In 2022, generative artificial intelligence (AI) surged into public awareness, while 2023 witnessed its initial adoption in the business sphere. As we enter 2024, it becomes a crucial year for the future of AI, as both researchers and businesses aim to discern its optimal integration into daily life.
As we look forward to the year ahead, let’s explore the top AI trends:
Top AI Technology Trends in 2024
From innovative multimodal AI models to the proliferation of small language models, these emerging trends hold the potential to redefine the capabilities of AI and its impact on society.
Generative AI
When generative AI initially gained widespread attention, business leaders relied heavily on marketing materials and sensational news reports. Actual experience, if any, was often limited to experimenting with tools like ChatGPT and DALL-E. As the initial hype dissipates, the business community develops a more nuanced understanding of AI generators.
In 2024, investments in generative AI will fuel its ongoing evolution, leading to the creation of new AI tools for generating text, video, images, and audio. This sustained financial support will drive further advancements in the field, expanding its capabilities and applications.
Generative AI will continue to gain momentum for three key reasons:
- accessibility and user-friendliness of applications;
- tangible benefits for both businesses and individuals;
- heightened awareness fueled by media attention on AI advancements.
The most important change will probably involve data — curating unstructured content, enhancing data quality, and integrating different sources.
Multimodal AI
The upcoming wave of progress will not just concentrate on improving performance within a singular domain, but on multimodal models capable of processing various types of data as inputs.
The term «multimodality» sounds complicated but is actually quite simple. As a society, our consumption of content is evolving towards richer and more interactive experiences. With our attention spans shorter than ever, content is tailored for quick consumption via mobile apps: from TikToks to Snapchats to Slack messages. We also engage with content through reactions and emojis. This shift is reflected in the AI industry, where multimodal deep learning is emerging.
Multimodal AI offers immediate advantages, enhancing the intuitiveness and versatility of AI applications in app stores and virtual assistants. Users can inquire about an image and receive a natural language response, or request verbal guidance for a task and receive visual aids with accompanying text instructions. This approach enriches training and inference by processing diverse data inputs, with video presenting significant potential for comprehensive learning.
Capable And Powerful Small Language Models
If 2023 marked the era of large language models, 2024 will showcase the prowess of small language models (SLMs). While LLMs rely on extensive datasets like Common Crawl and The Pile, SLMs are trained on more refined sources such as textbooks and journals, offering higher-quality data. Despite their reduced parameter count and resource requirements, SLMs deliver comparable content quality to their larger counterparts, making them cost-effective and accessible.
Notable examples include Microsoft’s PHI-2 and Mistral 7B, poised to drive the next wave of generative AI applications. Enterprises can customize SLMs to specific tasks and domains, ensuring compliance with legal and regulatory standards and accelerating their adoption.
Power of AI Trends when Combined with Other Emerging Technologies
Merging AI with new tech like blockchain brings a wave of innovation. This fusion secures sensitive data by combining AI’s prediction with blockchain’s tamper-proof ledger. This allows secure processing of information, like financial transactions, without compromising privacy.
Furthermore, AI’s real-time analysis of sensor data from connected devices (IoT) revolutionizes how we interact with them. This, for example, allows predicting equipment failures and optimizing resources. This convergence of AI and IoT boosts efficiency, safety, and reliability across various industries.
Finally, AI-powered robots are transforming industries. By combining AI with robots, companies can automate tasks, streamline production, and empower human workers. Collaborative robots work safely alongside humans, performing precise and complex tasks. This AI-robotics collaboration unlocks new levels of productivity and innovation in the digital age.
Enterprise AI Trends and Use Cases in Various Industries
Modern enterprises use AI in industry operations in many different ways: automating IT and business, enhancing customer service, addressing talent shortage issues, etc. For example,
OrbitSoft Company uses ChatGPT for writing ad texts and for smart contract development. In this article, we shared useful information on how data science can save hundreds of hours of work time. To learn more about AI applications in business, explore our website.
Let’s take a look at the latest AI trends in business and some use cases.
