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Understanding Ledger’s Secure Screen and Why It’s Important
August 30, 2024
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KEY TAKEAWAYS:
— The screen of the device you use for crypto transactions is a potential attack vector.

Screens rely on the security of the computer chip that controls them, and not all chips or devices are built with security in mind.

—Ledger devices use a secure screen that connects directly to the Secure Element chip, meaning that what you see is what you sign.

Blockchain transactions, once processed, are immutable and irreversible. If you want to sign a transaction, you want to know the outcome before you steam ahead. If you make a mistake, your funds could be gone forever. While some lost funds can be attributed to copying down addresses carelessly or inputting incorrect information, they are often the result of hacking.

A common attack vector is the screen of your device. Without a secure screen, a malicious transaction wouldn’t look nefarious at all. That’s because screens we use for everyday work, study, and entertainment aren’t designed for security, they are built for performance. And when it comes to protecting and managing digital assets, these devices fall short.

Simply, you can’t trust the screen on your laptop or smartphone. But how can we mitigate this risk? 

The answer lies in a secure screen that guarantees the legitimacy of the information it shows. That’s exactly why Ledger devices have a secure screen driven directly by the Secure Element chip. It’s designed with security in mind, ensuring that what you see is what you sign

But what is a secure screen and why is it so important? Let’s dive in.

The Screen of Your Laptop or Smartphone Can’t Be Trusted

Behind every screen is a chip. That chip is responsible for the information the screen shows. For your laptop or smartphone to work, the screen must be able to access information from the chip. The type of chip it uses and how it communicates with the screen is integral to the security of any device. 

The problem arises with trusting the details of a transaction on a device connected to the internet. When you use a crypto wallet on your laptop or smartphone, you rely solely on the security of that device. Since they typically connect to the internet they are vulnerable to online threats.

Once exploited, hackers can change details on the screen of an infected device—even remotely. For example, if you were trying to initiate a crypto transaction on your laptop, a hacker could change transaction details on its screen, such as the recipient address or the total number of assets you want to send. Essentially, you can’t sign any transaction on an internet-connected device without risking your assets. 

This is exactly why hardware wallets exist: they keep your private keys stored in a chip isolated from the internet-connected device and any potential malware it hosts. By storing your private keys in a chip in a separate device that doesn’t connect to the internet, they are immune to online threats.

Some Hardware Wallet Screens Are More Secure Than Others

At this point, you might think that using any hardware wallet is enough. After all, the chip that controls the screen is completely separate from the internet-connected device initiating the transaction. That must be safe, right? 

Unfortunately, it’s not as simple as it seems. Any screen is a potential attack vector, and not all hardware wallets have the same level of security. It’s not just about keeping the chip containing private keys separate from internet connectivity, you also have to ensure that all of the device’s components are protected from physical hacks. 

Typically, hardware wallets use MCU chips to control their screens, and this is where the issue lies. It’s reasonably easy and inexpensive for a hacker to replace the firmware of an MCU chip. If a hacker gains access to the MCU that controls your hardware wallet’s screen, they wouldn’t need to gain access to your private keys. Simply with access to your screen, a hacker can tamper with the details of a transaction to trick you into signing away your assets.

To mitigate this risk, some hardware wallet providers have opted to remove the feature of a screen entirely. But without a screen, how can you know a transaction is legitimate? The answer is, you can’t. 

Luckily, the Ledger security model offers a different and more practical answer: a secure screen. But how does this work exactly? 

Understanding Ledger’s Secure Screen

The security of a Ledger device’s secure screen starts with its internal components. Ledger devices store private keys on a Secure Element chip, an industry-leading computer chip often used in bank cards and passports since it can withstand common attack vectors like side-channel attacks and glitching. 

Today, several hardware wallet providers use a Secure Element to generate and store private keys, but they typically drive their screens with MCU chips, which are vulnerable to physical hacking. Ledger devices are unique for using the Secure Element to drive their secure screens. Since the Secure Element chip drives the secure screen directly, no hacker can intercept this information or tamper with the transaction details it shows. 

