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DevSpeak: Artificial Intelligence

DevSpeak: Artificial Intelligence

Artificial Intelligence (AI) often sounds like something straight out of a science fiction movie—robots taking over the world or computers that think and act like humans. But the reality of AI is much different and far less scary. AI is already a significant part of our lives, helping us in ways we might not even realize.

Artificial Intelligence, Defined

At its core, Artificial Intelligence is simply the ability of a machine to perform tasks that would normally require human intelligence. These tasks can include things like understanding language, recognizing patterns and solving problems.

AI is just a tool designed to mimic certain aspects of human thinking or behavior. But it’s important to note that AI doesn’t have feelings, consciousness, or self-awareness. It’s just a set of algorithms—basically, step-by-step instructions for processing data and making decisions based on that data.

For example, when you use voice commands to ask your smartphone for the weather, AI is at work. It understands your question, searches for the information, and provides you with an answer—all in a matter of seconds. But it’s not “thinking” the way humans do; it’s following a programmed sequence of actions based on the input it receives from you… a thinking, creative human.

General vs. Narrow AI

Now that we know what AI is, it’s crucial to understand that there are two main types: General AI and Narrow AI.

It’s a little more complicated than just General and Narrow. If you want to dive deeper into the types of AI, check out this video from IBM.

Narrow AI

This is the type of AI we interact with daily. Narrow AI (often referred to as weak AI) is designed to perform a specific task or a set of related tasks. It’s very good at what it does, but it’s limited to that particular function. A facial recognition system can identify people in photos, but it can’t play chess or write a song.

These types of AI can seem deceptively intelligent, but that’s because it’s trained to be incredibly proficient at one thing. As humans, we tend to recognize someone who is really good at something as very capable. AI is not a human. Just because it’s impressively responsive as a chat bot doesn’t mean that it has real insight or understanding of anything it’s been trained on.

Search engine algorithms are a great example of this. Google seems like it knows everything about you sometimes. It places ads at the exact right time. Have you ever gotten an ad on YouTube for something that you were just thinking about but never voiced aloud? Spookily insightful, huh?

Only it’s not. Google’s algorithm has sampled terabytes of data on literally billions of people. It is excellent at seeing the patterns and knowing that if you searched for A and you purchased B, you’re likely going to think about C sometime in the next few days. This doesn’t mean it knows you, it just knows what humans are likely to do.

General AI 

This is the kind of AI you see in movies — machines that can think, learn and apply knowledge across a wide range of tasks, just like a human. However, General AI (referred to as strong AI) doesn’t exist yet. While there’s some disagreement about how long, we’re still definitely a long way from creating a machine that can do everything a human can do.

To accomplish this, we’d need to make algorithms that can do everything the human brain can. The problem with that is that we don’t really understand how our brain does its thing entirely. Even if we can simulate the number of neurons and interconnections in a human brain (a BIG task), will that equate to learning, insight and creative thinking? Is a brain just a computer or something more is a question that science hasn’t come very close to answering.

Recent studies indicate that we may be even further from General AI than we thought. Some recent evidence suggests that human reasoning may actually be using an unprecedented macroscopic quantum system throughout our bodies, giving rise to what we think of as “consciousness”. If that or anything like it is the case, we’re orders of magnitude further from general AI that can compare to human intelligence than we thought we were.

Regarding GPT: Understanding Large Language Models

Let’s take a short digression to talk about one of the most ubiquitous forms of AI out there – the Large Language Model (LLM), used in programs such as GPT (Generative Pre-trained Transformer). Since these specialize in one of the cornerstones of civilization (communication), they’re easy to overestimate or misunderstand. After all, we typically see the ability to communicate well in humans as a sign of intelligence.

Large Language Models (LLMs) are a type of AI designed to understand and generate human-like text based on the input they receive. They are trained on vast amounts of text data, allowing them to learn patterns, grammar and even some aspects of reasoning. When you ask GPT a question or give it a prompt, it analyzes the input and generates a response that seems coherent and relevant, often mimicking human language quite convincingly.

How GPT Forms Responses

When you interact with GPT, you’re essentially giving it a prompt – a piece of text that it will use as a starting point to generate a response. GPT doesn’t “think” or “understand” the way humans do. Instead, it uses the patterns it has learned during training to predict what text is likely to come next based on the input it received.

If you ask GPT to write a story about a cat, it’ll use the knowledge it has about cats, stories and language structure to craft a response. The more detailed your prompt, the more focused and accurate its response will be. It isn’t actually composing a story… it’s just giving a response that sounds like something a human may say.

