Hyperliquid will adopt a new system to calculate fees on the platform, which includes different tiers for staking as well as separate fee schedules for perpetual contracts and spot trading. In a recent post, the decentralized exchange announced that it…

Hyperliquid unveils new fee discount system and account linking feature for May 5

SoFi CEO Anthony Noto said the company is preparing to re-enter the crypto 
market and integrate blockchain technology across all major business lines, as 
regulatory conditions continue to improve. The comments came during an 
interview with CNBC, where Noto outlined…

‘We’re going to reenter crypto’: SoFi CEO says blockchain will touch all products

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_**Opinion by: Felix Xu, co-founder of ARPA Network and Bella Protocol**_
AI has been a dominant narrative since 2024, but users and companies still 
cannot completely trust it. Whether it&#8217;s finances, personal data or healthcare 
decisions, hesitation around AI&#8217;s reliability and integrity remains high.
This growing AI trust deficit is now one of the most significant barriers to 
widespread adoption. Decentralized, privacy-preserving technologies are 
quickly being recognized as viable solutions that offer verifiability, 
transparency and stronger data protection without compromising AI&#8217;s growth.
## The pervasive AI trust deficit
AI was the second most popular category occupying crypto mindshare in 2024, 
with over 16% investor interest. Startups and multinational companies have 
allocated considerable resources to AI to expand the technology to people&#8217;s 
finances, health, and every other aspect.
For example, the emerging DeFi x AI (DeFAI) sector shipped more than 7,000 
projects with a peak market cap of $7 billion in early 2025 before the markets 
crashed. DeFAI has demonstrated the transformative potential of AI to make 
decentralized finance (DeFi) more user-friendly with natural language 
commands, execute complex multi-step operations, and conduct complex market 
research.
Innovation alone hasn&#8217;t, however, solved AI&#8217;s core vulnerabilities: 
hallucinations, manipulation and privacy concerns.
In November 2024, a user convinced an AI agent on Base to send $47,000 despite 
being programmed never to do so. While the scenario was part of a game, it 
raised real concerns: Can AI agents be trusted with autonomy over financial 
operations?
Audits, bug bounties and red teams help but don&#8217;t eliminate the risk of prompt 
injection, logic flaws or unauthorized data use. According to KPMG (2023), 61% 
of people still hesitate to trust AI, and even industry professionals share 
that concern. A Forrester survey cited in Harvard Business Review found that 
25% of analysts named trust as AI&#8217;s biggest obstacle.
That skepticism remains strong. A poll conducted at The Wall Street Journal&#8217;s 
CIO Network Summit found that 61% of America&#8217;s top IT leaders are still 
experimenting with AI agents. The rest were still experimenting or avoiding 
them altogether, citing lack of reliability, cybersecurity risks and data 
privacy as top concerns.
Industries like healthcare feel these risks most acutely. Sharing electronic 
health records (EHR) with LLMs to improve outcomes is promising, but it is 
also legally and ethically risky without airtight privacy protections.
For example, the healthcare industry suffers adversely from data privacy 
breaches. This problem compounds when hospitals share EHR data to train AI 
algorithms without protecting patient privacy.
## Decentralized, privacy-preserving infrastructure
J.M. Barrie wrote in _Peter Pan_ , &#8220;All the world is made of faith, and trust, 
and pixie dust.&#8221; Trust isn&#8217;t just a nice to have in AI &#8212; it&#8217;s foundational. 
AI&#8217;s projected economic boon of $15.7 trillion by 2030 may never materialize 
without it.
Enter decentralized cryptographic systems like zero-knowledge succinct non- 
interactive arguments of knowledge (ZK-SNARKs). These technologies offer a new 
path: allowing users to verify AI decisions without revealing personal data or 
the model&#8217;s inner workings.
By applying privacy-preserving cryptography to machine learning 
infrastructure, AI can be auditable, trustworthy and privacy-respecting, 
especially in sectors like finance and healthcare.
_**Recent:**__**Blockchain &#8216;s next big breakthroughs: What to watch**_
ZK-SNARKs rely on advanced cryptographic proof systems that let one party 
prove something is true without revealing how. For AI, this enables models to 
be verified for correctness without disclosing their training data, input 
values or proprietary logic.
Imagine a decentralized AI lending agent. Instead of reviewing full financial 
records, it checks encrypted credit score proofs to make autonomous loan 
decisions without accessing sensitive data. This protects both user privacy 
and institutional risk.
ZK technology also addresses the black-box nature of LLMs. By using dynamic 
proofs, it&#8217;s possible to verify AI outputs while shielding both data integrity 
and model architecture. That&#8217;s a win for users and companies &#8212; one no longer 
fears data misuse, while the other safeguards its IP.
## Decentralized AI
We&#8217;re entering a new phase of AI where better models aren&#8217;t enough. Users 
demand transparency; enterprises need resilience; regulators expect 
accountability.
Decentralized, verifiable cryptography delivers all three.
Technologies like ZK-SNARKs, threshold multiparty computation, and BLS-based 
verification systems aren&#8217;t just &#8220;crypto tools&#8221; &#8212; they&#8217;re becoming the 
foundation of trustworthy AI. Combined with blockchain&#8217;s transparency, they 
create a powerful new stack for privacy-preserving, auditable and reliable AI 
systems.
Gartner predicted that 80% of companies will be using AI by 2026. Adoption 
won&#8217;t be driven by hype or resources alone. It will hinge on building AI that 
people and companies can actually trust.
And that starts with decentralization.
_**Opinion by: Felix Xu, co-founder of ARPA Network and Bella Protocol.**_
This article is for general information purposes and is not intended to be and 
should not be taken as legal or investment advice. The views, thoughts, and 
opinions expressed here are the author&#8217;s alone and do not necessarily reflect 
or represent the views and opinions of Cointelegraph.

