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Home Blog Page 28

Copper Hits ATH As Gold and Silver Rally On Safe Haven Narrative

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Copper has reached a new all-time high, surpassing $12,000 per metric ton on the London Metal Exchange (LME) for the first time ever. Prices hit a peak of around $12,159.50 per ton on December 23, driven by: Tight global supply from mine outages in Chile, Peru, and Indonesia.

Pre-emptive stockpiling in the US ahead of potential tariffs. Strong long-term demand from EVs, AI data centers, and renewable energy infrastructure. This marks the highest level on record, with copper up nearly 40% year-to-date — its biggest annual gain since 2009.

In US terms, COMEX copper futures are trading around $5.50–$5.56 per pound, also near record levels. Gold has crossed $4,500 per ounce, smashing through this milestone with spot prices reaching just below or above $4,500 reports vary slightly between ~$4,489 and $4,500+ in recent sessions.

It set fresh records multiple times this week, fueled by: Safe-haven buying amid escalating geopolitical tensions like the US-Venezuela issues. Expectations of further Fed rate cuts, Robust central bank purchases and a weakening US dollar.

Gold is up about 70% in 2025, on track for its strongest yearly performance since 1979. Both metals are rallying in tandem this holiday week, reflecting a mix of industrial demand, supply constraints, policy uncertainty, and flight-to-safety flows.

Electric vehicles (EVs) require significantly more copper than traditional internal combustion engine (ICE) vehicles due to their reliance on electricity for propulsion, power management, and energy storage.

Copper’s excellent electrical conductivity, thermal properties, durability, and malleability make it irreplaceable in key components—substitutes like aluminum are less efficient and often require larger volumes.  A typical ICE vehicle uses 20–25 kg (44–55 lbs) of copper, mostly in wiring, radiators, and basic electrical systems.

This difference arises because EVs replace mechanical systems with electrical ones, demanding extensive copper for efficient power delivery. Windings in the stator and rotor use copper wire—up to a mile (1.6 km) of copper wiring in some motors.

Permanent magnet or induction motors rely heavily on copper for efficiency and torque. Battery Pack: Copper foil as current collectors (anode side). Busbars, connectors, and interconnects for high-current flow between cells. Extensive high-voltage cabling, inverters, converters, and onboard chargers.

EVs have far more electrical components like sensors, infotainment, regenerative braking than ICE cars. Thermal management— like cooling systems, brakes, and auxiliary systems are inherent. EV adoption also boosts copper use in: charging stations: Cables, connectors, and internal wiring, fast chargers use more.

Grid upgrades: Transformers, cables, and substations to handle increased load. Projections show charging infrastructure alone could demand hundreds of thousands of tonnes annually as stations proliferate.

EVs are a major driver of copper’s bullish outlook amid the energy transition. Global EV-related copper demand was minimal a decade ago but has surged. EV sector demand could exceed 2.5–2.8 million tonnes by 2030 from ~0.5–1 Mt today, even as per-vehicle usage slightly declines due to efficiency gains such as lighter wiring, better designs.

This represents 8–10% of total global copper demand by 2030, up from <2% now. Combined with renewables (solar/wind) and data centers/AI, clean energy could drive copper demand growth of 50–100% by mid-century.

The rapid rise in EV sales—despite recent slowdowns in some markets—ensures strong structural demand, contributing to tight supply and record prices. Copper truly powers the shift to electrified transport.

Silver has also hit records above $70/oz in sympathy. It’s been an epic year for commodities — merry Christmas to the bulls.

The Merchant Identity Problem: How to Prove Legitimacy Online

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Online businesses struggle to build merchant identity. Consumers seem to be wary of merchants without a physical presence.

Despite the challenge, you can still run a successful online business. If you have been struggling to expand your client pool, this guide dives deep into the reasons you are struggling and how to solve your problems with checkout solutions and a reliable payment service provider.

Why Trust Is Fragile in Online Commerce

When customers can’t see the business in person, establishing long-term trust can be a challenge.

