Citigroup has raised its 12-month price targets for bitcoin and ether, pointing to renewed institutional demand, a more supportive macroeconomic environment, and expectations that cryptocurrency exchange-traded fund inflows will resume after a period of weakness.

The bank lifted its bitcoin target to $113,000 from $82,000 and raised its ether forecast to $3,028 from $2,240, representing substantial increases in both projections as the broader crypto market regains momentum after months of trailing other risk assets.

Citi expects cryptocurrency investment flows to return at a slower but more consistent pace as financial advisers, brokerages and other traditional investment channels gradually increase their allocations to bitcoin. The bank forecasts about $5 billion in crypto inflows over the next 12 months, indicating that it expects institutional participation rather than speculative retail activity to provide an important source of demand.

The revised outlook comes as bitcoin and ether have staged a strong three-month rebound. Bitcoin has gained nearly 40% during the period, while ether has risen about 68%, narrowing their year-to-date declines to roughly 4% and 9%, respectively.

The difference in performance is significant because crypto had spent much of the earlier period lagging broader risk assets. Citi’s latest assessment suggests that the market is beginning to benefit from a combination of renewed fund flows and a macroeconomic backdrop that has become more favorable for assets sensitive to liquidity and investor risk appetite.

Citi’s forecast puts particular weight on the role of ETF demand. The emergence of spot bitcoin and ether ETFs has created a regulated channel through which traditional investors can gain exposure to the assets without directly holding cryptocurrencies, making the pace of inflows a necessary indicator of institutional demand.

The bank expects those flows to resume gradually rather than return in a sudden surge. That matters because a slower, steadier accumulation of bitcoin through advisers and brokerages could provide a more durable source of demand than the rapid speculative buying that has historically characterized crypto rallies.

Bitcoin has already risen about 40% from its July lows. The recovery has coincided with a softer US dollar and renewed attention to liquidity conditions after the US Treasury moved to buy back longer-dated government bonds.

A weaker dollar can provide support for dollar-denominated alternative assets by improving financial conditions and increasing the attractiveness of assets outside traditional cash and fixed-income instruments. For crypto, that effect can be amplified when investors are simultaneously looking for assets that can benefit from greater liquidity.

Citi’s forecast therefore rests on more than a simple continuation of recent price momentum. Its thesis assumes that the underlying pool of institutional capital available to crypto will continue expanding, even if the pace of new investment remains more measured than during previous periods of aggressive inflows.

The outlook also highlights the growing importance of financial intermediaries to the cryptocurrency market. As advisers and brokerages become more comfortable allocating client assets to bitcoin, even modest portfolio allocations can translate into sizeable flows because of the scale of assets managed by traditional financial institutions.

Regulatory Uncertainty Remains A Constraint

The more constructive outlook comes against a less straightforward regulatory backdrop in the United States.

The US Senate last week failed to advance the Clarity Act, legislation intended to establish a broader regulatory framework for digital assets. The setback narrowed the immediate path toward comprehensive market-structure legislation and represented another reminder that regulatory certainty remains incomplete for the cryptocurrency industry.

Citi nevertheless stated that developments from the Securities and Exchange Commission helped limit the negative market reaction.

“The Clarity Act’s failure narrowed the path to a market-structure bill, yet spurred Securities and Exchange Commission (SEC) rule announcements that dampened negative sentiment,” Citi said in its note dated Wednesday.

That assessment captures the fragmented nature of crypto regulation. The absence of a comprehensive legislative framework does not necessarily eliminate institutional demand, particularly when investors can operate through regulated investment products. At the same time, uncertainty around market structure, token classification, and regulatory oversight remains an important risk for an industry that is increasingly dependent on mainstream financial institutions.

Therefore, the market is being shaped by two forces moving at different speeds for bitcoin and ether. Capital-market infrastructure around crypto has continued to develop, while the underlying regulatory framework remains unfinished.

