11 Examples of AI Used in Sustainability
What is AI Marketing: Use Cases, Tools & Trends in 2025
Marketers can use AI in multiple ways to assist with the gathering, filtering, and analysis of data. They can further use this data to forecast sales, enhance purchase experiences for customers, create customer personas, improve decision-making, and segment potential customers efficiently. AI can assist in descriptive analytics by quickly sorting through large amounts of data to identify trends and patterns that may not be obvious to the human eye. More so, AI tools can create visualizations and reports that make it easier for marketers to understand and communicate the data. AI helps businesses segment their audience based on behavior, preferences, and demographics to deliver highly personalized marketing messages and improve ROI. This is like having a bespoke tailor for each customer, ensuring they only see what suits them best.
The Strategic Power of Transactional Emails (And How to Use Them Right)
Instead of manually creating variations, Smartly.io generates them automatically from your product feed or assets. Its highlight feature is the AI caption generator, which also adjusts tone and length based on the platform. You can observe keywords rivals are ranking for, how their ads are performing, and where your opportunities lie. To get started, you enter your product details, brand colors, and campaign goal. It assists in writing blog posts, compressing lengthy reports, and so on, without having to leave the current page you are working on.
Artificial intelligence Reasoning, Algorithms, Automation
Robotics powered by AI has made significant strides in industries like manufacturing, healthcare, and logistics. The rise of powerful language models like OpenAI’s GPT (Generative Pretrained Transformer) and Google’s BERT has drastically improved NLP’s capabilities. These models are capable of understanding context, generating human-like text, and even answering questions with impressive accuracy. There are several types of machine learning, including supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. In supervised learning, the machine is trained on labeled data, meaning the correct output is already known, and the system learns to predict these outputs. Unsupervised learning, on the other hand, deals with unlabeled data, where the machine must find patterns and structures within the data on its own.
Healthcare
That year almost 15 new cases of copyright-related suits were filed against companies involved in creating generative AI programs. One prominent company, Stability AI, came under fire for using unlicensed images to generate new content. Currently, AI-made content cannot be copyrighted, but there are arguments for and against copyrighting it. For example, maps of almost four million miles of public roads in the United States would be needed for an autonomous vehicle to operate effectively, which presents a daunting task for manufacturers.
35+ Best AI Tools: Lists by Category 2025
Wix combines fast site generation with one of the most flexible editors out there. You can start with a few prompts, adjust layouts, rewrite content, and even rework your branding. Wix also comes with built-in tools for payments, SEO, bookings, and email campaigns, enough to run a small business without adding anything extra. Premium plans start at £17/month with a custom domain and eCommerce options. The free version provides access to the GPT-3.5 model, which is great for basic tasks like answering questions, writing, and brainstorming. However, the paid version, ChatGPT Plus, costs $20 per month and unlocks access to the more powerful GPT-4 model.
Quantum Machine Learning
The team is also looking to see how foundation models could be implemented on their chips. The design that the team at IBM Research have created can encode 35 million phase-change memory devices per chip; in other words, models with up to 17 million parameters. While this isn’t yet at a size comparable to today’s cutting-edge generative AI models, combining several of these chips together has allowed it to tackle experiments on real AI use cases as effectively as digital chips could.
In search of AI algorithms that mimic the brain
During inference, an AI model goes to work on real-time data, comparing the user’s query with information processed during training and stored in its weights, or parameters. The response that the model comes back with depends on the task, whether that’s identifying spam, converting speech to text, or distilling a long document into key takeaways. Over the last decade, we’ve seen an explosion of applications for artificial intelligence. In that time, we’ve seen AI go from a purely academic endeavor to a force powering actions across myriad industries and affecting the lives of millions each day. These chips were conceived and designed by IBM researchers in the Tokyo, Zurich, Yorktown Heights, New York, and Almaden, California labs, and built by an external fabrication company. The phase change memory and metal levels were processed and validated at IBM Research’s lab in the Albany Nanotech Complex.
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You could qualify such classes as "on-site" or "physical"; but except in a context where online and non-online have already been clearly distinguished this is going to read/sound rather clunky. What you're asking for is a term to "mark" an "unmarked" category, which is usually going to be awkward. I'm translating some words used in messages and labels in a e-learning web application used by companies. So, I'm trying to find the right answer for a course, instead of online, took in a classroom or any corporate environment.
