Marijuana rescheduling is an enormous win and a transformative shift, but it won't make business easier overnight, our columnist writes.
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The Securities and Exchange Commission filed proposed final consent judgments today seeking officer-and-director bars against three former FTX executives who testified against Sam Bankman-Fried, with Caroline Ellison facing a decade-long prohibition, while Gary Wang and Nishad Singh would receive eight-year restrictions.
The filings in Manhattan federal court formalize settlement terms for executives who cooperated extensively with prosecutors during Bankman-Fried’s criminal trial but still face permanent securities law injunctions.
Ellison, Wang, and Singh agreed to permanent injunctions barring future violations of federal antifraud provisions, along with five-year conduct-based restrictions, according to SEC Litigation Release 26450.
The proposed judgments require court approval before taking effect.
The U.S. SEC said it has filed proposed final consent judgments in the Southern District of New York against Caroline Ellison, former CEO of Alameda Research, Zixiao “Gary” Wang, former CTO of FTX, and Nishad Singh, former co-lead engineer of FTX. Subject to court approval, the…
— Wu Blockchain (@WuBlockchain) December 19, 2025
Notably, the latest SEC enforcement action was conducted by Amy Burkart alongside investigators Devlin Su, Ivan Snyder, David Brown, Brian Huchro, and Pasha Salimi under the supervision of Laura D’Allaird and Amy Flaherty Hartman from the Cyber and Emerging Technologies Unit.
The SEC’s original complaints alleged that from May 2019 through November 2022, the executives participated in raising over $1.8 billion from investors through false claims about FTX’s safety measures and risk controls.
Prosecutors charged that Bankman-Fried, Wang, and Singh exempted Alameda Research from automated risk mitigation while granting the trading firm unlimited access to customer deposits.
Wang and Singh wrote software that diverted FTX customer funds to Alameda, while Ellison directed misappropriated assets toward the hedge fund’s trading operations.
Bankman-Fried subsequently transferred hundreds of millions in additional customer funds to Alameda for venture investments and personal loans to executives, including Wang and Singh.
The three defendants consented to final judgments without admitting or denying the SEC’s allegations.
Beyond permanent antifraud injunctions under Securities Exchange Act Section 10(b) and Securities Act Section 17(a), they accepted conduct-based restrictions that would prevent similar violations for five years.
Just days ago, it was discovered that Ellison completed approximately 11 months at Danbury Federal Correctional Institution before transferring to community confinement in October, with her projected release now set for February 2026.
— Cryptonews.com (@cryptonews) December 17, 2025
Caroline Ellison moved to community confinement after 11 months, projected release February 2026 following FTX fraud cooperation.#FTX #Cryptohttps://t.co/gFUZ1a4Tdu
Judge Lewis Kaplan sentenced her to two years despite defense requests for probation, praising her substantial cooperation while maintaining that the fraud’s severity warranted incarceration.
During her September 2024 sentencing hearing, Ellison expressed deep remorse while holding back tears.
“On some level, my brain doesn’t even comprehend all the people I harmed,” she told the court.
Her attorneys had requested no prison time, but Kaplan rejected what he termed a “literal get-out-of-jail-free card” despite acknowledging her unprecedented cooperation.
Federal prosecutors emphasized Ellison’s critical testimony in their September sentencing recommendation, noting the “what” and “how” of the crimes would have been difficult to prove without her three days of trial testimony.
She revealed that Bankman-Fried instructed executives to invest billions in customer assets that had been secretly siphoned from FTX through Alameda Research.
Wang and Singh received time-served sentences with supervised release after testifying that Bankman-Fried directed the creation of an “allow negative” feature that granted Alameda nearly unlimited access to customer funds.
Both avoided additional prison time entirely following their cooperation.
FTX’s Chapter 11 reorganization plan resumed distributions in May 2025, delivering between 119% and 143% to eligible creditors who completed verification requirements through designated service providers BitGo or Kraken.
Around 98% of affected users with claims under $50,000 received 119% of their declared funds under the bankruptcy court’s approved restructuring framework.
Bankman-Fried remains incarcerated at a low‑security Federal Correctional Institution Terminal Island in Los Angeles, serving his 25-year sentence following conviction on seven fraud and conspiracy counts.