Lack of credibility

It is difficult to build online business credibility because users don’t know the real face behind the brand. Anonymity casts doubt about the authenticity of the products.

Imposter problem

Due to the lack of physical presence, a lot of online shops have to deal with impostors scamming customers and damaging their reputation.

Local rules

Some online shops do not disclose their operating country. The rules they follow may be different from your usual standards.

What Makes Legitimacy Hard to Prove

A website with a brand name is hardly legitimate. People are reluctant to believe in small online merchants for many reasons.

Unclear ownership

Online shop ownership is incredibly opaque. Most owners do not disclose their personal information, making the online shop very impersonal and questionable without a real face to answer for.

Lack of financial reports

Small-scale online merchants are not required to disclose financial information. The lack of transparency can cause customers to distrust the brand’s ethics and quality.

New businesses

New businesses without existing customers or reviews can find it substantially hard to prove their legitimacy. People have no way of understanding their history or financial background.

Trust Signals That Actually Matter to Customers

Verifying merchant identity online is complicated, especially if the merchant isn’t in the same country. Therefore, international merchants should offer extra comfort with these tips.

Transparent pricing

A clear price list is the first step to gaining consumer trust. People are more willing to engage with online merchants with transparent pricing than a shop with lots of hidden fees.

Consistent work

From delivery timeframe to customer service to product quality, consistency is key. Customers will only return if they have positive experience with the merchant before.

Clear policies

Terms and conditions, such as returns, refunds, personal data, or complaints policies, should be clearly listed. It can avoid disappointments and confusion for consumers, bringing up satisfaction rates.

Technical Proof of Legitimacy: Beyond the Surface Layer

Simply having a lovely UX is not enough. Customers need to know they are sending money to a real seller and that they are protected.

Licensing

Online merchants are still subject to local regulations. Check the government requirements for your industry to get the licenses needed for operations.

Data protection

A reputable online merchant must follow local regulations to ensure sensitive information is encrypted and protected. Customer information should never be sold or leaked to third parties for profit.

Business accounts

Setting up a business account adds authority to your brand. Instead of using your personal account, a professional business account with centralized financial reports shows better credibility for partners and banks.

The Role of Tiers, Badges, and Third-Party Verification Programs

When you are starting out, consider getting verified in several places to gain online merchant legitimacy.

Marketplace

Online marketplaces like Amazon, Etsy, and eBay are great places for sellers to begin. Buyers feel protected by the platform. Therefore, they are more willing to trust and try out unfamiliar brands.

Official certificates

For many niches, there are government-approved licenses to demonstrate authenticity. With a license, clients can rely on you to deliver quality products and services.

Industry verifications

Platforms like Trustpilot allow real users to review and make comments about the merchant. New customers may treat these reviews as the benchmark to whether the brand is trustworthy.

How Merchants Can Proactively Reduce Customer Doubt

These are a few simple steps you can take to gain customer trust.

Centralize financial management

Instead of using multiple accounts for payments and refunds, centralizing your financial needs can build greater trust and make transactions easier. Pick a payment service provider like PayDo to sort out your needs.

Prompt customer support

Having a 24/7 customer support team can significantly boost conversion rates. New and existing customers feel supported when they are interacting with a human.

Consistent performance

A business that always misses deadlines and has payment issues will drive suppliers and customers away. Formulate some backup plans so you can meet your targets anytime.

In conclusion

Online merchant legitimacy can be difficult to prove, but it is not impossible.

There are many ways merchants can reduce customer doubt and build a reputable brand online. Work with an established provider to deliver the smoothest shopping experience for your clients.

MiniMax’s M2.1: Frontier-Level Open-Source Model Excels in Multi-Language Coding, Mobile Dev, Agentic Workflows

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MiniMax, the fast-rising Chinese AI startup often dubbed one of the “AI Tigers,” has launched MiniMax M2.1, a significant upgrade to its sparse Mixture-of-Experts (MoE) model series.

