The reactivation of dormant Bitcoin wallets could signal increased market 
volatility and influence investor sentiment amid economic shifts.
The post Bitcoin whale awakens after 14 years, sitting on $148 million 
windfall appeared first on Crypto Briefing.

Bitcoin whale awakens after 14 years, sitting on $148 million windfall

TradFi is taking another step into fully embracing bitcoin as an asset. Morgan 
Stanley is creating its own Bitcoin investment fund that will trade on the 
stock market like a regular exchange‑traded fund (ETF) share. To get it 
started, the lender is putting in about $1 million of its own money as seed 
capital. Related Reading: Legendary Bitcoin Trader Says HYPE Will Soar To 
$150, Here’s Why A TradFi Bitcoin Trust Morgan Stanley has filed another 
amended S‑1/A for the Morgan Stanley Bitcoin Trust (MSBT), confirming ticker 
MSBT on NYSE Arca. The bank outlined the ticker symbol in a new submission to 
the U.S. Securities and Exchange Commission, revising the Bitcoin fund 
proposal it first filed in January. The Morgan Stanley Bitcoin Trust would be 
the first spot Bitcoin ETF not just distribute but directly issued by a major 
U.S. bank. It would also mark the first time that the seed basket cash will be 
used to acquire spot BTC before trading begins. We are talking about a 
50,000‑share seed basket and roughly $1 million in initial capital. The trust 
is set to hold bitcoin via custodians (Coinbase Custody and BNY Mellon under 
the broader ETF plan), with assets stored primarily in cold storage, and 
shares reflecting the underlying BTC held. Once it launches, regular investors 
(especially Morgan Stanley clients) will be able to buy and sell MSBT through 
their normal brokerage accounts, getting regulated, brokerage‑account exposure 
to bitcoin’s price without touching self‑custody or spot exchanges directly. 
The trust will also to support both cash and in‑kind creations/redemptions, 
giving authorized participants (APs) flexibility, just like the main spot 
Bitcoin ETFs that launched in 2024 Trading And Risk Assessment However, it is 
worth noting custodians are not FDIC‑insured. This means that if something 
goes wrong (hack, theft, failure), you don’t have the government safety net 
that protects U.S. bank deposits up to a certain amount. Besides that, 
insurance is through private policies, and the ETF still faces market, 
regulatory and operational risk, especially in a crowded field dominated by 
BlackRock’s IBIT and other early movers. Related Reading: Hyperliquid Breaks 
Crypto Wall? Fiat On-Ramp Lets Anyone Trade With Bank Card Morgan Stanley 
already holds hundreds of millions in existing BTC ETFs and is building a 
broader crypto stack (Ethereum and Solana filings, trust‑bank application for 
custody, advisor access to BTC products). A bank‑issued MSBT product could 
normalize bitcoin exposure for traditional wealth‑management clients, 
strengthen the “Bitcoin as strategic asset” narrative, and extend the 
institutional ETF cycle. MSBT’s launch timeline, fee level and early inflows 
will be key sentiment catalysts. Strong demand could reinforce BTC’s 
ETF‑driven structural bid, while a lukewarm debut would signal saturation in 
the U.S. spot Bitcoin ETF trade. At the moment of writing, BTC trades on the 
highs $70k. Source: BTCUSD on Tradingview Cover image from Perplexity, BTCUSD 
chart from Tradingview

Bitcoin Just Got A $1 Million Nudge, But Will Morgan Stanley’s MSBT ETF Really Move The Needle?

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Bittensor’s TAO ripped higher on Thursday and topped in early European trading 
on Friday after Nvidia CEO Jensen Huang highlighted the project on the All-In 
podcast, pushing the token from $243.5 to $310.6 before it cooled to $298.1 by 
press time. The move put one of crypto’s most closely watched AI-linked assets 
back in focus, not because Huang endorsed the token directly, but because he 
treated the underlying technical milestone as meaningful in a much bigger 
debate over open AI infrastructure. The moment came when Chamath Palihapitiya 
pointed Huang to what he called a “pretty crazy technical accomplishment” 
inside “this crypto project called Bittensor.” He described a recent training 
run on Subnet 3 in which participants used distributed excess compute to train 
a Llama model “totally distributed” while still managing the process 
statefully. Nvidia CEO Responds To Bittensor&#8217;s Accomplishment Huang’s 
immediate reaction was brief but memorable: “Our modern version of 
Folding@home.” That line mattered because it effectively reframed Bittensor’s 
latest milestone in language traditional tech audiences already understand. 
Folding@home was one of the most recognizable examples of decentralized 
volunteer computers; Huang’s comparison suggested he viewed Bittensor’s 
experiment less as crypto theater and more as a legitimate expression of 
distributed coordination. Related Reading: Austin Arnold Unveils His Top 6 
Crypto Altcoin Picks For 2026 In the context of TAO’s price action, traders 
appeared to read that as external validation from one of the most influential 
executives in AI hardware. Huang then widened the discussion beyond Bittensor 
itself and into the structure of the AI market. “I believe we fundamentally 
need models as first-class products, proprietary products, as well as models 
as open source. These two things are not A or B, it’s A and B. There’s no 
question about it,” he said. He followed that with an even sharper 
distinction: “Models are a technology, not a product. Models are technology, 
not a service.” Related Reading: Is Dogecoin About To Repeat NVIDIA’s Run? 
Here’s What The Chart Says He spent the next stretch explaining why that dual- 
track model matters. For general-purpose consumer use, Huang said most people 
will continue to prefer turnkey services rather than fine-tuning their own 
systems. “I would really, really love not to go fine-tune my own. I would 
really love to keep using ChatGPT. I love to use Claude. I love to use Gemini. 
I love to use X,” he said, arguing that this horizontal layer of AI products 
“is thriving” and “is going to be great.” On the @theallinpod this week, 
@chamath asked @nvidia CEO Jensen Huang about decentralized AI training, 
calling our Covenant-72B run &#8220;a pretty crazy technical accomplishment.&#8221; One 
correction: it&#8217;s 72 billion parameters, not four. Trained permissionlessly 
across 70+ contributors… pic.twitter.com/BN0tWG66e8 — templar (@tplr_ai) March 
19, 2026 But he drew a hard line when it came to industry-specific deployment, 
saying domain expertise “has to be captured in a way that they can control,” 
and that “it can only come from open models.” That distinction goes to the 
heart of why Bittensor reacted so violently. While Huang didn’t make a token 
call, or presented Bittensor as the winner of open AI, he did endorse the 
coexistence of proprietary and open model ecosystems, while acknowledging that 
specialized industries will need more controllable, open foundations. At press 
time, TAO traded at $297.0 Featured image created with DALL.E, chart from 
TradingView.com

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