US Softening Tariff Stance, Will it Work for the Crypto Market?

TheNewsCryptoОпубліковано о 2026-02-20Востаннє оновлено о 2026-02-20

Анотація

The US has reduced tariffs on Indonesia from 32% to 19%, including exemptions for products like palm oil and rubber, signaling a potential softening of its tariff stance. Similar reductions have been made for other countries, including India. This policy shift may alleviate financial pressure on lower-income consumers affected by inflation, potentially allowing them to allocate more funds to the crypto market. The overall crypto market cap has increased by 1.48% to $2.33 trillion, though the article emphasizes this is not investment advice.

The US has lowered its tariffs on Indonesia. This is in line with other countries, which now have a lower rate on their exports to the US. Thereby signaling a possibility that the Trump Administration might be softening its stance when it comes to imposing high tariffs. For the crypto market, this brings up a scenario where the space sees comparatively higher allocations.

US Tariff on Indonesia

Indonesia and the US have reached a deal to bring down the tariff on the former from 32% to 19%. A lot of items have been exempt, giving them an entry with 0% rate. This includes products like palm oil, rubber, and cocoa, among others. Indonesia’s senior Economic Minister Airlangga Hartarto has called the deal a win-win, adding that it respects the sovereignty of both nations.

A fact sheet by the White House has called this a breakthrough for the country’s different sectors, namely agriculture, manufacturing, and digital. Indonesia, in response, has agreed to remove barriers on more than 99% of American exports, per the fact sheet.

Other Similar US Tariff Instances

This is not a standalone case where the US has reduced or eliminated the tariff rate for a country. India is the most recent nation which secured a deal to bring down the rate to 18% from almost 50%. All the details are likely to be published after signing the official document; however, such developments go on to show that America may be softening its stand on tariff.

The said tariff rate on Indonesia puts it together with other countries, like Cambodia, Malaysia, the Philippines, and Thailand. Vietnam is also on the list, but with a slightly higher rate of 20%. Needless to say, a lowered tariff rate is estimated to work well for crypto enthusiasts.

What’s for the Crypto Market?

A recent report underlined that lower-income consumers were struggling due to high inflation triggered by the tariff policy. A reduced rate could offer some sigh of relief, enabling them to allocate a portion of their portfolios to the crypto market. The sentiment could eventually be replicated by bigger investors upon noticing a bullish movement.

For now, the crypto market is up by 1.48% in terms of the market cap, which is $2.33 trillion. It is important to note that the content of this article is neither advice nor a recommendation. Do thorough research and risk assessment before crypto investments.

Highlighted Crypto News Today:

Capital Rotates From DeFi to Tokenized Real-World Assets Amid Crypto Market Pullback

TagsCrypto MarketTARIFF

Пов'язані питання

QWhat is the new tariff rate the US has agreed upon with Indonesia, and what was the previous rate?

AThe US has lowered the tariff rate on Indonesia from 32% to 19%.

QAccording to the article, how could a reduced tariff rate potentially benefit the crypto market?

AA reduced tariff rate could offer relief to lower-income consumers struggling with high prices, potentially enabling them to allocate a portion of their portfolios to the crypto market. This sentiment could be replicated by larger investors if they notice a bullish movement.

QBesides Indonesia, which other countries are mentioned as having similar reduced US tariff rates?

AOther countries with similar reduced US tariff rates include Cambodia, Malaysia, the Philippines, Thailand, and Vietnam (with a slightly higher rate of 20%).

QWhat did Indonesia agree to do in response to the US lowering its tariffs?

AIn response, Indonesia agreed to remove barriers on more than 99% of American exports.

QWhat was the overall performance of the crypto market at the time the article was written, as measured by its market cap?

AAt the time of writing, the crypto market was up by 1.48%, with a total market capitalization of $2.33 trillion.

Пов'язані матеріали

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

Ethereum Q1 2026 Report: Fees Down, Users & Transactions Hit New Highs Token Terminal's Q1 2026 report on Ethereum presents a pivotal development: the network achieved record highs in monthly active users (13.2M, +85.9% YoY), total transactions (200.4M, +81.5% YoY), and throughput (25.78 TPS), while transaction fees on the mainnet plummeted by 47.9% quarter-over-quarter. This shift is attributed to the network's strategic move into a "low fees for scale" phase, exemplified by the Fusaka upgrade which increased data capacity and lowered block space costs, releasing pent-up demand (a manifestation of Jevons's Paradox). The report highlights a core narrative shift for Ethereum: from a DeFi-centric blockchain to a global financial settlement layer. It maintains a dominant position in tokenized assets, holding majority market shares among top chains in stablecoins (61.8%), tokenized funds (73.0%), and tokenized commodities (84.0%). Growth in tokenized funds (+73.1% YoY) and commodities (+325.9% YoY) was particularly strong, driven by institutions like BlackRock and JPMorgan entering the space. Contrasting these usage gains, several USD-denominated value metrics declined in Q1: fully diluted market cap fell 30.3% QoQ, total value locked (TVL) dropped 11.0%, and ecosystem transaction volume decreased 24.0%. The report interprets this as Ethereum prioritizing long-term network expansion and cementing its role as the default settlement layer for finance over short-term fee capture. The commentary from Etherealize argues that, much like the early internet, Ethereum's open, permissionless model is poised to win over closed alternatives as institutional tokenization accelerates.