The screen benefits from the Secure Element’s ability to withstand attacks, meaning “what you see is what you sign”. If the details on the screen of your Ledger device match what you see in Ledger Live, you can sign with confidence. This allows you to double-check the accuracy of your internet-connected device too. If the details on your Ledger device don’t match those on your internet-connected device, your laptop or smartphone is likely infected with malware. 

Finally, driving a screen with the Secure  Element also introduces the ability to carry out cryptographic attestations; allowing you to verify your Ledger device is running the genuine BOLOS operating system. These are just a few ways a secure screen makes interacting with the blockchain more secure and intuitive. 

What Does The Secure Screen Protect Me From

So now you know why having a secure screen is important, but what about the work it’s doing? Let’s dive into some of the most common attacks the screen of your device may face and how Ledger’s secure screen approaches them.

Address Poisoning

Ledger’s secure screen protects you from address poisoning. To explain, address poisoning is when an attacker sends you a small amount of crypto to appear in your transaction history. The transaction is designed to look like you initiated it, for example, the attacker will use an address with only a few characters different from your own. The scammer simply hopes you mistakenly copy their address from your transaction history, confusing their address for one you are familiar with.

This incredibly common scam catches out even the most experienced crypto users. However, with Ledger’s secure screen, you don’t have to worry about address poisoning: you can see the full details of a transaction, including the entire wallet address directly on your Ledger device. 

Address Switcher Malware

Another way scammers may attack your screen is through address switcher malware. With this scam, the attacker takes control of your computer or smartphone’s clipboard. With access to your clipboard, a hacker can use your own transactions against you.

For example, say you were trying to send funds to a friend, when initiating the transaction, the scammer copies their address onto your clipboard. When you sign the transaction, the funds end up in the hacker’s account instead of your friend’s. They can also replicate this attack when you plan to receive funds from a friend. The attacker replaces your address with their own, and when you share the address with your friend, the funds end up in the hacker’s account.

Ledger’s secure screen is controlled by a Secure Element chip, completely separate from your internet-connected device. Your Ledger device’s secure screen will always show the correct transaction details, even if your internet-connected device is compromised

Clickjacking Malware

Finally, hackers will attempt to trick you into revealing potentially sensitive information or unknowingly consent to malicious actions via clickjacking. This attack uses your clicks against you, modifying your device’s screen to convince you to hand over your login credentials, download more malware, or sign malicious transactions or smart contract approvals. 

 In these cases, a bad actor may take control of your screen to convince you to sign away your assets. All they need to do is make the approval look legitimate, i.e. from a familiar app you use, and your assets are theirs. 

Ledger’s secure screen cannot be targeted with clickjacking malware, as the Secure Element is tamper-proof and drives the secure screen directly.

All you need to do to protect yourself is double-check that the receiving address on your Ledger device’s secure screen matches the one on your internet-connected device before signing any transaction. Your Ledger device will handle the rest!

A Secure Screen: Just One Piece of Ledger’s Security Model

In conclusion, it’s clear that a secure screen is one of the most important aspects of managing crypto transactions. Without a secure screen, you don’t know what you’re signing. Remember, using a screen with vulnerabilities to send transactions could end in losing your funds. In the very worst-case scenario, you could lose everything by sending your assets to a spoofed address. 

No matter how big or small your portfolio is, understanding the results of signing a transaction is paramount. But a secure screen is just one piece of Ledger’s security model. So don’t stop here! Check out the full article on Ledger’s Security model to learn more about the different aspects of the Ledger ecosystem keeping you, your assets, and your devices safe.

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🤖Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?🤖
The race to build the future of robotics is no longer just about robots. It's about who controls the intelligence behind them.
 
Over the last three years, a small group of companies has emerged as the backbone of the AI revolution. Microsoft provides cloud infrastructure. NVIDIA supplies the chips. Google, OpenAI, Anthropic, Meta, and others develop the models. Together, they control much of the compute, data, and software stack powering modern AI.
 