How To Leverage Generative AI For Small Business Growth
Forward-thinking organizations are re-architecting their workflows, teams, and processes around artificial intelligence for business as a core capability, rather than a bolt-on. By embracing AI workflow automation, organizations can significantly enhance process speed, accuracy, and scalability, while enabling employees to focus on higher-value tasks. More companies are now integrating AI business automation with workflow orchestration platforms to achieve enterprise-wide process transformation. Its ability to automate tasks, improve decision-making, and improve efficiency reshapes how companies operate and compete.
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This process relies on a software architecture called a deep neural network (DNN), specifically transformer networks. Transformer networks are adept at breaking down text into "tokens," which are basically parts of words ("words" is one token, "basically" is two tokens). Then, it predicts the sequence that's most likely to make sense with the user based on their interactions. The calculation is different for every person and conversation, requiring a huge amount of electricity and energy. If you just want to play around with the tool before using it to ask specific questions, you can use the automatically generated prompts that come up in ChatGPT.
Difference Between Machine Learning and Artificial Intelligence
You borrow because you believe in your future — that your degree will open doors, that you’ll land a job that makes the debt manageable. The job market changes, industries shift, and sometimes life doesn’t go according to plan. Understanding these challenges is more info crucial as we move deeper into the age of intelligent machines. In reinforcement learning, an agent learns by interacting with an environment and receiving feedback in the form of rewards or punishments.
Pursuing an Advanced Degree in Artificial Intelligence
Their use in these sectors shows that tech can adapt and drive progress. High computational requirements make it costly for smaller businesses. ML enhances AI capabilities by analyzing data and learning from patterns.
Top 15 AI Business Use Cases in 2025 + Examples
AI categorizes and organizes large volumes of HR data, making it easier to retrieve and analyse information. This supports better decision-making and efficient HR management. Using AI, HR can predict which employees are at risk of leaving the company. By analysing factors such as engagement, satisfaction, and performance, proactive measures can be taken to improve retention. Employs machine learning to detect fraudulent activities by identifying irregular betting behaviours.
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RNA vaccines, such as the vaccines for SARS-CoV-2, are usually packaged in lipid nanoparticles (LNPs) for delivery. These particles protect mRNA from being broken down in the body and help it to enter cells once injected. This approach could dramatically speed the process of developing new RNA vaccines, as well as therapies that could be used to treat obesity, diabetes, and other metabolic disorders, the researchers say. Fields ranging from robotics to medicine to political science are attempting to train AI systems to make meaningful decisions of all kinds. For example, using an AI system to intelligently control traffic in a congested city could help motorists reach their destinations faster, while improving safety or sustainability.
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The augmentation of human expertise is reaching new heights with the introduction of agentic AI workflows. Agentic AI employs GenAI and large-language models to independently strategize, reason, and execute complex processes. By creating autonomous agents with specific goals — such as research or document drafting — these systems can accomplish tasks, even self-checking their work before submission. The human brain, remarkable as it is, has limitations in processing multiple variables at once, which can lead to human error. AI systems excel at this type of real-time complex data analysis, considering thousands of factors in milliseconds to identify optimal solutions. AI presents significant opportunities for businesses to reduce operational costs while maximizing efficiency.
11+ Best AI Novel Writing Software Tools in 2025
They didn’t have to write custom programs, they just had to ask questions of a database in high-level language. In the future, the researchers plan to design MBTL algorithms that can extend to more complex problems, such as high-dimensional task spaces. They are also interested in applying their approach to real-world problems, especially in next-generation mobility systems. To boost the reliability of reinforcement learning models for complex tasks with variability, MIT researchers have introduced a more efficient algorithm for training them. Reinforcement learning models, which underlie these AI decision-making systems, still often fail when faced with even small variations in the tasks they are trained to perform.
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HubSpot AI is best for Small and medium business owners who want one platform to manage social media scheduling, customer relations, content creation, SEO recommendations, email marketing, and more. The features you get within HubSpot are individual apps outside the platform; therefore, your marketing team can benefit from this. The suite of marketing and sales apps ensures you don’t have to switch between various apps whenever you need to get something done. Pictory stands out in its ability to transform written content into captivating videos. This eliminates the need for complex video editing software or filming elaborate scenes. Provide your script or text, and its AI will find and compile relevant media assets, transforming your words into a visually dynamic and informative social media post.
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It supports style transfer, portrait enhancement, and batch creation. Adobe Firefly offers powerful AI image generation tailored for creatives. It supports text-to-image, text effects, and vector generation, all under Adobe’s safe-for-commercial-use license.