Crypto jumps on U.S. CPI data as Trump urges Powell to cut interest rates

ambcryptoОпубликовано 2026-01-13Обновлено 2026-01-13

Введение

The latest U.S. CPI data showed annual inflation steady at 2.7% in December, reinforcing expectations that the Federal Reserve may cut interest rates later in 2026. Core CPI rose 2.6% year-over-year, indicating persistent but stable underlying inflation. Shelter costs remained a key driver, rising 0.4% monthly. Following the report, the crypto market added roughly $27 billion, with Bitcoin climbing above $91,000. Former President Trump urged the Fed to cut rates, citing strong economic conditions. Stable inflation near the Fed’s target supports the case for eventual monetary easing, improving liquidity and benefiting risk assets like cryptocurrencies.

The cryptocurrency market added more than $26 billion in value on 13 January after the latest U.S. inflation data reinforced expectations that the Federal Reserve could begin cutting interest rates later this year.

The Bureau of Labor Statistics [BLS] reported on Tuesday that the Consumer Price Index [CPI] rose 0.3% in December. At the same time, annual inflation held steady at 2.7%, remaining close to the Federal Reserve’s long-term target.

The data showed that while inflation is no longer falling rapidly, price pressures have stabilised at levels that could allow policymakers to shift toward easing if economic growth slows.

Core CPI, which excludes food and energy, increased 0.2% month-over-month and 2.6% year-over-year. The move confirms that underlying inflation remains sticky but is no longer accelerating.

Shelter and services keep inflation elevated

The BLS said shelter costs rose 0.4% in December, remaining the single largest contributor to monthly inflation. Housing-related prices are still rising faster than most other categories, with shelter up 3.2% over the past year.

Services inflation also continued to outpace goods. The trend reflects ongoing wage and rent pressures in the U.S. economy, a key reason the Federal Reserve has been cautious about cutting rates too quickly.

Energy prices rise as gasoline falls in new CPI report

Energy prices were not the source of the latest inflation relief. The CPI report showed that the energy index rose 0.3% in December, as higher prices for electricity and energy services offset falling fuel costs.

Gasoline prices declined for the month, but that drop was insufficient to pull overall energy prices into deflation. This means inflation remains structurally supported by services and housing rather than being driven down by falling fuel prices.

Trump pushes Fed to cut rates post CPI report

The CPI release quickly sparked political reaction. President Donald Trump took to social media shortly after the data was published. He argued that the Federal Reserve should lower interest rates.

“Great (LOW!) Inflation numbers for the USA. That means that Jerome ‘Too Late’ Powell should cut interest rates, MEANINGFULLY!!!” Trump wrote, adding that economic growth remained strong alongside stable inflation.

While the Federal Reserve operates independently of political pressure, inflation running near 2.7% strengthens the case for eventual rate cuts if economic momentum cools.

Crypto market reacts to policy shift expectations

The crypto market responded positively to the inflation data. The total cryptocurrency market capitalization rose to around $3.12 trillion, up roughly $27 billion on the day, according to TradingView.

Bitcoin climbed back above $91,000, while Ethereum and major altcoins also advanced as investors increased exposure to risk assets.

Technically, the broader crypto market showed improving momentum following the CPI release. On the 12-hour chart, total market capitalisation pushed above short-term resistance, with MACD turning positive — a sign that upside momentum may be rebuilding.

Why CPI matters for Bitcoin

As institutional participation has grown through ETFs, derivatives, and macro-linked trading strategies, Bitcoin has become increasingly sensitive to U.S. inflation data.

Stable inflation near the Fed’s target allows:

  • Bond yields to ease
  • Liquidity conditions to loosen
  • Risk assets to attract capital

With the headline CPI holding at 2.7% and core inflation at 2.6%, markets are increasingly pricing in the possibility of a Federal Reserve pivot later in 2026. This backdrop has historically supported Bitcoin and other digital assets.

If inflation remains contained while growth slows, monetary policy may soon shift from restraint to stimulus, potentially providing a powerful tailwind for crypto markets.


Final Thoughts

  • U.S. inflation remained stable at 2.7%, increasing expectations that the Federal Reserve may begin cutting interest rates later in 2026.
  • Lower inflation reduces the need for tight monetary policy, improving liquidity conditions and making risk assets like Bitcoin more attractive.