Citi’s higher targets imply that the bank expects the expansion of institutional access and improving liquidity conditions to outweigh those constraints over the next year. Its $5 billion inflow forecast also provides a more concrete basis for the bullish outlook, since sustained ETF demand would give the market a source of buying pressure beyond short-term trading activity.

Still, the scale of the recent rebound means expectations have already moved higher. Bitcoin’s 40% advance from its July low and ether’s much larger three-month gain leave both assets more dependent on continued flows and favorable financial conditions to sustain the recovery.

Analysts expect the key test for Citi’s thesis to be whether ETF inflows can transition from intermittent bursts of demand into a steady institutional allocation cycle. If advisers and brokerages continue increasing exposure, the market could have a more persistent source of demand. If those flows fail to materialize, the recent rally would face a much weaker fundamental support base.

However, Citi is currently betting that the combination of renewed ETF demand, a softer dollar, and improving macroeconomic conditions can carry bitcoin to $113,000 and ether to $3,028 over the next 12 months. The forecasts raise the bar for the crypto market, placing greater importance on actual capital flows rather than price momentum alone.

The Pentagon is creating a new four-star military command dedicated to autonomous and robotic warfare, as Defense Secretary Pete Hegseth seeks to accelerate the U.S. military’s adoption of drones, artificial intelligence, and other low-cost autonomous systems.

Hegseth announced the Autonomous Warfare Command, or AutoWarCom, on Wednesday during a “State of the Force” address at Marine Corps Base Quantico in Virginia. The command will have “service-like authorities” and is intended to scale autonomous and robotic capabilities across the joint force.

The initiative represents the first creation of a new U.S. combatant command since Space Command was established in 2019. The Pentagon currently has 11 combatant commands covering geographic regions and specific military missions; AutoWarCom would become the 12th.

“The pace of war is changing faster than the process to support it,” Hegseth said.

He pointed to advances in computing, artificial intelligence, and commercial manufacturing as forces changing the economics of warfare.

“Cheap compute, superintelligence, and advanced commercial manufacturing have enabled the proliferation of low-cost, high-precision strike,” Hegseth said.

The command is intended to address that shift by giving autonomous systems their own institutional structure, acquisition authority, and personnel pathways rather than leaving development scattered across existing military organizations.

According to a Pentagon memo released alongside the announcement, the command is targeted for establishment by October 1, 2027. The process will require congressional action, while the Pentagon develops the organization through an interim effort known as Project Agincourt. The command is expected to have dedicated manpower, budget, and acquisition authorities.

The announcement reflects a growing recognition inside the Pentagon that the economics of warfare are changing.

For decades, the U.S. military has relied heavily on sophisticated and extremely expensive platforms, including fighter aircraft, ships, armored vehicles and precision weapons. Those systems provide capabilities that inexpensive drones cannot simply replace, but their cost can make them difficult to deploy at scale against an adversary able to produce large quantities of cheaper systems.

Hegseth framed the emerging model as a combination of high-end weapons and mass-produced autonomous systems.

“Today we need both quality and quantity,” he said.

The Pentagon’s challenge is not just about developing more capable weapons. It is developing systems quickly enough, cheaply enough, and in sufficient numbers to match the pace at which battlefield technology is evolving.

The new command is intended to bring those requirements together across the military. Its portfolio is expected to include drones, artificial intelligence, and command-and-control systems, with the goal of moving autonomous capabilities from experimentation into routine military operations.

That institutional shift could also alter the Pentagon’s procurement process. Traditional defense programs can take years to move from design to deployment, while commercial AI and drone technologies can evolve on much shorter cycles.

Hegseth’s criticism is that the military’s acquisition system is not moving at the same speed as the technology available to potential adversaries.

The Pentagon has already created a task force focused on countering drones, but AutoWarCom is designed to address the other side of the equation: developing and deploying the autonomous systems themselves.

Ukraine Has Become A Test Case For Drone Warfare

The war in Ukraine has provided one of the clearest demonstrations of how inexpensive unmanned systems can change battlefield operations.