Now that AI is moving into the physical world, many are asking a bigger question:
 
Will these same companies end up controlling robotics too?
 
It's a valid concern.
 
The latest generation of robots relies on enormous amounts of compute, simulation, training data, and foundation models. Many robotics startups today are built on infrastructure provided by large technology companies. NVIDIA's Omniverse is becoming a key simulation environment for robot training. Microsoft Azure is powering the training of robotics foundation models. Physical AI startups increasingly depend on hyperscale cloud infrastructure to train and deploy intelligent systems. Recent partnerships across the industry show just how central Big Tech has become to robotics development.
But while Big Tech is building the highways, another movement is trying to ensure it doesn't own every destination.
 
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The idea behind decentralized AI is simple. Instead of a handful of companies owning the models, compute infrastructure, data pipelines, and intelligence networks, these resources are distributed across thousands of participants.
 
This means anyone can contribute compute, contribute models, validate outputs and can participate.
The most visible example today is the decentralized AI network known as Bittensor (@bittensor). The network has evolved into a large ecosystem of specialized AI markets called subnets, where participants compete to provide useful machine intelligence and are rewarded based on performance. Rather than relying on a single company, intelligence is generated and validated by a distributed network of miners and validators.
 
Think of it as an attempt to build an open marketplace for AI instead of a world where intelligence is rented from a few centralized providers.
 
Why This Matters for Robotics
 
Robotics has a unique problem. Unlike chatbots, robots operate in the physical world. They need to perceive environments, make decisions, move safely and they need to learn continuously.
 
The challenge is that collecting and training on real-world robotic data is incredibly expensive. That's one reason large companies have such an advantage. They can afford the compute, simulation environments, and data infrastructure needed to train robotics models at scale.
 
This is where decentralized systems become interesting.
 
Instead of one company collecting all the data and training all the models, decentralized networks could allow thousands of contributors to participate in building robotic intelligence.
 
Imagine a future where:
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  • Delivery robots contribute navigation data.
  • Factory robots contribute manipulation data.
  • Developers contribute models.
  • Validators evaluate performance.
The resulting intelligence becomes a shared network rather than a proprietary asset.
 
That vision is beginning to emerge.
 
Bittensor's Move Toward Physical AI
 
While many people associate Bittensor (@bittensor) with language models and AI services, parts of the ecosystem are increasingly exploring embodied intelligence and robotics.
 
One example is Kinitro, a subnet focused on incentivizing the training and evaluation of embodied AI systems. The goal is to create competitive environments where developers build robotic intelligence and are rewarded based on performance.
 
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Not a decentralized robot network yet.
 
But the infrastructure that could support one.
 
Beyond Bittensor: The Rise of Physical AI Networks
 
Bittensor isn't alone.
 
Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
 
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If one company disappears, the network survives.
 
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Training advanced robotics models requires enormous compute budgets, sophisticated simulation environments, access to specialized hardware, and vast amounts of real-world data.
 
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Train on Azure.
 
Run foundation models from OpenAI.
 
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Navigating the world of blockchain 🧭
Navigating the world of blockchain can feel like learning a completely foreign language. Between technical jargon and fast-moving Web3 terminology, getting started can be overwhelming.

Whether you are exploring digital assets, building on-chain, or simply trying to understand decentralized technology, here is your foundational glossary of essential blockchain terms every beginner should know.

🏛️ 1. Core Architecture: The Base Layer

  • Blockchain: A distributed, immutable digital ledger that records transactions across a peer-to-peer network of computers. Once data is written to a block and added to the chain, it cannot be altered without altering all subsequent blocks.
  • Block: A collection of verified transactions grouped together. Once filled, the block is cryptographically linked to the previous one, forming a chronological "chain."
  • Node: An individual computer connected to a blockchain network that helps validate transactions, store ledger data, and maintain network consensus.
  • Consensus Mechanism: The set of rules and algorithms that network nodes use to agree on the validity of transactions.

