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This transition aligns with a broader trend: building software atop LLMs rather than deploying chatbots as standalone tools. Moving from chatbot interfaces to applications that use LLMs on the back end to summarize or parse unstructured data can help mitigate some of the issues that make generative AI difficult to scale.#OpenfabricAI #DeFi #Crypto #trading

Generative AI moves beyond chatbots

When most laypeople hear the term generative AI, they think of tools like ChatGPT and Claude powered by LLMs. Early explorations from businesses, too, have tended to involve incorporating LLMs into products and services via chat interfaces. But, as the technology matures, AI developers, end users and business customers alike are looking beyond chatbots.
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. Generative AI moves beyond chatbots

When most laypeople hear the term generative AI, they think of tools like ChatGPT and Claude powered by LLMs. Early explorations from businesses, too, have tended to involve incorporating LLMs into products and services via chat interfaces. But, as the technology matures, AI developers, end users and business customers alike are looking beyond chatbots.
#OpenfabricAI #DeFi #Crypto #Trading

One reason for this is AI's uneven impact across roles and job functions. Organizations are discovering what Stave termed the "jagged technological frontier," where AI enhances productivity for some tasks or employees, while diminishing it for others. A junior analyst, for example, might significantly increase their output by using a tool that only bogs down a more experienced counterpart.#OpenfabricAI #defi #Crypto #trading

One reason for this is AI's uneven impact across roles and job functions. Organizations are discovering what Stave termed the "jagged technological frontier," where AI enhances productivity for some tasks or employees, while diminishing it for others. A junior analyst, for example, might significantly increase their output by using a tool that only bogs down a more experienced counterpart.#OpenfabricAI #defi #Crypto #crypto #OFN

"The most surprising thing for me [in 2024] is actually the lack of adoption that we're seeing," said Jen Stave, launch director for the Digital Data Design Institute at Harvard University. "When you look across businesses, companies are investing in AI. They're building their own custom tools. They're buying off-the-shelf enterprise versions of the large language models (LLMs). But there really hasn't been this groundswell of adoption within companies."#OpenfabricAI #DeFi #crypto #trading

Although many businesses have explored generative AI through proofs of concept, fewer have fully integrated it into their operations. In a September 2024 research report, Informa TechTarget's Enterprise Strategy Group found that, although over 90% of organizations had increased their generative AI use over the previous year, only 8% considered their initiatives mature.#OpenfabricAI #DeFi #Crypto #trading

The 2025 AI landscape reflects that complexity. While excitement still abounds -- particularly for emerging areas, like agentic AI and multimodal models -- it's also poised to be a year of growing pains.

Companies are increasingly looking for proven results from generative AI, rather than early-stage prototypes. That's no easy feat for a technology that's often expensive, error-prone and vulnerable to misuse. And regulators will need to balance innovation and safety, while keeping up with a fast-moving tech environment.

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8 AI and machine learning trends to watch in 2025

AI agents, multimodal models, an emphasis on real-world results -- learn about the top AI and machine learning trends and what they mean for businesses in 2025.

Lev Craig, Site Editor

Published: 03 Jan 2025

Generative AI is at a crossroads. It's now more than two years since ChatGPT's launch, and the initial optimism about AI's potential is decidedly tempered by an awareness of its limitations and costs.
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What’s ahead?

This time of year is rife with predictions and we’ll be sharing more of our own in the weeks to come. Clear from the AI trends in 2024 is that innovation won’t be slowing down anytime soon: the full agentic revolution is still about to hit, and with it will come new choices for regulators, new capabilities for cybercriminals to weaponize—and new opportunities for cyber-defenders to proactively secure the digital world.

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Promoting public peace
Trend took part in the 2024 Paris Peace Forum and announced its partnership with the Forum on developing guidance for secure AI adoption and implementation. As Martin Tisné, CEO of the AI Collaborative, said at the Forum meeting, what’s most important is to ensure that AI is outcomes-based from the start, so that its development and uses coincide with the good it can bring to society.#OpenfabricAI #defi #Crypto #trading

Beating the bad guys to it
Using AI to discover vulnerabilities and exploits got a fair bit of attention throughout the year. While AI isn’t always needed, in situations where complexity is high and unknowns abound, it can deliver excellent results. The Frontier Model Forum found vulnerability discovery and patching is an emerging area of AI strength, due partly to increased use of coding examples in post-training and partly because of expanding context windows. AI can also support open-source intelligence gathering and reporting through real-time monitoring and analysis, trend identification, and more.#OpenfabricAI #defi #Crypto #trading

AI Can do Good, Too

While it’s important to be clear about the risks of AI, it’s just as important to stay mindful of the benefits—and a number of efforts sought to highlight those positive capabilities in 2024.

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Born in the USA: AI regulation stateside
The back half of the year was busy at the federal level in the U.S., with the White House issuing its very first National Security Memorandum on AI in October. The memo called for “concrete and impactful steps” to:

Ensure U.S. leadership in the development of safe, trustable AI

Advance U.S. national security with AI

Drive international agreements on AI use and governance

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