The artificial intelligence (AI) market is projected to reach $243.70 billion in 2025, reflecting the massive financial backing behind AI advancements.

It is not surprising that major technology companies such as Amazon, Google, Meta, and Microsoft plan to invest approximately $320 billion in AI this year.

However, a growing concern lies in the billions being funneled into centralized, closed-source AI models controlled by a few dominant players.

The Security and Ethical Risks of Centralized AI

A few centralized entities dominate AI development, raising security and ethical concerns.

Hugo Feiler, CEO and co-founder of layer-1 network Minima, told Cryptonews that centralized AI systems aggregate large amounts of sensitive data and computational resources in a single hub, creating considerable vulnerabilities.

“Such systems are attractive targets for cybercriminals, and a security breach could lead to the exposure of sensitive information or, even more alarmingly, allow malicious individuals to manipulate AI algorithms,” Feiler said.

He noted that biases in centralized AI systems remain a concern as major tech firms maintain control over AI development.

How Decentralized Data Strengthens AI Integrity

As AI development progresses, the demand for trusted and secure data grows.

Industry experts believe that decentralized data will play a key role in ensuring data integrity for AI innovation moving forward.

Porter Stowell, head of ecosystem and community at Filecoin Foundation, explained that decentralized data is stored across multiple nodes in a distributed network.

“Unlike traditional cloud storage, which relies on a handful of major providers, decentralized data ensures that no single party has unilateral control over access, availability, or security,” Stowell said.

He added that blockchain plays a critical role by providing a transparent and immutable ledger for tracking data storage and retrieval.

“In the case of the Filecoin network, blockchain technology ensures that data is provably stored using cryptographic proofs like Proof-of-Storage and Proof-of-Spacetime, making it tamper-proof and verifiable,” he remarked.

Rowan Stone, CEO of Sapien, told Cryptonews that while not all data needs to be decentralized, the concept plays an important role.

For example, Stone pointed out that banking giant JPMorgan alone holds nearly 120 petabytes of data.

“This is huge in comparison to just 1 petabyte of open internet data OpenAI’s GPT-4o model was trained on,” Stone said. “If we were to quantify the sum of collective human frontier knowledge, it would be close to 5.5 billion petabytes – orders of magnitude beyond what today’s public AI models are trained on.”

Stone elaborated that it’s not challenging to access data, but rather to curate and structure information efficiently.

“Centralized systems struggle to scale, lacking the flexibility to incentivize the right specialists to validate, label, and optimize data at the speed AI development demands. Decentralization solves this,” he said.

Decentralized Data’s Impact Across AI Sectors

A number of companies are working to ensure decentralization becomes the norm, particularly in AI model training.

Ismael Hishon-Rezaizadeh, co-founder and CEO of Lagrange, told Cryptonews that decentralized storage solutions like Filecoin allow data to be stored across multiple nodes, facilitating access to large datasets for model training and inference.

He added that protocols that incentivize users to share their data compensate participants for their contributions.

“These datasets are then used for training models or making predictions based on real-world data,” Hishon-Rezaizadeh said.

For example, Sapien is building a decentralized data foundry—a permissionless protocol where AI models can source human expertise globally. This allows anyone to contribute knowledge to advance AI.

Sapien recently collaborated with carVertical, a company that specializes in vehicle history reporting. CarVertical needed to improve the accuracy and efficiency of its vehicle data processes.

“Traditionally, these types of data labeling tasks rely on centralized teams, which can be slow, costly, and limited by the expertise of a small group creating biases,” Stone said.

By working with Sapien, carVertical was able to match user vehicle queries with correct automobile makes and models.

Contributors from diverse backgrounds then helped refine the system, ensuring accurate search results and minimizing irrelevant matches.

“We trained a decentralized network to tag and verify vehicle identification numbers (VINs),” Stone explained. “This process was supercharged with automation processes, while human validators ensured data accuracy.”

Contributors were able to label thousands of vehicle images, standardizing how cars were displayed in carVertical’s catalog.

This improved both consistency and user experience for the company. Contributors were also rewarded for their work.

Additionally, blockchain was leveraged as a system of accountability.

“The blockchain gives a ledger of value where specific AI models can fine-tune their capabilities through a diverse and ever-expansive network of contributors of various backgrounds,” Stone remarked.

Addressing the Challenges of Decentralized Data Implementation

While decentralized data sets will undoubtedly have an impact on AI models, a number of challenges remain.

Jiahao Sun, founder and CEO at decentralized AI company FLock.io, told Cryptonews that there are concerns around scalability, data verification, and interoperability when it comes to decentralized data sets.

“Blockchain networks can face bottlenecks in processing large volumes of data,” Sun said. “Also, decentralized data can come from multiple, unverified sources. Moreover, many blockchain networks operate in silos, making data sharing complex.”