AI has a trust problem — Decentralized privacy-preserving tech can fix it

**Key points:**
 * Bitcoin&#8217;s most recently-moved supply segment is increasing as higher prices see an influx of &#8220;speculative capital.&#8221;
 * &#8220;Hot supply&#8221; has doubled in just five weeks versus local lows in March.
 * Active address numbers have yet to mimic a classic bull market comeback.
Bitcoin (BTC) short-term holders (STHs) are back in the game as a &#8220;speculative 
capital&#8221; enters the market.
In an X thread on April 29, onchain analytics firm Glassnode reported a surge 
in Bitcoin&#8217;s so-called &#8220;hot capital.&#8221;
## Bitcoin sees &#8220;surge in capital turnover&#8221;
New investors are entering the market as BTC price action circles its highest 
levels in several months.
Glassnode reveals that the sum of coins which last moved up to a week ago has 
reached its largest figure since early February.
&#8220;This metric captures short-term holder activity and is a proxy for 
speculative capital entering the market,&#8221; it explains.
In the past week alone, hot capital has shot up by over 90% to near $40 
billion. Since local lows in late March, hot capital has increased by $21.5 
billion, a &#8220;surge in capital turnover&#8221; which underscores a sea change in 
market sentiment.
&#8220;BTC hot capital bottomed at $17.5B on 23 Mar &#8211; its lowest level since Dec,&#8221; 
Glassnode summarizes.
&gt; &#8220;In just 5 weeks, it has added over $21.5B, suggesting a rapid shift from 
&gt; dormancy to speculation among newer market entrants.&#8221;
_Bitcoin &#8220;hot supply&#8221; data. Source: Glassnode/X_
## BTC bull market comeback in progress
As Cointelegraph continues to report, STH investors have recently returned to 
aggregate profit as price hovers near $95,000.
_**Related:**__**Bitcoin in &#8216;critical zone&#8217; as triple breakout meets $93.5K 
support battle**_
Analyzing overall network participation, however, Glassnode suggested that a 
full bull market comeback has not yet taken place.
&#8220;Signs of early FOMO are emerging, with the Hot Capital Share ticking higher 
and profitability metrics like Percent Supply in Profit (86%) and NUPL (0.53) 
expanding notably,&#8221; it wrote in an introduction to its latest &#8220;Market Pulse&#8221; 
analysis piece released on April 28.
&gt; &#8220;However, while on-chain activity such as transfer volume and fees are 
&gt; recovering, daily active addresses remain suppressed, suggesting that full 
&gt; organic network engagement is still rebuilding.&#8221;
_Bitcoin active addresses (7-day simple moving average). Source: Glassnode_
Earlier this week, other sources reported on the potential dangers of &#8220;FOMO&#8221; 
when it comes to an enduring BTC price recovery.
This article does not contain investment advice or recommendations. Every 
investment and trading move involves risk, and readers should conduct their 
own research when making a decision.
New analysis on April 29 from Axel Adler Jr., a contributor to onchain 
analytics platform CryptoQuant, shows

Bitcoin 'hot supply' nears $40B as new investors flood in at $95K

Bitcoin ETFs notched their seventh consecutive day of inflows, driven by 
Blackrock’s massive $971 million addition, despite sizable withdrawals from 
ARKB and FBTC. Ether ETFs also held firm, posting a third day of gains with 
$64 million in net inflows. Blackrock Powers Inflow Into Bitcoin ETFs as Ether 
ETFs Hold Momentum With Third Day of […]