— Cryptonews.com (@cryptonews) November 3, 2025
Sam Bankman-Fried (SBF) is pushing for a new trial this week following his 2023 conviction tied to his time at FTX.#SBF #FTXhttps://t.co/xEIAr7gcJE
Most recently, his November appeal hearing challenged the claim that he was “presumed guilty,” asserting that he was denied fair trial procedures.
At the same time, his family continues to seek presidential clemency, arguing that FTX maintained sufficient assets to repay all customers in full throughout the collapse.
The post SEC Seeks 10-Year Ban for Ellison, 8 Years for Wang and Singh appeared first on Cryptonews.
BlackRock’s spot Bitcoin exchange-traded fund IBIT, has emerged as a notable outlier on the 2025 ETF flow leaderboard, ranking sixth by year-to-date inflows despite posting a negative return for the year, according to data highlighted by Bloomberg Intelligence analyst Eric Balchunas.
$IBIT is the only ETF on the 2025 Flow Leaderboard with a negative return for the year. CT's knee-jerk reaction is to whine about the return but the real takeaway is that is was 6th place DESPITE the negative return (Boomers putting on a HODL clinic). Even took in more than $GLD… pic.twitter.com/68uq3HFRuO
— Eric Balchunas (@EricBalchunas) December 19, 2025
IBIT is currently the only ETF among the top flow leaders showing a year-to-date loss, with returns down roughly 9.6%. Yet the fund has still attracted approximately $25.4 billion in net inflows, placing it ahead of a range of established equity and commodity products — including the SPDR Gold Trust (GLD), which is up more than 64% over the same period.
The divergence between price performance and investor demand underscores a structural shift in how capital is engaging with Bitcoin exposure through regulated vehicles. Rather than reacting to short-term price movements, investors appear to be using periods of drawdown to accumulate positions via ETFs.
\Balchunas describes the trend as a “HODL clinic,” suggesting that longer-term allocators are increasingly driving flows into spot Bitcoin ETFs, treating them as strategic holdings rather than momentum trades.
By comparison, the largest inflows in 2025 have gone to broad-based equity ETFs such as Vanguard’s S&P 500 tracker VOO, which has drawn more than $145 billion in net inflows alongside a mid-teens return. Other top-ranking funds include large-cap and total market products such as IVV, VTI, and SPYM, all benefiting from strong equity market performance.
IBIT’s presence among these vehicles is notable given Bitcoin’s higher volatility and its relatively recent introduction as an ETF asset class.
The data also highlights a contrast with gold ETFs. While GLD has benefited from strong price appreciation in 2025, its inflows have lagged behind IBIT’s, indicating that performance alone has not been the primary driver of allocation decisions this year.
According to Balchunas, the more significant takeaway may be what IBIT’s inflows imply for future cycles. If a Bitcoin ETF can attract more than $25 billion in a year marked by negative returns, the potential for substantially larger inflows during a strong market environment could be considerable.
As spot Bitcoin ETFs continue to mature within traditional portfolio frameworks, flow data is increasingly being viewed as a leading indicator of long-term adoption. IBIT’s 2025 performance suggests that, even amid price weakness, investor conviction in regulated Bitcoin exposure remains resilient.
The post Bitcoin ETF IBIT Ranks Among Top 2025 Fund Flows Despite Negative Returns appeared first on Cryptonews.
AI is transforming the data center — and straining its limits.
Traditional cooling methods can’t keep up with the rising density and power demands of artificial intelligence (AI) workloads, which are expected to drive a 4.2x increase in data center energy consumption between 2023 and 2028. In response, organizations are modernizing their infrastructure to achieve new performance goals without compromising energy efficiency or sustainability.
This is the story of how Schneider Electric turned inward, using its own liquid cooling and infrastructure offerings to reshape its global IT operations.
Schneider Electric manages the data of over 130,000 employees across more than 200 plants and distribution sites worldwide, supporting 7 million compute hours per month with 46 petabytes of live storage. It’s one of the largest internal IT footprints in the world. As AI drove a surge in demand for high-density compute, conventional air cooling became insufficient.