Retail and E-commerce
AI technology in the retail and e-commerce sectors is revolutionizing the way businesses interact with customers and manage their operations. Through sophisticated algorithms, AI analyzes vast amounts of data on customer behavior and preferences to provide personalized product recommendations, enhancing the shopping experience.
A prime example of AI’s impact in retail is demonstrated by Amazon’s use of personalized recommendation algorithms. By leveraging AI to analyze customer browsing and purchase history, Amazon delivers tailored product suggestions to each user, fostering higher engagement, increased sales, and greater customer satisfaction. This application underscores the power of AI in transforming the retail landscape by delivering relevant and compelling experiences to consumers.
Education
Within educational platforms, AI meticulously examines students’ learning behaviors and preferences, customizing content to suit each individual’s requirements for a highly efficient learning journey.
For instance, Coursera effectively employs AI to tailor learning experiences to individual students. By adjusting content according to each student’s unique learning style and preferences, Coursera enhances student engagement and overall academic performance.
Banking and Financial Services
In the finance sector, AI is predominantly utilized for fraud detection. Advanced machine learning algorithms scrutinize transaction patterns in real-time to swiftly pinpoint and counter potential fraudulent activities. By integrating AI protocols into legacy systems, banking institutions bolster their security measures, fostering a more data-driven financial environment.
For instance, JPMorgan Chase & Co uses AI for instantaneous analysis, facilitating the prompt detection of anomalies and safeguarding both the financial institution and its clients.
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What Is The Future of Artificial Intelligence?
Positive aspects
The future of artificial intelligence (AI) holds tremendous potential to reshape various aspects of human life and industries. As technology continues to advance, AI is expected to become even more integrated into our daily lives, leading to transformative changes in fields such as healthcare, transportation, finance, and beyond.
Overall, the future of artificial intelligence is characterized by innovation, growth, and opportunity. As AI technologies continue to evolve and mature, they have the potential to address some of the most pressing challenges facing society and create new opportunities for economic growth and human advancement.
Possible negative aspects
However, it is essential to consider ethical, privacy, and security implications as AI becomes more pervasive in our lives. The enhanced capabilities of multimodal AI and the reduced barriers to entry also present new challenges, including the potential for misuse. Deepfakes, privacy issues, perpetuation of bias may become more accessible to malefactors. For instance, in January 2024, social media platforms experienced a surge of explicit celebrity AI photos, while research from May 2023 indicated a significant increase in voice deepfakes compared to the previous year.
In conclusion, the year 2024 is poised to be a pivotal moment in the trajectory of artificial intelligence (AI), marked by significant advancements and transformative applications across various industries. As we embrace the future of AI, it is imperative to navigate possible challenges thoughtfully, ensuring that AI continues to be a force for positive change while upholding ethical standards and well-being of our society.
FAQs
In 2024, several key AI trends are expected to shape the landscape of artificial intelligence:
- evolution of generative AI;
- enhanced multimodal AI capabilities;
- proliferation of small language models;
- convergence of AI with other emerging technologies;
- continued focus on ethical AI and responsible AI deployment.
Yes, the trends for 2024 highlight specific applications of AI across various industries:
Generative AI: Continued advancements in generative AI will lead to the creation of new tools for generating text, video, images, and audio. These applications will improve content creation, creative design, and storytelling across industries such as media, marketing, and entertainment.
Multimodal AI: The integration of multimodal AI models enables the processing of diverse data inputs, leading to more intuitive and versatile AI app development. This technology will enhance virtual assistants, content recommendation systems, and customer service platforms across industries like retail, healthcare, and education.
Small Language Models (SLMs): SLMs offer compact and cost-effective AI solutions for natural language processing tasks. These models will be deployed in various applications, including personalized recommendations and chatbots, improving customer engagement and operational efficiency in industries such as finance, e-commerce, and customer service.
Yes, businesses can leverage AI trends like generative AI, multimodal AI, SLMs, and AI-driven robotics for operational efficiency, data-driven insights, competitive advantage, and scalability, driving growth and innovation in today’s digital landscape. For example, Amazon uses AI to analyze its clients’ browsing and purchase history to increase sales and improve customer experience.
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