Похожее

Sequoia Dialogue with Jensen Huang: Computing Model Undergoes a 60-Year Transformation; You Won't Be Replaced by AI, But You Will Be Dimensionality-Reduced by 'Those Who Master AI'

NVIDIA founder and CEO Jensen Huang, in a conversation with Sequoia Capital's Konstantine Buhler, argues that we are witnessing the most significant computing shift in 60 years—from retrieval-based to generative computing. Instead of just storing and retrieving data, future systems will generate highly personalized content (text, images, video) on demand, powered by massive "AI factories." Huang envisions a global "intelligence network" that will envelop the planet, following the historical patterns of energy and communication grids. He outlines a five-layer investment framework: 1) Energy, 2) Chips/Computers, 3) Infrastructure (data centers), 4) AI Models, and 5) Applications. He predicts this ecosystem will reach a scale of $20 trillion annually. Crucially, Huang pushes back against fears of AI-driven job loss. He distinguishes between specific "tasks" (e.g., typing, analyzing images) and overall "jobs" (e.g., CEO, radiologist). While AI automates tasks, it increases efficiency and demand for the higher-value problem-solving aspects of professions, thus creating more jobs and "up-leveling" careers. The real risk, he asserts, is not being replaced by AI, but being outperformed by someone who effectively leverages it. He urges everyone to embrace AI as a tool for augmented capability and innovation.

marsbit48 мин. назад

Sequoia Dialogue with Jensen Huang: Computing Model Undergoes a 60-Year Transformation; You Won't Be Replaced by AI, But You Will Be Dimensionality-Reduced by 'Those Who Master AI'

marsbit48 мин. назад

"I Don't Need a Better Model Anymore": A Panorama of AI Users Under a Reddit Hot Post

Titled "I Don't Need a Better Model Anymore": AI User Reactions on Reddit Anthropic recently released Claude Fable 5, its first publicly available 'Mythos'-tier model, achieving 80.3% on the SWE-Bench Pro benchmark and significantly outperforming its predecessor and competitors. However, a viral Reddit post titled "Claude Fable made me realize I don't need better models anymore" highlighted a growing user sentiment of "good enough." Top comments expressed "model fatigue," with users stating that earlier models like Opus 4.5/4.8 already sufficed for their workflows. High cost was a key concern, as Fable 5's API is nearly twice the price of Opus 4.8, with users questioning the return on investment and suggesting the field has hit a plateau. The most frequent complaint targeted Fable 5's stringent safety filters. Designed to intercept high-risk requests (e.g., cybersecurity), the system was perceived as overly conservative. Users reported frequent rejections for routine security-related tasks, leading to automatic fallbacks to the older Opus model. Paying users were particularly frustrated, feeling they paid a premium for a less usable product. Dissenting voices came from users with heavy, complex tasks. For workloads like high-energy physics simulations with thousands of code lines, Fable 5's improved long-context understanding and error detection represented a significant, worthwhile leap—described as moving from a "college player to an NBA starter." The debate underscores a divergence between benchmark performance and practical utility. For most users, current models meet their needs, making further advances relevant only for extreme use-cases. The discussion also raised concerns about a potential "Public AI Freeze," where the most powerful models (like the restricted Mythos 5) remain exclusive to enterprises and governments, while public offerings stagnate. The launch presents two report cards: one of technical excellence and another of user skepticism. Fable 5's ultimate reception may depend on Anthropic's ability to refine its safety filters and justify its cost for specialized, high-demand users.

marsbit55 мин. назад

"I Don't Need a Better Model Anymore": A Panorama of AI Users Under a Reddit Hot Post

marsbit55 мин. назад

When AI Traffic Surpasses Humans, How Do You Prove You're Human?

With AI-generated web traffic surpassing human activity, websites face a crisis as AI agents bypass ads, avoid clicks, and scrape data without generating revenue. This disrupts the ad-based internet economy, diverting traffic and reducing site visits. In response, sites are blocking AI crawlers and deploying traps like Cloudflare's "honeypot" pages. Traditional CAPTCHAs are now ineffective against advanced AI. The focus has shifted to behavioral biometrics—analyzing unique human patterns such as cursor movement, typing rhythm, and keystroke dynamics. Companies like IBM and BioCatch use this data to distinguish humans from bots, even detecting fraud through behavioral inconsistencies. Two competing approaches aim to verify human identity centrally. Sam Altman’s World (formerly Worldcoin) uses iris scanning to create unique credentials, though it faces privacy concerns and regulatory bans. Alternatively, cryptographic zero-knowledge proofs offer anonymous verification without revealing personal data, championed by Vitalik Buterin to avoid centralized surveillance. However, both systems have flaws. Centralized solutions risk biometric data misuse, while decentralized models may be exploited through identity rental markets in economically unequal regions. Despite challenges, the author favors cryptographic methods for preserving privacy over pervasive behavioral monitoring that permanently captures and controls personal biometric data.

