@Mr 10/10 @Mr_Simplifier

This is exactly what people miss. Traditional finance relies heavily on centralized, legacy rails that are objectively a softer target than decentralized networks. But you hit the nail on the head regarding the real vector: math vs. psychology. Breaking Bitcoin’s SHA-256 requires compute power that doesn't exist yet, but running automated, hyper-personalized phishing scripts using LLMs and leaked data takes almost zero effort. The biggest risk of AI isn't that it becomes a master hacker; it's that it becomes a master manipulator. The cryptography remains undefeated, but our collective opsec is about to get tested like never before.

CZ 🔶 BNB @cz_binance

a day ago

Everyone worried about AI hacking crypto, but the internet and banking systems rely on weaker encryption. That said, AI doesn’t need to break Bitcoin’s cryptography to cause damage, leaked data already enables more phishing, social engineering, etc, Stay SAFU!

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Good conversation creates good memories ,good friends brings good vibes and good times brings lasting happiness and joy Tune in the conversation to get a hand of good loyal active international friends x.com/i/spaces/1mxPa…

After almost a year I visited my village today and so much had changed. Some roads were new and some places looked different but a few familiar spots brought back so many old memories Some places are more than just places. They hold our childhood memories our happiest moments and a part of our lives that we can never get back. Time passes people change and life moves on but the memories always stay in our hearts Being back in my village today made me miss those old days even more Sometimes all it takes is a visit to an old place to bring back a thousand memories. No matter how much things change our roots will always feel like home .

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Don't let fear stop you from chasing your dreams. Be brave, take the first step, and grow stronger with every challenge. x.com/i/spaces/1mxPa…

We’re leaving the office and heading to work

A millionfold in 10 years is mind-blowing. 🤯 The tandem of hardware and software design is clearly paying off. Can't wait to see what the Vera Rubin platform brings next for physical AI and inference! 🚀

NVIDIA @nvidia

3 days ago

With NVIDIA extreme co-design, we’ve accelerated AI performance a millionfold over 10 years, and we’re not stopping there.

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I’m really curious, @elonmusk. You must be the highest-paid on X monetization program. Congratulations on hitting 241.5 million followers.

Tenstorrent's $1.5 billion raise signals demand for alternatives to Nvidia. Tenstorrent reportedly secured $1.5 billion at a $6.2 billion valuation, strengthening its position as a challenger in AI computing. The attraction of alternative chip designs is straightforward: AI developers want more choices over cost, performance and the hardware their software depends on. An industry concentrated around a few suppliers can become expensive and difficult to scale when demand rises rapidly. Tenstorrent's approach, including its use of the RISC-V architecture, offers a different path from relying entirely on proprietary platforms. But raising capital is only the first hurdle. Semiconductor companies must also build a strong software ecosystem, secure manufacturing capacity and persuade customers to deploy their products in real workloads. The investment shows that the market sees room for competition. Whether that opportunity turns into meaningful market share will depend on execution.

AI is lowering the cost of attacks, and defenders cannot afford to stay manual. A cybersecurity investigation reported that an attacker used autonomous AI agents to compromise more than 100 websites. The case highlights how automation can allow attacks to be attempted at greater scale without a proportionate increase in human effort. This changes the economics of cybersecurity. Defenders have traditionally relied on teams of specialists to investigate suspicious activity, test vulnerabilities and respond to incidents. Attackers can now use automation to speed up some of those tasks. The same technology can help security teams scan systems, identify weaknesses and respond faster, so the outcome is not predetermined. But organisations that depend on slow, manual processes may struggle to keep pace with automated threats. Cybersecurity is becoming a contest between systems that can detect and act quickly. The organisations that combine automation with careful human oversight will be better positioned to manage that risk.

1 red ball 🏀 =2.5 kg

Anthropic: $965B valuation $65B revenue Walmart: $870B valuation $713B revenue Anthropic is worth more than Walmart with 11x less revenue. Are AI valuations completely broken?

Andrew Lokenauth @FluentInFinance

a month ago

Anthropic valuation: $965B Walmart valuation: $870B Anthropic revenue: $65B Walmart revenue: $713B Totally normal, right?

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Devin’s maker Cognition just crossed $1B in annualized revenue. Less than 2 years after launch. AI builders: Could your startup be the next Devin?

A new humanoid robot just started shipping. But the interesting part isn’t the robot. Feather wants humanoids to be a platform: - Open SDK - Swappable hardware - Your choice of AI models Basically build your own startup on top of a robot… Is robotics the next big AI wave?

The appearance of things changes according to the emotions; and thus we see magic and beauty in them, while the magic and beauty are really in ourselves. @WafaZahra786 @Arya07__ @Rohee211 @Boss_onX @MURshoo584 x.com/i/spaces/1jGXg…

Which of these do you think is most harmful to your health 👇

The AI boom may be changing the inflation equation. The Federal Reserve has a problem that conventional interest-rate policy was not designed to solve neatly: some of the biggest investors driving demand are relatively insensitive to borrowing costs. Technology giants can continue funding AI infrastructure from enormous cash reserves, while a small business may postpone expansion because its bank loan has become more expensive. Households can face higher mortgage and credit-card costs without sharing equally in the benefits of AI investment. Normally, higher rates cool demand across the economy. But when investment is concentrated in powerful, well-funded companies, the adjustment can become uneven. AI may eventually improve productivity and reduce some costs. The complication is timing: the spending pressure arrives before all the productivity gains are realised.

China's 4.5% growth tells only half the story. China’s economy grew 4.5% in Q3, beating expectations. On the surface, that looks like a recovery gaining momentum. But the composition of growth matters more than the headline. Industrial production is holding up, exports are helping, and retail sales have improved. Meanwhile, property investment continues to deteriorate and households remain cautious about spending. Compare that with an economy growing because domestic consumers and private businesses are confidently investing. The two situations can produce similar GDP numbers while having very different levels of resilience. China is growing, but the question is whether domestic demand can eventually carry more of the load. Strong output does not automatically mean households feel wealthier or more secure.

AI spending is becoming an inflation problem for the Federal Reserve. The AI boom is creating an unusual problem for the Fed. Companies are investing heavily in computing infrastructure, chips and data centres even as borrowing costs rise. Higher interest rates may do little to slow cash-rich technology giants, but they can make loans, mortgages and credit-card debt more expensive for everyone else. This creates an uneven economic adjustment: the companies driving investment may keep spending while smaller businesses and households absorb much of the pressure. AI can increase productivity over time, but the cost of building that future can still push prices higher today. The Fed's challenge is controlling inflation without weakening the rest of the economy unnecessarily.

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