Ukraine, facing disadvantages in conventional armor and aircraft, has made extensive use of relatively inexpensive drones for reconnaissance, targeting and attack. Russia has also deployed large numbers of drones, turning the battlefield into an environment in which inexpensive unmanned systems can threaten far more costly military equipment.

Reuters reported that drones are estimated to account for about 70% of Russian casualties, highlighting the extent to which unmanned systems have become integrated into modern combat.

The lesson for the Pentagon is not simply that drones are replacing traditional weapons. Instead, warfare is increasingly becoming a layered system in which expensive aircraft, missiles and ships operate alongside large numbers of cheaper autonomous platforms. A military that can produce and deploy thousands of relatively inexpensive systems may be able to impose costs on an adversary without exposing pilots and other personnel to the same level of risk.

Hegseth’s emphasis on both “quality and quantity” reflects that emerging model.

It also explains why the Pentagon is increasingly looking toward commercial technology companies. Advances in processors, AI models, sensors, communications, and manufacturing are coming from the private sector, where development cycles are generally faster than those of traditional defense programs.

AutoWarCom is meant to provide the military with an institutional mechanism for absorbing those technologies more quickly.

AI Introduces A New Security Problem

The move also carries risks that extend beyond procurement and battlefield efficiency.

AI-enabled military systems can process information and make decisions faster than humans, but increasing autonomy creates questions about reliability, accountability, and human control over the use of force.

Security experts have warned that an accelerating technology competition between the United States and China could increase those risks, particularly if autonomous systems become connected to sensitive military operations or nuclear command structures.

Both U.S. and Chinese experts have called for guardrails and greater consensus around the use of AI in military systems, including nuclear weapons. That tension is becoming more consequential as both countries invest heavily in advanced AI. The United States is trying to preserve its technological lead while China is rapidly expanding its own capabilities in AI, robotics and autonomous systems.

The creation of AutoWarCom signals that the Pentagon views autonomy not as an isolated technology program but as an organizational and operational capability.

The new command will also need to solve a practical problem: turning large numbers of autonomous systems into an effective military force. That requires more than buying drones. It involves software, communications networks, sensors, electronic warfare defenses, logistics, command structures, trained personnel, and systems capable of operating when communications are disrupted.

The Pentagon’s decision to create dedicated career pathways for personnel working with autonomous systems is an acknowledgment of that requirement.

However, experts note that, for the U.S. military, the shift could eventually alter the balance between exquisite but expensive platforms and cheaper systems designed to be produced and replaced at scale.

Alphabet is preparing to put its artificial intelligence chips into orbit on Thursday, using a SpaceX Falcon 9 rocket to conduct the first in-orbit test of a project aimed at turning space into a potential new location for large-scale AI computing.

The launch, scheduled for 11:15 a.m. PT from Vandenberg Space Force Base in California, will carry Planet Labs satellites aboard SpaceX’s uncrewed Transporter-18 mission. One of the satellites will be a solar-powered prototype equipped with Google’s tensor processing units, or TPUs.

The mission marks the first orbital test of Project Suncatcher, an initiative Alphabet unveiled in November 2025 to investigate whether solar-powered computing infrastructure could eventually support AI workloads in space.

Alphabet described the project as an effort to determine “whether space could one day host scalable machine learning infrastructure.”

The idea marks a significant departure from the conventional data-center model, in which AI companies build large facilities on the ground and compete for electricity, land, cooling capacity and connections to already-strained power grids.

Google is instead exploring whether some of those constraints could be addressed by moving the computing infrastructure above the atmosphere.

Low Earth orbit offers one potential advantage that has attracted growing interest from the technology and space industries: abundant sunlight.

Alphabet said satellites in low Earth orbit can access near-constant sunlight and generate up to eight times more solar power than equivalent systems on Earth. The company eventually envisions linking multiple satellite constellations together so they can collectively handle larger AI workloads in orbit.

