Digital Event Horizon
NVIDIA experts predict that AI will shape industries in 2025 by enabling the adoption of accelerated computing for data analytics, giving rise to new categories of essential workers like prompt engineers and AI personality designers, and creating opportunities for enterprises to harness their unique data for new applications. The future of humanoid intelligence is expected to be shaped by agentic AI, AI agents, multistep reasoning, and AI query engines, leading to increased efficiency, productivity, and innovation across industries.
Agentic AI, autonomous or "reasoning" AI, is expected to be the next big thing in 2025, requiring diverse language models and advanced data architectures.Generative AI-empowered analytics technology will widen adoption of accelerated data analytics by empowering users to create new applications.Prompt engineers and AI personality designers are emerging as essential workers, designing precise text strings for chatbots and agentic AI.Startups will use revenue per employee (RPE) to discuss investments with investors, focusing on employee revenue impact.Enterprises will have AI agents that work across internal networks, and AI orchestrators to route human inquiries and provide collective results.AI systems will tackle complex problems using multistep reasoning, enabling accurate and deeper analysis.AI query engines will revolutionize data mining and company-specific search engines will interpret user intent for more relevant results.
NVIDIA experts across various fields have shared their insights on how artificial intelligence (AI) will shape industries in 2025. According to industry verticals, the next big thing is agentic AI, a form of autonomous or "reasoning" AI that requires using diverse language models, sophisticated retrieval-augmented generation stacks, and advanced data architectures.
Generative AI-empowered analytics technology is expected to further widen the adoption of accelerated data analytics by empowering users to create new data analytics applications. The seamless integration of accelerated computing, facilitated by a simplified developer experience, will help eliminate adoption barriers and allow organizations to harness their unique data for new AI applications and richer business intelligence.
The startup workforce is also expected to evolve with the emergence of new categories of essential workers, including prompt engineers and AI personality designers. Prompt engineers design and refine precise text strings that optimize AI training and produce desired outcomes based on the creation, testing, and iteration of prompt designs for chatbots and agentic AI. The demand for prompt engineers will extend beyond tech companies to sectors like legal, customer support, and publishing.
Startups incorporating AI into their practices will increasingly use revenue per employee (RPE) to discuss investments with investors and business partners. This approach will allow startup owners to focus on how hiring each new employee helps everyone else in the business generate more revenue.
Enterprises are set to have a slew of AI agents, which are semiautonomous, trained models that work across internal networks to help with customer service, human resources, data security, and more. To maximize these efficiencies, expect to see a rise in AI orchestrators that work across numerous agents to seamlessly route human inquiries and interpret collective results to recommend and take actions for users.
AI systems will tackle increasingly complex problems and respond with greater accuracy and deeper analysis using a capability called multistep reasoning. These models dynamically evaluate each step, ensuring contextually relevant and transparent responses. Multistep reasoning also involves integrating knowledge from various sources to enable AI to make logical connections and synthesize information across different domains.
The challenge of gaining quick access to data is becoming increasingly important for businesses. AI query engines will change how companies mine their data, and company-specific search engines will be able to sift through structured and unstructured data using natural language processing and machine learning to interpret a user's intent and provide more relevant and comprehensive results.
NVIDIA experts across various fields have shared their insights on how AI will shape industries in 2025. According to industry verticals, the next big thing is agentic AI, a form of autonomous or "reasoning" AI that requires using diverse language models, sophisticated retrieval-augmented generation stacks, and advanced data architectures.
Generative AI-empowered analytics technology is expected to further widen the adoption of accelerated data analytics by empowering users to create new data analytics applications. The seamless integration of accelerated computing, facilitated by a simplified developer experience, will help eliminate adoption barriers and allow organizations to harness their unique data for new AI applications and richer business intelligence.
The startup workforce is also expected to evolve with the emergence of new categories of essential workers, including prompt engineers and AI personality designers. Prompt engineers design and refine precise text strings that optimize AI training and produce desired outcomes based on the creation, testing, and iteration of prompt designs for chatbots and agentic AI. The demand for prompt engineers will extend beyond tech companies to sectors like legal, customer support, and publishing.
Startups incorporating AI into their practices will increasingly use revenue per employee (RPE) to discuss investments with investors and business partners. This approach will allow startup owners to focus on how hiring each new employee helps everyone else in the business generate more revenue.
Enterprises are set to have a slew of AI agents, which are semiautonomous, trained models that work across internal networks to help with customer service, human resources, data security, and more. To maximize these efficiencies, expect to see a rise in AI orchestrators that work across numerous agents to seamlessly route human inquiries and interpret collective results to recommend and take actions for users.
AI systems will tackle increasingly complex problems and respond with greater accuracy and deeper analysis using a capability called multistep reasoning. These models dynamically evaluate each step, ensuring contextually relevant and transparent responses. Multistep reasoning also involves integrating knowledge from various sources to enable AI to make logical connections and synthesize information across different domains.
The challenge of gaining quick access to data is becoming increasingly important for businesses. AI query engines will change how companies mine their data, and company-specific search engines will be able to sift through structured and unstructured data using natural language processing and machine learning to interpret a user's intent and provide more relevant and comprehensive results.
Related Information:
https://blogs.nvidia.com/blog/generative-ai-predictions-2025-humanoids-agents/
Published: Thu Dec 5 15:06:55 2024 by llama3.2 3B Q4_K_M
