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What are the latest trends in artificial intelligence for 2025?

Last Updated: 28.06.2025 04:08

What are the latest trends in artificial intelligence for 2025?

Multimodal AI can perform more complex tasks and make more accurate predictions than unimodal AI systems, which only process one type of data.

Examples of AI agents include personal assistants, chatbots, surgical robots, and generative AI.

An artificial intelligence (AI) agent is a software program that can interact with its environment, collect data, and use the data to perform self-determined tasks to meet predetermined goals

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AI-powered chatbots on company websites that can address inquiries, offer assistance, and provide personalized solutions

News and sports:

Siri is a virtual assistant that uses voice recognition and artificial intelligence (AI) to perform tasks for users. It's available on Apple devices like iPhones, iPads, Macs, Apple TVs, and Apple Watches.

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Demand prediction:

Google Assistant is a virtual assistant software application developed by Google that is primarily available on home automation and mobile devices. Based on artificial intelligence, Google Assistant can engage in two-way conversations, unlike the company's previous virtual assistant, Google Now.

Reminders and alarms:

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This can increase opportunities for seamless interaction with virtual agents.

Multimodal AI is a type of artificial intelligence (AI) that can process and integrate multiple types of data, including text, images, audio, and more.

Google Assistant:

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Customer service:

Some of the latest AI trends in 2025 include generative AI, AI agents, multimodal AI, quantum computing, and edge computing.

Find the weather, traffic, directions, nearby attractions, and more

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Examples of Google Assistant tasks

Generative AI

1. Generative AI :

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Control your smart home devices

Retail:

AI can understand both the words and emotions of customers

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Set reminders and alarms

An AI-powered personal assistant from Amazon that can play music, control smart devices, and answer questions

Quantum algorithms can tackle complex optimization problems, like finding the best route in logistics or optimizing investment portfolios, by exploring multiple solutions simultaneously due to superposition.

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Home automation:

Exercise:

Launch apps, perform tasks, and access content

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Packages:

Most current quantum AI applications use a hybrid model, where classical computers handle data preprocessing and post-processing while utilizing quantum computing for the computationally intensive core calculations.

Quantum systems are susceptible to noise, which can affect computation accuracy, requiring robust error correction methods.

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AI-powered chatbots in healthcare that can guide patients through insurance claims and manage prescription refills

These agents can enhance output and decision-making in sectors like banking and healthcare.

Amazon's Alexa is a virtual assistant that uses artificial intelligence (AI) to understand and respond to voice commands. Alexa uses natural language processing, machine learning, and other AI technologies to perform tasks.

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Edge computing in AI, also known as Edge AI, is the use of AI algorithms and models on local devices instead of in the cloud. This allows devices to process data quickly and make decisions in real time.

Local information:

Get news updates and sports scores

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Environmental management:

AI can help customer service agents by accessing and synthesizing information quickly.

Key points about Quantum Computing AI:

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Real-time processing:

Breaking current encryption methods by factoring large numbers efficiently using Shor's algorithm, while also developing new quantum-resistant encryption techniques.

Multimodal AI is expected to become even more powerful and transformative in the future.

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This can revolutionize content creation in marketing.

Drug discovery:

AI can analyze data to forecast future fashion trends.

Quantum computers can process information exponentially faster than classical computers for specific tasks.

5. Edge computing :

By simulating molecular interactions with high accuracy, quantum computers can help identify potential drug candidates faster and more effectively.

Surgical robots

Fashion trend forecasting:

An AI-powered personal assistant from Apple.

Generative AI is a type of artificial intelligence (AI) that can create content, analyze data, and perform other tasks. Some examples of generative AI include:

AI can monitor and manage pollution and natural disasters.

AI can identify new drug candidates by analyzing large amounts of data.

Intuitive Surgical's da Vinci, a surgical system that provides precision and control in surgeries beyond human capabilities

Google Gemini:

Computer vision can analyze medical images while NLP processes patient records

Multi-agent collaboration

An AI chatbot that can interact with users in natural language. Users can ask it questions, request text in different styles, and more.

AI agents can perform tasks like IT troubleshooting and workflow optimization.

DALL-E:

Customer service:

2. AI agents

AI can analyze historical data and trends to predict demand for products.

Can be controlled with voice commands to perform tasks like playing music, providing information, and adjusting the lighting

Material Science:

An image generator that can create detailed images based on text descriptions. It uses neural networks and deep learning algorithms.

Examples of multimodal AI

Hybrid Approach:

Cryptography:

Potential applications

Video game development:

Personal assistants

Multimodal AI can enhance user experiences by enabling more natural interactions. For example, users can upload photos or audio clips to get help troubleshooting or find recipe ideas.

Banking chatbots:

Generative AI can help businesses save time and money by automating tasks like content creation and data analysis.

Early Stage Development:

An AI-powered personal assistant that can understand needs and respond accordingly

Noise and Error Correction:

Important Considerations:

Quantum computers can simulate complex quantum systems much more efficiently than classical computers, enabling detailed modeling of molecules, materials, and other phenomena crucial for research and development in fields like chemistry and materials science.

Search:

Answer questions using Google search

Healthcare:

Multimodal AI models can take many types of data as input.

Enhanced Simulation Power:

Quantum computing is a multidisciplinary field comprising aspects of computer science, physics, and mathematics that utilizes quantum mechanics to solve complex problems faster than on classical computers. The field of quantum computing includes hardware research and application development.

Can receive a photo and generate a written recipe, or vice versa.

Financial Modeling:

Get a summary of your exercise activity

3. Multimodal AI

AI can create game environments, characters, and storylines.

Apps:

Example Applications:

AI-powered chatbots that can provide personalized responses to customers.

Quantum computing technology is still in its early stages, and building large-scale, commercially viable quantum computers is a significant challenge.

ChatGPT:

Chatbots

Optimization Problems:

Key points about edge computing in AI:

4. Quantum computing

Drug Discovery:

Alexa:

Smart shopping assistants can see and respond to products that customers are interested in.

To use Google Assistant, you can say "Hey Google" followed by your request. For example, you can say "Hey Google, set the temperature to 75 degrees".

A branch of artificial intelligence that creates new realistic and creative materials

Optimizing investment portfolios and assessing risk more accurately by leveraging quantum algorithms to analyze complex financial data.

AI-powered tools like OpenAI's GPT-4 can create content like text, images, and videos.

Google Assistant

Track packages online

Siri:

Amazon's Alexa and Google Assistant:

Designing novel materials with desired properties by simulating their atomic structure at a quantum level.

These are discussed here.

A dynamic process that brings together agents from multiple business functions to achieve a common objective

Because data is processed close to its source, edge computing enables fast, near-in...