That would turn individual satellites into components of a distributed computing network rather than simply communications or observation platforms.

The concept remains highly experimental. Alphabet has already tested its TPUs running AI workloads at a facility at the University of California, Davis, but Thursday’s mission will provide the first opportunity to observe how the chips operate in the substantially harsher environment of low Earth orbit.

The test will matter much to the AI industry because conventional data centers rely on extensive infrastructure to maintain stable operating conditions. Space removes many of those physical advantages while introducing different problems, including radiation, extreme temperature variations, and the difficulty of dissipating heat.

AI chips generate substantial amounts of heat, meaning a space-based data center would need specialized cooling systems that can function without the conventional cooling infrastructure available on Earth.

The economics present another hurdle. Launch capacity remains limited and expensive, meaning that putting large amounts of computing hardware into orbit currently carries a significant transportation cost. Orbital debris and congestion could add another operational risk as more satellites are deployed.

Those constraints make space-based AI computing a long-term proposition rather than an immediate alternative to terrestrial data centers. But the potential payoff is large enough for major technology and space companies to begin testing the concept.

Alphabet and SpaceX Converge on Orbital Computing

SpaceX has been one of the most vocal proponents of space-based computing, arguing that orbit offers effectively “infinite real estate” at a time when AI companies are facing growing opposition to large data-center developments on Earth.

The company is also developing its own orbital data-center concept. SpaceX plans to deploy swarms of satellites equipped with graphics processing units and solar arrays, with the hardware expected to be manufactured in part through Tesla, Elon Musk’s electric-vehicle company.

Musk said earlier this year that space-based data centers would eventually become the cheapest way to train AI and argued that this could happen within two or three years. SpaceX’s historic IPO earlier this year was largely based on that.

SpaceX President and Chief Operating Officer Gwynne Shotwell said at an event in September that the company expects to deploy “supercompute in space” in 2027.

Alphabet and SpaceX therefore have overlapping ambitions even as their technology businesses compete in AI. Alphabet is also a significant investor in SpaceX, with its stake currently valued at more than $82 billion. That relationship gives Google an unusually close connection to the launch infrastructure required to test a technology that could eventually compete with conventional terrestrial data centers.

The economics are nevertheless far from established. A space-based computing network would have to overcome the cost of launching hardware, replacing failed satellites, maintaining communications links, and protecting processors from radiation. It would also need to demonstrate that the advantages of solar power and orbital real estate outweigh those costs.

For AI companies, the attraction is the scale of the infrastructure challenge. The rapid expansion of generative AI has created extraordinary demand for electricity and computing capacity, forcing companies to commit billions of dollars to new data centers and power infrastructure.

Moving some workloads into orbit could theoretically provide access to continuous solar energy while avoiding some of the land-use, permitting and grid constraints increasingly affecting data-center construction on Earth.

But that does not mean space eliminates the infrastructure problem. It only changes its nature.

Instead of transmission lines and local permitting, operators would have to manage launch capacity, orbital traffic, communications, thermal management, radiation protection and satellite replacement.

Against that backdrop, Thursday’s mission is seen as less a demonstration that orbital data centers are ready for commercial deployment than a test of whether one of the fundamental components, the AI processor, can operate effectively in space.

If Google’s TPUs perform reliably, the company will have taken an important first step toward validating the technical foundations of Project Suncatcher. Further progress would still require proving that large numbers of computing satellites can be launched, connected, cooled, and maintained at a cost competitive with terrestrial facilities.

The timing is notable because AI infrastructure is becoming one of the industry’s biggest constraints. Companies are racing to build larger clusters, while electricity shortages, permitting delays and community resistance increasingly complicate expansion.

Space offers an extreme solution to those problems, but it introduces an equally extreme set of engineering and economic challenges.

The Transporter-18 mission will also be a particularly busy day for SpaceX. The company is scheduled to conduct a separate launch from Florida’s Space Coast carrying astronauts to the International Space Station for NASA, beginning a six-month mission.