The release, announced December 22, emphasizes real-world complex tasks, positioning M2.1 as a state-of-the-art open-source contender for coding, agent scaffolding, and enterprise automation—delivering performance that rivals or exceeds closed-source leaders like Claude Sonnet 4.5 and Gemini 3 Pro in key areas.

Founded in December 2021 by alumni from computer vision giant SenseTime (including CEO Yan Junjie), MiniMax has grown explosively, raising over $850 million across rounds, with a $600 million infusion in March 2024 led by Alibaba, pushing its valuation to $2.5-3 billion. Additional backers include Tencent, HongShan (formerly Sequoia China), and MiHoYo.

The company, which confidentially filed for a Hong Kong IPO targeting up to $700 million at an over $4 billion valuation, boasts 27.6 million monthly active users (as of September 2025) across consumer apps like Hailuo AI (text-to-video), Talkie (AI companions), and its Open Platform API. M2.1 builds on the October-launched M2—a 230B total / 10B active parameter MoE that topped open-source rankings on Artificial Analysis composites—by prioritizing usability in multilingual programming, native mobile development, office scenarios, and agent generalization.

Retaining the efficient architecture for low-latency inference (~100+ tokens/second on optimized setups), M2.1 offers API pricing at roughly 8-10% of Claude Sonnet while claiming 2x speed. Benchmark Highlights (independent and MiniMax-reported):Multi-SWE-Bench: 49.4% — industry-leading for multilingual tasks.

  • SWE-Bench Multilingual: 72.5% — outperforming Claude Sonnet 4.5.
  • SWE-Bench Verified: Up to 74.0% in agent frameworks (edging DeepSeek V3.2’s 73.1%).
  • VIBE (Visual & Interactive Benchmark for Execution): Aggregate 88.6% (new open-sourced benchmark using Agent-as-Verifier); standout 91.5% on VIBE-Web and 89.7% on VIBE-Android, surpassing Claude Opus/Sonnet in full-stack app generation with aesthetic and functional excellence.

Other gains include refined interleaved thinking for composite instructions, concise Chain-of-Thought outputs reducing token usage, and stable integration with tools like Claude Code, Droid, Cline, Kilo Code, Roo Code, BlackBox, plus context mechanisms (Skill.md, agent.md, Slash Commands). Beyond coding, M2.1 elevates general dialogue, technical writing, and non-technical responses with more structured, detailed outputs.

The model is immediately accessible via MiniMax’s API (text generation endpoint), integrated platforms (Kilo Code, Vercel AI Gateway, Ollama), and open weights on Hugging Face (MiniMaxAI/MiniMax-M2.1).

Recommended inference: vLLM/SGLang with temperature=1.0, top_p=0.95.

Community response has been electric: On X and Reddit’s r/LocalLLaMA, developers hailed M2.1 as a “beast at UI/UX design” with “clean” app prototypes in a few interactions, faster tool calling, and superior “vibe coding.”

Early tests show strong long-horizon reasoning and reduced bugs versus M2. Comparisons position it ahead of DeepSeek V3.2 and GLM 4.7 in aesthetics/mobile, while closing gaps with proprietary frontiers. MiniMax frames M2.1 as the “brain” for the agentic era, powering its MiniMax Agent platform for end-to-end tasks (administration, data science, finance, HR, software dev).

M2.1 accelerates democratization—offering elite coding/agent capabilities at an accessible scale as open-source Chinese labs (MiniMax, DeepSeek, Zhipu) dominate 2025 releases, challenging global incumbents and fueling AI-native workflows worldwide.

Gold Hits Record $4,525 While Bitcoin Lags – Peter Schiff Calls End of BTC Bull Run

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Gold has surged to a historic high of $4,525, reaffirming its status as a safe-haven asset at a time of mounting global uncertainty, while Bitcoin continues to struggle to regain bullish momentum.

The divergence between the two assets has reignited the long-running debate over Bitcoin’s role as “digital gold,” with longtime crypto critic Peter Schiff seizing the moment to declare that the Bitcoin bull run is over.

