alphabet in chatbot flub helped erase $100 billion from its market value. Here in this category, one of the major challenges that aroused is emerging from its efforts to make the inclusion of generative artificial intelligence in its popular Google Search.

As per the startup’s Chief Executive Sam Altman, the executives of the technical department are considering all the facts that are related to how to operate AI like ChatGPT while accounting for the high expense. ChatGPT from OpenAI enables drafting prose and answering search queries. The platform has eye-watering computing costs of a couple or more cents per conversation.

In an interview session, Alphabet’s Chairman John Hennessy communicated that the company is having an exchange with AI known as a large language model likely cost which is 10 times more than a standard keyword search. The availability of the fine-tuning will be helpful in reducing the expense quickly.

After the attainment of the adequate amount of revenue from potential chat-based search ads, the technology has the capability to chip into the bottom line of Mountain View. Its net income is around $60 billion in 2022.

Morgan Stanley had made the estimation that Google’s 3.3 trillion search queries last year cost roughly a fifth of a cent each. This is going to increase the number that is depending on how much text AI must generate. Google could face a $6 billion (roughly Rs. 49,742 crore) increment in the expenses by 2024. Google has a requirement to handle navigational searches for sites.

For instance, SemiAnalysis, a research and consulting firm is focusing on chip technology which is mentioned by the ChatGPT-style AI to search could cost Alphabet $3 billion (roughly Rs. 24,870 crores), an amount limited by Google’s in-house chips called Tensor Processing Units, or TPUs, along with other optimizations.

It is a matter of consideration that this form of AI is quite costlier than conventional search is the computing power involved. AI is dependent on billions of dollars of chips, a cost that has to be spread out over their useful life in several years. Electricity is inclusive of all the costs and pressure on companies with carbon-footprint objectives.

The process of handling AI-powered search queries is popularly known as “inference,” in which a “neural network” is loosely modelled on the human brain’s biology.

Google’s web crawlers have already scanned the internet to compile an index of information. When a user types a query, Google serves up the most relevant answers stored in the index.

Alphabet’s Hennessy said that the cost of the inference has to drive down and they are termed as a couple of year problems at worst.

Alphabet is presently facing pressure to take on the challenge regardless to be worrying about the expenditures. Earlier this month, its rival Microsoft held a high-profile event at its Redmond, Washington headquarters is making a plan to embed AI chat technology into its Bing search engine. The top executives are having an objective to Google’s search market share by 91%.

Alphabet had made a discussion about its plans to improve its search engine, but a promotional video for its AI chatbot Bard has revealed that the system is answering a question in an inaccurate manner, fomenting a stock slide that shaved $100 billion off its market value.

Microsoft later drew the scrutiny of its own when the AI made threats or professed love to test users, prompting the company to make the restriction of long chat sessions it said “provoked” unintended answers.

Microsoft’s Chief Financial Officer, Amy Hood has told that the upside from gaining users and advertising revenue outweighed expenses is launched to millions of consumers.

The CEO of search engine Richard Socher said that an AI chat experience along with applications for charts, videos and other generative tech raised expenses between 30% and 50%. He also mentioned that the technology gets cheaper at scale and over time.

Footing the bill is one of main reasons why search and social media giants with billions of users have not yet launched an AI chatbot overnight.

He also mentioned that one is accuracy, and the second is you have to scale this in the right way.

Written by Srikanth

Passionate Tech Blogger on Emerging Technologies, which brings revolutionary changes to the People life.., Interested to explore latest Gadgets, Saas Programs

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