Intelligent Automation/RPA

Trends in generative AI 2024

Generative AI is changing the ways we live and work, and it’s here to stay. Here are some of the emerging and expected trends in generative AI for 2024.

The rise of generative AI trends

For the past decade, there’s been consistent buzz around the topic of artificial intelligence (AI). What once seemed like merely the intersection of computer science and science fiction, (or the subject of a popular film franchise), is now the latest technology trend. Implemented across industries and professions, AI has the capacity to alter every facet of life—as the advent of the internet did.

Generative AI, capable of creating text, images, and other media through generative models, appeals to a wide range of businesses and organizations. In the coming year, more generative AI is expected to enter the market, either as add-ons to existing provider services or stand-alone tools.

Here are some of the emerging and expected generative AI trends for 2024.

Increasing datasets and actionable AI

Generative AI applications like large language models (LLM) run on incredibly large datasets; some are trained in hundreds of billions of parameters. Increasing the size of the dataset has shown to be a way to improve the accuracy of the AI, making the LLM smarter. Undoubtedly, these applications will continue to become bigger and better.

This year will also see a major rollout of actionable AI, or AI being used to work within multiple systems of an organization. The increasing interoperability of generative AI allows for more dynamic orders to be carried out, which ultimately translates to time and money saved. By using AI as a personal assistant in daily work, and teaching it to perform the tasks related to a specific job or role, actionable AI can drive immense business value.

Multi-modality: generative AI trends in design, audio, speech, and video

More sophisticated generative AI tools will become available with the entrance of multi-modal models. Most AI tools and algorithms are limited to one mode of expression, but multi-modality will make AI capable of interpreting images, as well as understanding voice commands and responding to them.

Soon, generative AI will be implemented in the design of physical products and structures. In fact, one software corporation is already using generative design to allow users to create prototypes of a model they can then test simultaneously as digital twins. This will undoubtedly usher in a new era of product development.

Part and parcel of generative design trends are the coming of generative audio, speech, and video. Generative video will cut the costs of this content creation, and give brands the ability to widen their reach and appeal to new, younger audiences. In fact, this is already starting to appear on social media platforms.

Generative AI trends to offset the cost of enterprise data analysis

As the cost of cloud computing increases for organizations, data migration and storage is becoming a quality control issue; especially as the higher volume translates to greater complexity and risk for data corruption. This data is necessary to make critical business decisions, but many organizations only have a small number of data analysts on their employee roster.

With cutting-edge automation capabilities and an increasing ability to understand natural language, LLM can translate words to code for computers and then back to natural language for human users. This can supplement a smaller data analytics staff, reduce the amount of code the analysts need to do their jobs, and improve the overall quality of the data being produced.

Autonomous AI, augmented apps and services

Autonomous AI refers to a class of generative applications that can operate themselves by repeatedly producing and responding to prompts. This is a significantly more sophisticated technology than the chatbot generative agents, which are only able to reply to a prompt and then wait for user input to instruct them on what to do next.

As AI sweeps through business operations and enterprise applications, it’s feasible to predict that conversational AI will become an embedded feature. Developers like Microsoft and Adobe are incorporating natural query interfaces into their platforms, with others following suit to build their own LLMs to use as the basis for their brand’s generative AI capabilities. Chat interfaces will become the norm as businesses use AI to improve the quality of the customer experience.

How generative AI trends impact developers and prompt engineers

It comes as no surprise that as the demand for generative AI technology continues to grow, so will the career opportunities for developers and prompt engineers. These engineers program and train generative AI systems by giving them highly detailed instructions, hoping to see the system perform in a way that will most likely lead to the desired results. Also called “AI whispering,” this career avenue will explode for professionals who can encourage optimal performance from these systems.

The double-edged sword of generative AI trends

It’s undeniable that there are ample opportunities for generative AI to increase worker productivity, improve business operational efficiency, and positively impact user engagement with enterprise applications. What isn’t so apparent yet is how AI will have an adverse effect. What history has taught us is that with any major technological breakthrough, an equally seismic societal shift takes place, too.

The power and possibility of AI are never so glaring as when considered through the lens of cybercriminals and bad actors. Generative AI technology could be used to create propaganda and misinformation to disrupt elections and political narratives. Deepfakes, the term given to videos of people that have been digitally altered, could be used to spread fake news, create media for the purpose of blackmail and extortion, and a host of other ill motives.

Because generative AI could be used to mimic writing styles and speech patterns, it could be employed in sophisticated phishing attacks. It could also be used to automate processes that criminals use when searching for and exploiting vulnerabilities in a system. As such, it’s highly likely that generative AI will also fuel a new wave of cybercrime and cybersecurity attacks. To combat this, AI is also being utilized in cybersecurity solutions to improve the accuracy of threat analysis.

Conclusion

The year ahead will be full of technology advancements in AI. Multi-modality, actionable AI, and autonomous AI will offer defined business benefits for nearly every industry. Developers and prompt engineers will face a tidal wave of work opportunities in this burgeoning form of technology. Of course, it isn’t all sunshine and operational efficiency, there are risks to be weighed as well. The undeniable fact remains; generative AI is changing the ways we live and work, and it’s here to stay.

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