Schneider also faced visibility, efficiency, and uptime challenges. Coordinating and optimizing energy across global locations with different workloads and equipment required new levels of monitoring, insight, and control. These demands led Schneider to pursue liquid cooling alongside new monitoring and infrastructure management tools.
Liquid cooling absorbs and transfers heat away from servers more efficiently than air, allowing data centers to support hotter chips, denser racks, and higher-performance systems without significantly increasing energy use. It also helps reduce cooling energy consumption, improve thermal efficiency, and shrink the physical footprint required to run advanced workloads. These capabilities are increasingly vital for organizations balancing aggressive AI adoption with equally aggressive carbon reduction goals.
Schneider Electric first established a baseline: How much energy was its IT infrastructure consuming, and where were the biggest opportunities to reduce load and emissions? Its EcoStruxure IT Data Center Infrastructure Management platform captured real-time power and emissions data across sites, then its Resource Advisor team built a dashboard to visualize trends over time. This allowed the company to make more informed decisions about refresh cycles and new technology migrations.
Schneider upgraded cooling systems to InRow Cooling units, deployed Smart-UPS devices to field locations to reduce downtime, and modernized its rack infrastructure with NetShelter solutions. Across all global sites, these changes addressed Schneider’s core challenges: modernizing cooling infrastructure, enhancing energy visibility, improving operational efficiency, and increasing uptime.
The benefits came almost immediately. In just one year, Schneider achieved:
These results reinforced Schneider’s belief in liquid cooling as a driver of high-performance, sustainable infrastructure.
Schneider Electric demonstrated how AI preparations must go beyond capacity planning. Modern organizations need to rethink how they build, cool, and manage infrastructure to meet the challenges of the future.
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Similar pledges to fight scam networks were made by members of the Association of Southeast Asian Nations in the months leading up to the Bangkok conference.
The post Thailand Conference Launches International Initiative to Fight Online Scams appeared first on SecurityWeek.
Microsoft and NASA say they’re applying artificial intelligence to a challenge that has become increasingly urgent: how to cope with flooding and other disasters driven by extreme weather.
The result of their efforts is Hydrology Copilot, a set of AI agents aimed at making hydrological data easier to access and analyze. The platform is built on the foundation that was established for NASA Earth Copilot, a cloud-based AI tool that can sift through petabytes of Earth science data.
Hydrology is the scientific study of Earth’s water cycle, which encompasses precipitation, runoff, evaporation and the movement of water through rivers, lakes and soil. It’s not just an academic exercise: Hydrologic insights are put to use in fields ranging from agriculture to forestry to urban development.
“NASA has long produced advanced hydrology and land-surface datasets, powering breakthroughs in drought early-warning systems, environmental planning and environmental research,” Juan Carlos López, a senior solution specialist at Microsoft who focuses on space and AI, wrote in a blog post. “Yet despite their value, these datasets and the specialized tools required to navigate and interpret them remain difficult to access for many who could benefit most.”
That’s where Hydrology Copilot comes in: Powered by Microsoft Azure OpenAI Service and Microsoft Foundry, the platform lets researchers and others query NASA’s data using straightforward questions — for example, “Which regions may be facing elevated flood risk?”
Hydrology Copilot simplifies access to one of NASA’s most advanced hydrology datasets, the North American Land Data Assimilation System Version 3. The dataset integrates satellite measurements with computer models to present a continuously updated, high-resolution, continental-scale view of the water cycle.
Insights gleaned from the database can help planners figure out how to improve drought monitoring, agricultural planning, water resource management, flood risk assessment and emergency preparedness. Recent flooding in Western Washington, fueled by a succession of atmospheric rivers, shows how important it can be to gain such insights — and how useful Hydrology Copilot can be.
“The goal of this project is to provide the tools that can enable local officials, city planners and emergency responders to more easily understand weather patterns and better prepare for the types of hydrological events we are seeing now in the Pacific Northwest and around the world, and will likely continue to see in the future,” a Microsoft spokesperson told GeekWire in an emailed statement.
Hydrology Copilot is still under development, and is being used primarily by researchers for now. Microsoft’s Azure AI team can provide further information about the platform. To take a test spin through more publicly accessible hydrology datasets, check out King County’s Hydrologic Information Center and the interactive map provided by the National Water Prediction Service.
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