AI technology, driven by natural language processing (NLP), has advanced significantly, enabling the creation of generative AI systems that go beyond mere data processing. These systems, based on machine learning and neural networks, open new frontiers in the generation of new content, including images and code.
Many of these capabilities rely on open-source projects and high-performance platforms, leveraging large language models to drive creativity and innovation in artificial intelligence. This landscape of generative AI applications marks a surprising advance in the technology.
In this context, it is worth asking, how are the capabilities of generative AI being used? How do they integrate with Salesforce? Next, let’s see.
What is generative artificial intelligence?
Generative artificial intelligence is a new level of artificial intelligence whose core is not only data analysis but, above all, the creation of something new. It can be text, image, video, code, music, etc. These types of systems are based on training with large volumes of data.
How does it work?
Generative AI, broadly speaking, works by utilizing machine learning algorithms, specifically neural networks, to create new and original content. Its operation can be divided into several stages:
- Data Entry: begins with data entry, which can be text, images or other types of information.
- Processing and Analysis: AI uses algorithms such as natural language processing (NLP) or neural networks to understand key patterns and contexts in the input data.
- Content Generation: based on its analysis, generates new content that fits the style and context of the original entry.
- Evaluation and Improvement: includes evaluation mechanisms to guarantee both the quality and coherence of the generated content, learning and improving from feedback.
- Generated Content Output: Produces new content based on its processing of the original input, which can be text, images, music or any other type of data, depending on the application.
It is important to highlight that generative AI is not only used to create static content, but is also applied in real time in various applications. Its ability to create new high-quality content makes it invaluable in a variety of fields, from art and creativity to task automation and customer support.
Generative AI applications
The applications of generative AI are becoming more and more fascinating. The advancement of technology is achieving applications with much more efficient results in different spheres of life. The use given to them by various publics is driving development in multiple aspects, leading to a revolution in the ways of doing things that have been employed so far. Among the most widely known applications we have:
Content writing
The minutes, and sometimes hours, that people spend writing content for blogs, marketing campaigns, or responding to customers can be boosted with generative AI. The algorithms at its base are capable of generating personalized content for different purposes, considerably increasing efficiency in this work. Simple examples of what generative AI is capable of driving are:
- personalized recommendations of products or services based on user behavior patterns;
- the automated writing of marketing campaigns tailored to specific audience segments;
- the generation of conversational content in the question-and-answer style;
- the dynamic generation of web pages.
It is worth noting that content writing is the most developed application of generative AI. Mainly, it is used iteratively or as a first draft. Never as a finished product, at least for the time being.
Translation into multiple languages
Real-time translation is a necessity for many companies to be able to serve the most diverse audiences promptly. Response times are reduced, as are the risks of losing the customer. Specific solutions such as chatbots or virtual assistants for customer service are enhanced with generative AI.
Image creation
How many of us have wanted to create an image of something we think about and can only hope to describe it in words? What if by introducing that description into a system we can generate a very close or even novel image of what we want? Well, generative AI can do this.
Image design is very important for different businesses and creating them is not something that is usually simple. If before you had to create images laboriously, even without skills, to avoid copyright problems, the process is no longer so cumbersome. Generative AI, based on textual descriptions, returns unpublished images with high resolution.
Video creation
Not only image creation has benefited from this technology, but also videos. For example, it is now possible to make an automatic video summary based on the selection of frames that are key to its execution. A job that could previously take long hours, shortens its time thanks to this revolutionary technology.
Currently, there is talk of AI ARTS, or “Arts with Artificial Intelligence.” It refers to a discipline that combines art and AI. In this context, AI is used as a means to create works of art, either by generating art autonomously or collaborating with human artists to produce creative pieces.
Musical composition
For those who do not have musical skills, this technology makes their lives much easier. Examples of generative AI entering the world of music include: algorithmic musical compositions made with customizable parameters, the creation of incidental or background music for videos or games, as well as its contribution to interactive music creation tools.
Developer tasks
One of its most notable applications is autonomous code generation, where AI can create source code segments based on descriptions and requirements provided by developers. This speeds up the development process and reduces the manual workload.
Additionally, generative AI is used to generate realistic and diversified test data sets, which helps in software testing and ensures higher quality. It is also used in the creation of documentation and detailed code descriptions, making it easier to understand and maintain the software.
Other more general applications can be:
- Synthesis of texts, images or videos.
- Transfer of style, from something existing to something new generated by AI.
- Grow an existing data set.
- Planning events, trips, etc.
- Research
- Cybersecurity.
- Generation of voices and audios.
- Product designs.
- From a business perspective
Despite the possibility of using generative AI for specific purposes, ; it is in the business environment where its full potential is deployed. Its main applications are:
Customizations
Hyperpersonalization of messages sent to customers is one of the applications of generative AI for companies. A neutral message is no longer necessary to reach the most diverse audiences. Now companies rely on this technology to send messages tailored to the preferences and behavioral patterns of each customer. Based on the in-depth analysis of each audience segment, the greatest effectiveness is guaranteed in each message. Likewise, marketing campaigns are adjusted to this data and a result is obtained with greater potential to be well received by the client.
Automations and efficiency
Even in the least thought-out sectors, generative AI has a place, helping automation and significantly increasing the company’s efficiency. For example:
- Human Resources: Automation of tasks such as resume selection, candidate search, decision making, etc. This contributes to saving time and using it on prioritized tasks.
- Marketing: Adjustment of advertising campaigns and direct contact with customers according to their preferences and behaviors.
- Logistics: Based on generative AI, it is possible to enhance the optimization of supply and sourcing chains; which translates into agility in all operations.
- Maintenance: Automations enable notification of maintenance needs based on analysis of large amounts of data. Thus, it is possible to predict possible breakages before they occur, or revision needs.
- Finance: This technology helps financial specialists identify the best investment portfolios to suggest to different clients according to their particularities. Likewise, it becomes key in the detection and prevention of fraud. On the other hand, it also provides valuable information to virtual financial advisors, which are powered by natural language processing.
How does Salesforce make use of generative AI?
Salesforce, the CRM technology giant, continues to take advantage of the benefits of generative AI. Based on the AI Cloud, it extends this technology, which is so necessary and in demand today, much further to companies. With the potential of this cloud, Salesforce gives greater strength to its main products that rely on this technology.
A clear example of this is the Einstein GPT suite of solutions, considered the world’s first generative AI tool for CRM. Thanks to its integration with ChatGPT, companies can have an ideal ally for the generation of highly specialized content. Likewise, Tableau GPT also draws on generative AI, thus contributing to business intelligence, while facilitating data analysis and visualization. As if that were not enough, it is also worth mentioning Slack GPT and its important contribution to improving communication and productivity within the company.
Similarly, generative AI reaches the Sales, Service and Marketing clouds, now with a GPT version respectively. Sales GPT reduces time spent researching prospects. Service GPT optimizes the resolution of service cases and Marketing GPT simplifies tasks such as writing emails and marketing strategies. We will be talking about these soon.
As can be seen, Salesforce continues to advance in the integration of generative AI into its products. Without a doubt, using it is a very wise decision considering the enormous advantages it provides for companies. If you want to explore these multiple benefits in your Salesforce solution, feel free to contact the SkyPlanner team at hello@theskyplanner.com. We will be happy to advise you.