    • Proof of Work (PoW): Requires miners to solve complex mathematical puzzles using computational power (e.g., Bitcoin).
    • Proof of Stake (PoS): Requires validators to lock up ("stake") native tokens as collateral to participate in block validation (e.g., Ethereum).

🔑 2. Ownership & Security: Wallets and Keys

  • Public Key (Address): An alphanumeric string that acts like your bank account number or email address. It is safe to share publicly so others can send you digital assets.
  • Private Key: A secret cryptographic passphrase or key that grants full access and control over your wallet assets. Never share your private key or seed phrase with anyone.
  • Seed Phrase (Recovery Phrase): A sequence of 12 to 24 random words generated when you set up a wallet. It acts as the master backup key to restore your wallet and access your funds on any device.
  • Hot Wallet vs. Cold Wallet:

    • Hot Wallet: A software-based crypto wallet connected to the internet (e.g., browser extensions, mobile apps), making it convenient for frequent transactions but higher risk.
    • Cold Wallet: An offline hardware device (e.g., Ledger, Coldcard) designed to isolate private keys from internet-connected threats.

⚙️ 3. Execution & Functionality: Smart Contracts and Apps

  • Smart Contract: Self-executing code stored on a blockchain that automatically enforces agreement terms once predetermined conditions are met—eliminating the need for intermediaries.
  • dApp (Decentralized Application): Applications built on top of a blockchain network that run via smart contracts rather than centralized cloud servers.
  • Gas Fees: Network transaction fees paid to validators or miners to cover the computational energy required to process actions on a blockchain.
  • Layer 1 vs. Layer 2:

    • Layer 1 (L1): The underlying primary blockchain network (e.g., Bitcoin, Ethereum, Solana) that handles base security and finality.
    • Layer 2 (L2): Secondary frameworks or companion networks built on top of an L1 to increase transaction speeds and lower gas fees (e.g., Arbitrum, Optimism, Base).

💰 4. Financial & Market Concepts

  • Tokenomics: The economic design, supply dynamics, utility, and distribution model of a cryptocurrency or token project.
  • DeFi (Decentralized Finance): Financial services—such as lending, borrowing, trading, and earning interest—built on smart contracts without traditional banks or financial intermediaries.
  • Liquidity: The ease with which an asset can be bought or sold in a market without significantly impacting its price.
  • DYOR (Do Your Own Research): A foundational golden rule in the Web3 space reminding users to independently verify technical code, whitepapers, and team backgrounds before making any capital commitments.

💡 Quick Cheat Sheet

"Not your keys, not your coins."

If you do not hold the private keys or seed phrase to your digital wallet, you do not truly own the assets inside it—a centralized entity or exchange does. Always prioritize security first as you explore the space.

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AI Is Coming for Your Job Title

Artificial intelligence may or may not take your job, but it has already broken into the human resources department and vandalized the org chart.

The evidence is all over LinkedIn, where perfectly serviceable occupations now arrive wearing titles such as “forward-deployed and agentic AI architect.” That person may be building sophisticated software. They may also be helping a chatbot remember what happened three prompts ago. Either way, somebody approved the business cards.

The expanding AI lexicon offers a useful counterpoint to the darker debate about technology and employment. Most discussion centers on how many jobs AI will eliminate. Hiring data presents a more complicated picture that includes a weak overall labor market containing a small but rapidly growing neighborhood of AI-related work.

Indeed Hiring Lab found that the number of postings on Indeed mentioning AI surged 134% from its February 2020 level by the end of 2025, even as total postings stood only 6% above that benchmark. AI appeared in a record 4.2% of Indeed postings in December.

AI, in other words, is not merely changing work. It is adding syllables to it.