marsbit1 год тому

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

marsbit1 год тому

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

Pete Florence, a former senior research scientist at Google DeepMind and a key contributor to the Vision-Language-Action (VLA) model architecture, is deliberately distancing his startup, Generalist AI, from the trendy "world model" label. He argues that the industry should prioritize concrete goals over buzzwords. His goal is to create robots that can perform a vast range of unseen tasks with high speed and success rates, without needing task-specific training data. Recently, his company raised $400 million (¥2.7 billion) at a $2 billion valuation. Notable investors include NVIDIA's NVentures, Bezos Expeditions, NFDG, as well as Xiaomi co-founder Lin Bin, Zoom founder Eric Yuan, and renowned AI scientist Fei-Fei Li. Florence's approach stems from his academic background at MIT under Professor Russ Tedrake, focusing on understanding the physical world. After joining DeepMind, he developed models like Transporter Network and co-created the VLA framework. He left in 2025 to found Generalist AI. The company has launched two models: GEN-0, which demonstrated that scaling laws apply to physical motion, and GEN-1. GEN-1 was trained on over 500,000 hours of physical interaction data collected via a specialized wearable device. It achieves a 99% success rate on precise mechanical tasks like folding boxes and maintains performance three times faster than its predecessor. Florence believes GEN-1 is reaching a commercial utility threshold similar to the GPT-3 inflection point. The substantial funding round, following GEN-1's release, signifies strong investor confidence in Generalist AI's practical, goal-driven path to creating versatile, useful robots, regardless of the "world model" terminology.

marsbit1 год тому

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

marsbit1 год тому

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

In three days, Google lost two AI legends. On June 18, Noam Shazeer, co-author of the seminal "Attention is All You Need" paper and Gemini co-lead, left for OpenAI. Just 48 hours later, John Jumper, 2024 Nobel laureate and AlphaFold lead, departed DeepMind for Anthropic. This follows Andrej Karpathy joining Anthropic in May. These moves highlight a structural trend: top AI talent is concentrating at mission-driven, pre-IPO firms like OpenAI and Anthropic, while Google becomes a primary source. The exodus stems from a core mission mismatch. Google's ad-centric model often subordinates AI research to product and revenue goals, creating friction for pioneers like Shazeer, who returned in 2024 only to leave again. In contrast, OpenAI and Anthropic offer singular focus on pushing AI boundaries, whether towards AGI or safety-aligned models, which deeply appeals to top researchers like Jumper. Financial incentives amplify the pull. With both OpenAI and Anthropic nearing IPO, employees stand to gain immensely from equity, an upside Google's mature stock cannot match. Furthermore, the 2023 merger of Google Brain and DeepMind, intended to consolidate strength, has instead created cultural tension and slowed the path from research to product, as evidenced by Gemini's pace. This talent redistribution is reshaping the AI landscape. While Google retains vast data and compute resources, its true crisis is the quiet, continuous loss of the people who define the field's future. The real moat in AI is not infrastructure, but the concentration of brilliant minds—a battle Google is currently losing.

marsbit3 год тому

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

marsbit3 год тому

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

Beyond the familiar performance charts like MMLU-Pro and MMMU, which major AI models strive to ace, stands a key "examiner": Chinese-Canadian researcher Wenhu Chen. An assistant professor at the University of Waterloo and founder of TIGERLab, Chen addresses the crucial need for more rigorous AI evaluation. As models like GPT-4 began scoring near-perfect results on older benchmarks like MMLU, it became difficult to distinguish their true capabilities. In response, Chen introduced MMLU-Pro in 2024, featuring harder, more reasoning-focused questions with more answer choices, successfully reintroducing meaningful performance gaps. His work extends to multi-modal evaluation with MMMU and its enhanced version, MMMU-Pro. These benchmarks test a model's ability to understand and reason with complex information from images, charts, and text across diverse academic subjects, exposing the significant challenges even top models face in genuine comprehension. Chen's background in complex QA, table reasoning, and his experience at Google DeepMind on projects like Gemini inform his approach. He understands that effective benchmarks must anticipate how models might "cheat" by memorizing data or avoiding visual analysis. His lab also actively researches video understanding and generation models (e.g., UniVideo, Vamba), ensuring his evaluation work is grounded in practical model-building challenges. Now at Meta's Super Intelligence Lab, Chen continues his focus on multi-modal data and evaluation, representing the deep yet often unseen contributions of Chinese talent in shaping the fundamental tools of the AI industry.

marsbit3 год тому

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

marsbit3 год тому

Торгівля

Спот
Ф'ючерси
活动图片