Artificial Intelligence Trends For 2024: Here’s What To Expect

Experts in artificial intelligence (AI) are predicting and discussing trends affecting businesses in 2024. They offer an overview of what the AI landscape will look like in 2024, from more compact and efficient AI models to the increasing role of deepfakes in national elections.

Integrating Smaller AI Models

Amadeus Capital Partners partner Amelia Armour predicts a big shift towards using small AI models at the edges of networks. These sophisticated models use very little computing power while achieving remarkable efficiency.

This change will cause industrial automation to boom, especially when distributing goods via autonomous robots. As a result, production has skyrocketed in all of these areas.

Improving Network Capabilities Through Data Centers

Data centers will address the increasing need for AI processing capabilities by improving network speeds, reducing energy usage, and reducing heat generation. Thus, new and improved cooling techniques and photonic chips that transform high-speed data flows will become available.

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In 2024, these innovations will be front and center, solving the urgent demand for high-performance computing that is both efficient and safe from overheating.

Pushing For Open-Source Models

Finnish AI firm Silo’s CEO and co-founder Peter Sarlin predicts an increasing trend towards smaller, more affordable, and more specialized AI models that meet the needs of multiple language models. This change, which will democratize access to AI for enterprises, will be significantly helped by the rise of open-source models.

This development fits in perfectly with the general trend of incorporating AI models into software products, enabling the addition of new features to current frameworks.

Using Deepfakes In Elections

Meanwhile, Nathan Benaich, the founder of Air Street Capital, opines that deepfakes might play a part in several elections that will take place in 2024. Malicious attempts may be made during the US presidential election due to significant improvements in deepfake technology.

Regardless of whether or not the prospective consequences affect the outcome, regulatory inquiries are warranted because the potential implications are significant enough.

Innovative Funding Structures

According to Nathan Benaich, developing innovative fundraising models geared explicitly to compute-intensive enterprises is vital. Certain businesses have started investigating the possibility of obtaining collateralized debt financing to leverage their graphics processing units (GPUs).

Global AI Governance

Rick Hao, a top-level executive at Speedinvest, expressed a different point of view about AI regulation. He believes that the global conversation about AI control might slow down. Even though there have been a lot of talks, it seems impossible for Western democracies and China to agree on how to rule AI. Rick doesn’t think future discussions will have the same effect as the last ones or lead to real government action.

Opportunities In The AI Safety Sector

Due to the rapid progress of AI capabilities, Rick Hao expects AI safety to receive substantial investment despite its growing importance. As firms embrace advanced AI tech, transparency, trust, and governance will become crucial.

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Rick also notes that AI progress is surpassing many predictions. Recent advancements like Google DeepMind’s material science research demonstrate AI’s enormous potential. Thus, he expects more industry-changing technologies in 2024.

Rise In Multi-Modal AI Model

Runa Capital’s general partner, Dmitry Galperin, expects multi-modal AI models to process text, images, audio, and videos in 2024. These technologies may attract public interest, but their integration into enterprise landscapes may face ethical, security, and inaccurate content issues.

Additionally, co-founder and CEO of German-based GenAI firm Nyonic, Vanessa Cann, stresses the growing need for AI data quality assurance, protection, and observability.

Researchers might explore photonics interconnects, neuromorphic computing, and analog computing since these technologies enhance the trustworthiness and transparency of AI frameworks.

Custom AI Platforms For Businesses

Vanessa Cann opines that there will be a big shift towards AI models that are designed for particular industries and tasks. These models will incorporate the terminology and concepts of these industries.

Businesses that use foundation models are in a good position to get an advantage over their competitors. They have much room to grow in efficiency, innovation speed, and productivity because of the continual improvements to these core models.

Author: Owen Clark

Owen Clark, a seasoned crypto newsman and broker, deciphers the intricacies of the digital currency realm, empowering investors with his astute analysis and actionable insights.

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