Sun pointed out that solutions implementing decentralized oracles, reputation systems, and AI-driven validation can improve data reliability.

Cross-chain protocols and decentralized data marketplaces also help bridge the gaps between blockchain networks.

Yet the real concern remains around regulatory and compliance issues. Sun noted that governments are still battling with how to regulate the AI sector, along with decentralized data.

“A balanced approach will be important moving forward and should include compliance frameworks evolving alongside technological innovation,” Sun commented.

While this may be the case, Stone remains confident that AI models will soon shift from data scarcity to diverse data sourced globally through decentralized networks.

“Blockchain will enable trustless AI systems with transparent, verifiable data trails, reducing biases and enhancing accountability,” he said. “We’ll see the rise of incentivized knowledge economies, where individuals actively contribute to AI training for rewards. Ultimately, autonomous AI agents will tap into real-time, crowd-sourced expertise – reshaping how data is created, validated, and shared on a global scale.”

Centralized models have long dictated the flow of data, but mounting vulnerabilities and biases signal the need for a different approach.

A decentralized strategy positions data as a communal asset—one that can be curated, verified, and improved collectively.

A distributed model could redefine AI expectations by improving data transparency and integrity.

The post Why Decentralized Data Is Needed As AI Matures appeared first on Cryptonews.

Cardano is trading below the $0.80 mark as it flirts with a potential rebound after weeks of volatility and selling pressure. The broader crypto market is finding strong demand at current levels, and investors are cautiously optimistic about a quick recovery rally into multi-year highs. Despite the bearish sentiment that has gripped the market recently, many believe that Cardano could lead the charge in reversing the downtrend.

Top analyst Ali Martinez has shared a compelling technical analysis, revealing that Cardano appears to be following a similar pattern to its 2020-2021 price action. Martinez highlights that while the pace is slower this time, the structure mirrors the one that preceded Cardano’s explosive rally during the previous cycle. This historical pattern saw ADA surge significantly, and the current setup suggests that the cryptocurrency might be gearing up for a similar bullish breakout.

Cardano sits at a critical juncture as the market awaits confirmation of this potential trend. Investors are closely watching key levels, hoping that the technical signals and historical comparisons hold true. If Cardano repeats its past performance, it could lead to a substantial recovery, bringing optimism back to the market. The coming days will be crucial in determining whether history truly repeats itself for ADA.

Cardano Shows Bullish Potential

Cardano has faced massive volatility and uncertainty in recent weeks, with the price dropping over 20% in less than a week before recovering more than 25%. Currently, ADA is ranging below key supply levels around $0.82, reflecting the market’s indecision and the ongoing speculation about whether the next move will be a rally or a deeper correction. This consolidation phase has left investors anxious but hopeful for a breakout that could define Cardano’s short-term direction.

A compelling technical analysis shared by top analyst Ali Martinez on X has provided a glimmer of optimism for Cardano holders. Martinez points out that Cardano appears to be repeating the same price pattern observed during the 2020–2021 cycle. 

While the current pace is slower, the structure mirrors the prelude to ADA’s massive parabolic rally during the previous bull market. If history repeats itself, this setup suggests that Cardano could soon break out of its current range and enter a sustained upward trend.

The potential for such a rally hinges on Cardano reclaiming and holding key levels above $0.82 and gaining momentum in a broader market recovery. While the market remains speculative, the parallels with past cycles offer a positive outlook for ADA. 

Investors are closely monitoring these patterns, looking for confirmation that Cardano is ready to break through its consolidation phase and embark on a significant rally. If the historical pattern holds true, ADA could soon lead the market in a powerful move toward multi-year highs, providing much-needed optimism for both Cardano and the broader crypto ecosystem.

ADA Testing A Crucial Resistance Level

Cardano (ADA) is currently trading at $0.78, consolidating below the critical $0.82 supply level. This price previously acted as strong support in December but now serves as resistance, keeping ADA below key levels. Bulls need to reclaim this level as support to signal strength and pave the way for a recovery rally. A successful breakout above $0.82 could set ADA on track to target the $0.90 mark, which aligns with the 200-day moving average, a crucial indicator of long-term market trends.

Despite the potential for a breakout, ADA faces considerable risks as the market remains filled with uncertainty and volatility. If ADA loses the $0.75 mark, it could signal renewed selling pressure, sending the price into lower demand levels. Such a drop would delay any potential recovery and deepen bearish sentiment around Cardano.

Investors are closely watching whether ADA can maintain its current range and push above the $0.82 resistance, as this would confirm a shift in momentum. However, market conditions remain speculative, and bulls need to act decisively to prevent further declines. For now, ADA’s price direction hinges on reclaiming the $0.82 level and sustaining momentum in the face of broader market challenges.

Featured image from Dall-E, chart from TradingView