As investors reassess risk amid tightening financial conditions and volatile markets, Schiff argues that capital is flowing back to traditional stores of value leaving Bitcoin lagging behind in gold’s shadow.

He argues that Bitcoin’s failure to rise alongside surging tech stocks (S&P 500 up 0.5% to a record) and gold (hitting $4,525 per ounce) indicates the end of its bull run, forecasting a crash as all buyers are exhausted.

In a post on X, he wrote,

“If Bitcoin won’t go up when tech stocks rise, and it won’t go up when gold and silver rise, when will it go up? The answer is: it won’t. The Bitcoin trade is over. The suckers are all in. If Bitcoin won’t go up, it can only go down. If HODLers are lucky it won’t be a slow death.”

The post reflects Schiff’s consistent bearishness on Bitcoin since 2010, with recent December 2025 tweets predicting its collapse before a dollar crisis, despite BTC trading near $87,000 after peaking at $93,000 earlier in the month.

Schiff argues that Bitcoin remains tied to risk assets like stocks, rallying less during upswings and falling harder in downturns, dismissing it as “digital gold” since it won’t track gold’s rises.

Meanwhile, Binance CEO Changpeng Zhao “CZ”, in a response under the post, mocked Schiff’s prediction that Bitcoin’s bull run is over, urging followers to “save the tweet” as a future reminder of his repeated forecasting errors on BTC’s demise.

It is understood that Schiff has issued similar Bitcoin bearish calls for over a decade, including a 2019 claim that BTC would “never” reach $100,000, which it surpassed in 2021 and a 2018 warning that even $750 per BTC would remain “expensive.”

In line with Schiff’s prediction of the end of Bitcoin bull run, Fidelity’s global macro director, Jurien Timmer, has called the end of the latest bitcoin bull run, while highlighting gold’s continued bull market strength.

The October all-time high near $125,000, reached after roughly 145 months of cumulative rallying, fits well within the framework. Bitcoin bear markets, often referred to as winters, typically last about a year, Timmer says. As a result, he sees 2026 as a potential “year off” for bitcoin following the conclusion of the latest halving driven cycle.

“While I remain a secular bull on bitcoin, my concern is that bitcoin may well have ended another four year cycle halving phase, both in price and time,” Timmer wrote on X.

Timmer also highlights gold’s strong performance in 2025, contrasting it with bitcoin’s negative year, and does not expect a near term mean reversion between the two assets.

Gold is firmly in a bull market, up roughly 65% year to date, outperforming global money supply growth, Timmer noted. He adds that during the recent correction, gold has held onto most of its gains, which he views as characteristic behavior of a bull market.

Notably, in a counter statement, Jamie Coutts, Chief Crypto Analyst at Realvision, believes the Bitcoin bull market isn’t over yet despite substantial falls. Coutts told the Tapping Into Crypto podcast that the weakness in crypto is due to macro conditions creating a risk-off environment but he believes Trump is likely to “goose” the US economy before next year’s midterm election creating better conditions for crypto.

Coutts also said crypto is now at a “major inflection point” where institutional adoption will see the importance of the four-year cycle decline.

The flagship crypto aseet price slipped today below $87,000, falling nearly 1%, as multiple pressures hit the market at the same time. After weeks of moving sideways between $85,000 and $90,000, Bitcoin is struggling to find strong support, leaving traders cautious. BTC is currently trading at $87,183 at the time of writing this report.

Outlook

The contrasting performances of gold and Bitcoin in 2025 underscore a broader market shift. Gold’s record highs suggest continued investor preference for stability amid global uncertainty, while Bitcoin faces headwinds from macroeconomic factors and profit-taking pressures.

Analysts remain divided as some foresee a near-term consolidation or bear phase for Bitcoin, while others anticipate that institutional adoption and policy-driven economic growth could reignite bullish momentum.

OpenAI Admits Prompt Injection Risks in Atlas Browser Are Here to Stay, Unveils AI-Powered “Attacker” Defense

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OpenAI has openly acknowledged that prompt injection attacks—a sophisticated vulnerability where malicious instructions are concealed in web content, emails, or documents to manipulate AI agents—pose an intractable, long-term security threat to its ChatGPT Atlas browser, with no prospect of complete elimination.