marsbit1 ч. назад

When AI Traffic Surpasses Humans, How Do You Prove You're Human?

marsbit1 ч. назад

2026 Landscape of Decentralized AI: Why is Blockchain the Inevitable "Antidote" for AI?

**The 2026 Landscape of Decentralized AI: Why Blockchain is the "Cure" AI Cannot Ignore** Decentralized AI addresses fundamental bottlenecks of centralized AI: scarce and expensive computational resources, excessive control concentration, unverifiable model outputs, and increasing difficulty in acquiring training data due to privacy and regulation. Blockchain offers a path to make intelligence open, verifiable, and economically accessible. The technical stack comprises three layers: 1. **Applications & Services**: The main crypto use cases are "Agentic Finance" (converting natural language into on-chain actions) and "Agentic Payments" for machine-to-machine commerce. Projects like Giza, Infinity Labs, Coinvest AI, and x402 (handling 173M+ transactions) are key players. 2. **Middleware**: This coordination layer enables agents to discover, identify, and transact. Notable projects include Gokite AI (specialized L1), Virtuals (an OS for the agent economy), and especially Bittensor—a network of specialized subnets forming competitive AI micro-economies. 3. **Infrastructure**: The capital-intensive layer providing raw resources. It includes decentralized compute (Akash, Render, Aethir), verifiable inference (Venice AI, OpenGradient), distributed training (Prime Intellect, Templar AI), decentralized storage (Filecoin, Walrus), and privacy/verification layers (Nillion, Arcium, Phala Network) using technologies like ZKPs, MPC, and TEEs. The outlook for 2026-2027 indicates AI demand outpacing infrastructure, with AI agents as a primary growth engine. Computation is becoming an asset class, with on-chain markets as its financial layer. Tokenomics is emerging as a structural advantage for coordinating capital, compute, and data in decentralized AI networks. While still early—with adoption uneven and revenue often trailing token incentives—projects like Bittensor, NEAR, and Virtuals demonstrate a shift from speculative narrative to a new model for coordinating intelligence.

marsbit1 ч. назад

2026 Landscape of Decentralized AI: Why is Blockchain the Inevitable "Antidote" for AI?

marsbit1 ч. назад

a16z Crypto Partner: Cash Flow is the Moat

Cash Flow as the Moat: A Playbook for Crypto Founders Historically, the most enduring businesses have been built by positioning themselves within the "flow of funds"—facilitating the creation and transfer of value in a network and extracting a portion of it. Cryptocurrency is the first modern technology natively built for this purpose. For startups, failing to architect products and businesses to leverage these principles means missing a major opportunity. Blockchains are inherently network businesses. Each transaction settles on a shared ledger, and every new participant strengthens the underlying network for all. Well-designed network tokens amplify this by aligning users, developers, and validators around growing the network, with value flowing back to contributors in a transparent feedback loop. This model is not new; companies from railroads and Standard Oil to Google, Meta, and AWS have thrived by inserting themselves into critical flows of value (goods, attention, compute). Financial markets make it even clearer: firms like Visa and major market makers generate immense revenue not by predicting markets but by being in the path of transactions. The combination of fund flow and network effects creates one of the most durable business structures. The high margins in traditional finance (payments, custody, lending, FX) represent prime targets. Crypto founders have the opportunity to build the next version—programmable, instant, global, and natively in the flow of funds. The frontier extends beyond finance to areas like computing/GPUs, AI training data, energy, robotics, and space—markets without entrenched intermediaries, ripe for building new, efficient value rails on programmable infrastructure. Founders should ask: Are you in the flow of funds today? Does your revenue scale 10x with the value of activity on your platform? Where in your target market are profit margins highest relative to value created? The opportunity is clear: embed your startup into the new flows of value and let the network effects accumulate.

marsbit1 ч. назад

a16z Crypto Partner: Cash Flow is the Moat

marsbit1 ч. назад

Торговля

Спот
Фьючерсы
活动图片