04-19-2025 
|
Getting your Trinity Audio player ready...
|
As the metaverse continues to evolve, a new report suggests that educational applications could be a significant growth area for this emerging technology.
Metaverse in education is projected to clinch a market valuation of $69.4 billion by 2032 from its market capitalization of $3.85 billion in 2024. The leap during the forecast period represents a compound annual growth rate (CAGR) of 37.90%.
Several factors are driving metaverse in education growth over the next seven years. Top on the list is the desire for innovative learning experiences beyond traditional classrooms, a trend that has spiked since the COVID-19 pandemic.
Furthermore, rapid innovation in emerging technologies will contribute to the growth of the metaverse sector. Advancements in virtual reality (VR), augmented reality (AR), and 5G are driving increased interest in metaverse technologies.
Another key driver for the sector is the growing need for learning institutions to create a virtual campus environment to foster novel immersive experiences for teachers and students.
By comparison, hardware will record an impressive double-digit CAGR, with AR, VR, and MR devices expected to become mainstream. On the flip side, the software will record astronomical growth levels, with extended reality software and gaming engines taking up the lion’s share.
In terms of adoption of applications, learning and skills development will be the biggest drivers, with educational apps, cultural understanding, and self-regulation contributing their fair share. Apart from schools, corporations will contribute a chunk to the market share of the metaverse in education.
North America, led by the United States and Canada, will lead markets in education while the Asia Pacific will record the fastest CAGR in the forecast period. Industry leaders include Adobe, Devden, Fotonvr, Hatchxr, Lenovo (NASDAQ: LNVGF), Meta (NASDAQ: META), and Samsung Electronics, among others.
The report notes that achieving a market capitalization of nearly $70 billion in seven years will be an uphill climb. Analysts point to steep implementation costs on the infrastructure and content creation.
Several governments, including South Korea, have invested large sums to develop metaverse use cases. The heavy investments are intended to solve the problems of VR/AR hardware currently standing in the way of mainstream adoption of metaverse in the education sector.
Meta ups AI challenge with Llama 4 herd
Technology giant Meta has rolled out the fourth generation of its open-source large language model (LLM), building on the successes of the previous three offerings.
According to an official announcement, Llama 4 models are designed to outperform their rivals without additional finetuning. Meta’s latest innovation comprises three models, with the company commercially releasing two while one remains in development.The commercially available models, Llama 4 Scout and Maverick, rely on 17 billion active parameters but have key differences. Scout has 16 experts and fits in an Nvidia (NASDAQ: NVDA) H100 GPU, which Meta says is the “best multimodal model in the world in its class.”
However, the Llama 4 Maverick has 128 experts but surpasses GPT-4o and Gemini 2.0 across several benchmarks. Despite being compact, Meta’s statement notes that Maverick matches DeepSeek‘s coding abilities while scoring high on performance-to-cost ratio.
Llama 4 Behemoth, Meta’s most powerful LLM, is still in development. Upon launch, the company says it will outclass OpenAI’s latest LLM. Given its design as a teacher model, both Maverick and Scout lean on the incoming Llama 4 Behemoth for distillation.
“These models are our best yet thanks to distillation from Llama 4 Behemoth, a 288 billion active parameter model with 16 experts that is our most powerful yet and among the world’s smartest LLMs,” said Meta.
Despite the positive statement, early users of Meta’s Llama 4 models have criticized the LLMs for falling short on key metrics. EQ-Bench maintainer Sam Paech noted that “Llama-4 is performing not so well” in long-form writing benchmarks.
Furthermore, independent evaluations of the models reveal an inability to retrieve information at 300K token context length. However, at 85K tokens, Llama-4 showed glimpses of promises but failed to impress in standard logical puzzles.
Despite the shortcoming, Llama-4 was retrofitted with censorship guardrails, but its open-source nature may see users tweak it in the coming days.
While blockchain is not a priority for Meta, the company is not slowing down on other emerging technologies. AI is the center of its digitalization pivot, with the technology giant racing to integrate its LLMs into its social media platforms.
Outside of AI, Meta has its sights on enterprise applications for the metaverse despite a 20% budget cut in 2024. The company continues to nurture its ambitious goals for the metaverse, merging the offering with AI to create previously unseen experiences for users.
In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek’s coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI.
Watch: The Web3 trifecta: AI, metaverse & blockchain
Recommended for you
