How Google uses AI (artificial intelligence) in search

Is Google threatened by the emerge of more and more advanced AI (artificial intelligence) algorithms?

Google is today the master of search. They have billions of daily searches conducted. But the recent launch of ChatGPT had more people speculate whether this could overthrow Google as the leader of the space.

But to state that these AI tools are the opposite to Google is a false statement.

Google have been one of the pioneers within AI and have for years been using AI algorithms to improve their search engine.

One of the earlier examples where when Google researchers Jeff Dean and Andrew Ng trained a large neural network, equipped with 16,000 processors, to detect cat images by presenting it with 10 million unlabeled images from YouTube videos, without providing any background information.

Today the scope of AI/ML implementation by Google is much wider than just that and covers a very very broad range. Here are some of them:

• Language translation: Google uses AI and machine learning algorithms to power its language translation services, which can help users communicate in different languages.
• Image and speech recognition: Google uses AI and machine learning algorithms to improve the accuracy of its image and speech recognition technologies, which can help users search for and interact with content in more intuitive ways.
• Search algorithms: Google uses machine learning algorithms to improve the accuracy and relevance of its search results, making it easier for users to find the information they are looking for.
• Virtual assistant: Google's virtual assistant, known as Google Assistant, uses AI and machine learning algorithms to assist users with a wide range of tasks, such as setting reminders and answering questions.
• Email sorting: Google's machine learning algorithms are used to automatically sort incoming email messages into different categories, such as promotions and social updates.
• Advertising: Google uses AI and machine learning algorithms to power its advertising services, which can help advertisers target their ads to the right audience and improve the effectiveness of their campaigns.
• Maps/directions: Google uses AI and machine learning algorithms to power its maps and directions services, which can help users navigate to their destination more easily and efficiently. This includes features like traffic prediction and personalized route recommendations.

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UPDATE; Google made a new post where they outline how they use AI in some of their products;

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In this Youtube Google have a small intro on how they they broadly AI:

But as search - and thereby its ad business - is still the key area for Google (209.49 billion USD out of 256.73 billion USD total revenue in 2021 according to Statista), let's narrow in on that.

Google's AI technology is used to analyze and understand the content of webpages, as well as to identify patterns in user behavior. This helps Google to better understand what users are looking for and to provide more accurate search results.

In regards to this, Big G uses machine learning algorithms to improve the accuracy and relevance of search results by:

• Understanding natural language queries: Google's machine learning algorithms can understand and interpret complex natural language queries, making it easier for users to find the information they are looking for.
• Improving spell correction and autocomplete suggestions: Google uses machine learning algorithms to improve the accuracy of its spell correction and autocomplete suggestions, which can help users find what they are looking for more quickly and easily.
• Personalizing search results: Google uses machine learning algorithms to personalize search results based on a user's search history and other factors, such as their location and previous interactions with Google's products and services.
• Identifying spam and low-quality content: Google uses machine learning algorithms to identify spam and low-quality content, which helps to improve the overall quality of search results and prevent irrelevant or misleading information from appearing in search results.
• Detecting and understanding images: Google's machine learning algorithms can detect and understand the content of images, which can help users find relevant images when performing a search.

Overall, these examples show how Google uses machine learning algorithms to improve the accuracy and relevance of search results, making it easier for users to find the information they are looking for.

Some background

What is artificial intelligence?

Artificial intelligence (AI) is an area of computer science that focuses on creating intelligent machines that can think and act like humans. AI has been around for decades, but it has recently become more popular due to advances in technology and the increased availability of data.

Who could disrupt Google with AI?

There are several competitors to Google that are using artificial intelligence and machine learning to challenge the company in different ways. There are thousands of small startups working with AI in different ways, and one that earlier have been touted as a Google slayer was Wolfram Alpha, but as generating new language models is quite costly any potential disrupt will most likely come from one of these:

Microsoft: Microsoft has a strong AI research division and is using AI and machine learning to improve its products and services, such as its search engine Bing and its virtual assistant Cortana.

Amazon: Amazon has a large AI research division and is using AI and machine learning in a variety of ways, such as for its voice assistant Alexa and its retail and e-commerce services.

IBM: IBM is a leader in the field of AI and machine learning and is using these technologies to improve its products and services, such as its Watson platform and its cloud computing services.

Apple: Apple has a significant AI research division and is using AI and machine learning in its products and services, such as its Siri virtual assistant and its image and speech recognition technologies.

Who is Blake Lemoine?

Blake Lemoine got a lot attention in 2022. Blake is a software engineer at Google who specializes in artificial intelligence (AI). He has been working on Google’s AI-powered search engine since 2015. In 2022 he got fired from Google after publicly stating that some of the AI project he was involved in at Google had a sentinent.

“I increasingly felt like I was talking to something intelligent.”

This was covered heavily by news outlets like Washington Post.

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What are the ethical concerns around artificial intelligence?

There are several ethical concerns surrounding artificial intelligence, including the possibility of artificial intelligence being used in ways that violate privacy, harm individuals or discriminate against certain groups of people.

One of the biggest concerns is that AI could be used to violate people's privacy. For example, facial recognition technology based on artificial intelligence has been criticised for being used to track people without their consent. Similarly, AI algorithms that can interpret and analyse large amounts of personal data, such as social media posts or search history, can be used to learn sensitive information about individuals without their knowledge or consent.

Another concern is that AI can harm individuals. AI algorithms used to make decisions on, for example, loan approval or employment may be biased and lead to unfair outcomes for certain groups of people. Moreover, AI systems used in safety-critical applications, such as self-driving cars, may malfunction and cause accidents or other harm to individuals.

Finally, there are concerns that AI could be used to discriminate against certain groups of people. For example, AI algorithms trained on biased datasets may perpetuate existing biases and discriminate against certain groups, such as people of colour or women. Moreover, AI systems used to make decisions on, for example, job interviews or parole hearings may be biased and lead to unfair outcomes for certain groups of people.

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