The Titles Employers Actually Want

The undisputed champion is AI engineer, which ranked No. 1 on LinkedIn’s 2026 Jobs on the Rise list. The ranking, based on growth during the previous three years, also highlighted AI consultants and strategists, AI and machine-learning researchers and data annotators.

The title is popular partly because it is wonderfully accommodating. An AI engineer might build applications around large language models, connect corporate data to an AI system, improve model performance or spend Thursday afternoon persuading a customer service bot not to offer refunds for products the company doesn’t sell.

Indeed’s data showed the terminology spreading beyond Silicon Valley. Nearly 45% of data and analytics postings contained an AI-related term at the end of 2025, along with roughly 15% of marketing postings and 9% of human resources listings. A more recent Indeed analysis reported by Business Insider found that the number of frequently advertised job titles explicitly referencing AI rose from 264 in 2022 to 822 in the first quarter of 2026. Nearly two-thirds were outside traditional technology fields.

That produces titles such as AI marketing manager, AI learning specialist, responsible AI counsel and AI transformation lead. These are not always new occupations. Frequently, they are familiar jobs that have discovered a highly effective résumé keyword.

LinkedIn data cited by the World Economic Forum estimated that AI investment has supported 1.3 million positions, including AI engineers, data annotators and forward-deployed engineers, plus more than 600,000 AI-enabled data center jobs. The server racks, unlike the chatbots, still need electricians.

The Jobs With the Science-Fiction Salaries

At the upper end, AI has created a compensation market that resembles professional sports, except the competitors wear hoodies and discuss inference latency.

Syracuse University review put chief AI officer compensation between $200,000 and more than $500,000, while specialized roles can exceed $400,000 after bonuses and equity. Frontier research engineers, AI infrastructure specialists and engineers who can train or deploy advanced models command some of the largest packages.

Then there is the forward-deployed engineer, an old Palantir title that the AI boom has placed on a rocket sled. These engineers embed with customers, translating an executive’s desire to “do something with AI” into software that works. The Next Web reported that Indeed postings for the role were about 19 times higher in January than a year earlier.

CTO guide from the blog Signal Through the Noise placed forward-deployed engineer compensation between $238,000 and $700,000, research-engineering packages as high as $1.4 million and chief AI officer compensation above $1 million in some cases. It also made a less flattering observation: Many lavishly differentiated titles describe the same three basic functions. People build AI products, train models or keep the infrastructure from catching fire.

The Department of Unnecessary Titles

AI has created some genuinely new work. Evals engineers design tests to determine whether models perform reliably. AI red teamers try to make systems fail before customers do. Model behavior engineers study why an AI system responds as it does. AI governance leaders manage risks involving data, bias, security and regulation.

Other titles seem to have escaped from a brainstorming retreat.

There is the Claude Evangelist, whose mission apparently combines product education with the traditional duties of an apostle. There are vibe coders, who build software by describing what they want and accepting AI-generated code with varying degrees of supervision. “Vibe engineer” is the more respectable version, roughly equivalent to putting on a blazer before asking the machine to fix the login page.

“Context engineer” is a real discipline involving the data, instructions, memory and tools supplied to AI models. “Prompt engineer,” once advertised as a possible six-figure profession for gifted chatbot whisperers, is increasingly treated as one skill inside a broader AI role.

The CTO guide also identified “builder,” “AI-native developer,” “RAG engineer,” “agentic AI engineer” and “principal agentic GenAI forward-deployed context architect,” the last of which appears to require both technical proficiency and exceptional lung capacity.

Has AI created entirely new jobs? Absolutely. Some occupations, including AI safety, evaluation and model governance, exist because modern generative systems introduced new technical and business problems. However, many job titles are old jobs with fresh vocabulary, higher salary bands and a sudden aversion to the words “software developer.”

That may be the safest prediction about AI and employment. The machines will automate some tasks, generate others and force companies to rethink the division of labor. Before any of that is settled, however, corporate America will form a steering committee, appoint a chief agentic transformation evangelist and schedule a meeting to determine what that person does.

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