In a comprehensive blog post published Monday titled “Continuously hardening ChatGPT Atlas against prompt injection attacks,” the company likened the issue to “ever-evolving online scams that target humans,” stating unequivocally: “Prompt injection, much like scams and social engineering on the web, is unlikely to ever be fully ‘solved.’”

The admission underscores fundamental challenges in securing “agentic” AI systems that autonomously interact with the open web. Launched on October 21, 2025, for macOS (with Windows, iOS, and Android versions forthcoming), Atlas integrates ChatGPT directly into browsing via a persistent sidebar for contextual queries, summarization, and analysis. Its standout “agent mode”—available in preview for Plus, Pro, Business, and select Enterprise/Edu users—allows the AI to perform multi-step tasks, such as navigating sites, clicking links, filling forms, managing emails, or automating workflows like meal planning and grocery ordering.

However, this autonomy dramatically “expands the security threat surface,” OpenAI noted.

Indirect prompt injections exploit the agent’s need to process untrusted content: attackers embed hidden commands (e.g., in invisible text on webpages or crafted emails) that override user intent, potentially leading to data exfiltration, unauthorized actions, or privacy breaches. Vulnerabilities surfaced immediately post-launch. Security researchers demonstrated exploits, including one where hidden text in a Google Doc altered browser behavior, and another via the Omnibox (combined address/search bar), treating malicious URLs as trusted prompts. Brave’s contemporaneous analysis deemed indirect prompt injection a “systematic challenge” for all AI browsers, citing Perplexity’s Comet as similarly affected.

Additional reports highlighted issues like “ChatGPT Tainted Memories” (a CSRF flaw that injects persistent instructions) and low phishing detection rates (Atlas blocking only ~5.8% of malicious sites versus Chrome’s 47%). Aligning with broader concerns, the U.K.’s National Cyber Security Centre (NCSC) warned earlier in December that prompt injections “may never be totally mitigated,” advising focus on risk reduction rather than eradication—echoing OpenAI’s stance. To counter this “Sisyphean” challenge, OpenAI detailed a proactive defense framework:

  • LLM-based Automated Attacker: A reinforcement learning-trained bot simulates advanced hackers, iteratively crafting multi-step (tens to hundreds) attack chains in simulated environments. Leveraging access to the target’s internal reasoning traces—unavailable to external attackers—it uncovers novel exploits missed by human red teams.
  • Rapid Response Loop: Discoveries feed into adversarial training for updated models, system-level safeguards, and monitoring enhancements. A recent update, triggered by automated red teaming, rolled out an adversarially trained checkpoint to all users.
  • A demo illustrated the attacker’s prowess: It seeded a user’s inbox with a malicious email containing injected instructions. When the agent scanned for an out-of-office reply, it instead drafted a resignation to the CEO. Post-update, Atlas detected and flagged the attempt.

OpenAI has collaborated with third-party experts pre-launch and emphasizes user mitigations: mandatory confirmations for sensitive actions (e.g., emails, payments), “logged-out” mode to avoid credential exposure, narrow task instructions, and optional features like Browser Memories (opt-in, deletable, no training use for paid users).

Industry parallels abound. Anthropic employs similar red-teaming for Claude, while Google prioritizes architectural controls in agentic tools. Yet, experts remain cautious. Rami McCarthy, principal security researcher at Wiz, framed risk as “autonomy multiplied by access,” noting agentic browsers occupy a “challenging” high-access space.

“For most everyday use cases, agentic browsers don’t yet deliver enough value to justify their current risk profile,” McCarthy told TechCrunch, citing exposure to emails and payments.

As agentic AI proliferates, spanning OpenAI’s Atlas, Perplexity Comet, and emerging tools from Google/Anthropic, the prompt injection conundrum highlights systemic hurdles in trusting autonomous agents on the unfiltered internet.