Limitations of LLMs

While LLMs like GPT are incredibly powerful, they have significant limitations:

  • Lack of understanding: LLMs do not possess true understanding or consciousness. They generate text based on patterns, not on any deeper comprehension of the world. This means that while GPT can produce text that seems intelligent, it doesn’t actually “know” anything in the way humans do.
  • Dependence on training data: LLMs are only as good as the data they’ve been trained on. If the data is biased or incomplete, the model’s responses may also be biased or inaccurate. Additionally, GPT cannot create entirely new knowledge; it only recombines and reinterprets what it has already been exposed to.
  • Inability to think critically: GPT and other LLMs cannot critically evaluate or verify information. They can sometimes generate responses that are factually incorrect or nonsensical, particularly if the prompt is ambiguous or outside the model’s training scope.

You can train a parrot to respond to specific phrases with almost conversational quips… that doesn’t mean the parrot is carrying on a conversation with you. LLMs are similar to that in lots of ways. The AI is learning what responses to a prompt are likely to be appropriate based on the data it is fed. It’s complex, but it’s still just parroting the data it’s been given.

Apocalypse, Not

One of the biggest myths about AI is that it will eventually become so intelligent that it will take over the world, causing an “AI apocalypse.” This idea is more fiction than fact.

Remember, Narrow AI is designed to do specific tasks. It can’t suddenly decide to become something else. Your AI-powered vacuum cleaner isn’t going to start plotting world domination… it’s just going to keep cleaning your floors. Even if we one day develop General AI, the idea that it would turn against us is highly speculative and far from a present concern. It’s also likely that generations of sci fi writers have been assigning scary, but fundamentally human characteristics to a theoretical, inhuman system.

In reality, AI is just another tool. As people understand more of this, another alarmist point of view has become prevalent – the idea that AI will replace all of us. Again, this goes a little far. There are parts of life that AI has already made more efficient, but it’s just a tool. 

The invention of the power drill didn’t replace carpenters. Often human expertise is still required to get the best work out of these AIs. Writing from GPT will feel choppy and generic if it’s not edited by an expert. Images generated by non-artists from Midjourney often still lack the composition and cohesion that an artistic eye with experience can bring. 

You could give me (a writer) a powerful data aggregation algorithm, and I would be totally lost and would probably just waste time on it. To a data analyst, it can be a super power for tedious and mundane tasks that previously sucked their time dry. The expertise from a real human is still required to get the best work out of AI.

Human Intelligence Boosted

Hopefully this DevSpeak gives you a lot more insight into the very broad term “AI”, and how it affects your daily life. New tech and the jargon that comes with it is often confusing, but that’s why you have DevSpeak!

This one was a mouthful for sure! Thanks for sticking with us through this deep dive on an important topic. We’ll be back soon with more explainers designed to buff your understanding of the tech world!

What are Stablecoins? Web3 Concepts Explained

What are Stablecoins? Web3 Concepts Explained

Stablecoins have emerged as an important part of the web3 world, playing a crucial role in providing financial stability to a typically volatile cryptocurrency market. For those new to blockchain and crypto, stablecoins might seem like a complex concept, but they’re actually quite simple.

Think of them as a “digital version of the dollar” or other traditional currencies, designed to maintain a steady value rather than fluctuating like Bitcoin or Ethereum. In this blog, we’ll break down the concept of stablecoins, why they exist, how they work and their importance in the growing web3 world.

What Are Stablecoins?

A stablecoin is a type of cryptocurrency that is pegged to the value of a stable asset, typically fiat currencies like the US dollar or Euro. Unlike Bitcoin, which can experience dramatic price swings, stablecoins aim to stay steady. It should be noted however that no financial asset is perfectly stable, but stablecoins are comparatively stable to most cryptocurrencies.

Imagine you’re traveling to a foreign country and you exchange your money for local currency. When you return home, you expect your leftover foreign currency to hold roughly the same value. This is the idea behind stablecoins—they are designed to ensure your digital assets don’t lose value overnight, especially in the often volatile cryptocurrency world.

Why Do Stablecoins Exist?

Cryptocurrency is known for its wild price swings. Bitcoin, for example, can rise or fall by thousands of dollars in just a day. While this can be exciting for traders, it’s risky for businesses and individuals looking for stability. Enter stablecoins—designed to minimize this volatility by pegging their value to more stable assets.

Here’s why stablecoins are essential:

1. Price Stability for Transactions:

In a world where cryptocurrencies are becoming more common as payment methods, having a stable unit of currency is vital. Imagine buying a coffee for $5 worth of Bitcoin in the morning, only for that Bitcoin to lose value by the time your payment processes. With stablecoins, the value of your purchase remains consistent, making them ideal for everyday transactions. Depending on many variables (complexity, blockchain, amount), web3 transactions can take time. Vendors must rely on knowing that the price paid for a product or service is consistent with their asking price, even if the purchase takes a variable amount of time to fulfill.

2. Cross-border Transactions:

Traditional banking systems often charge high fees for international transfers and can take days to process. Stablecoins make cross-border payments faster, cheaper and easier. Since stablecoins are based on blockchain technology, you can send money across the world in minutes without worrying about the value changing dramatically during the process.

3. DeFi (Decentralized Finance) Applications:

Stablecoins have become an integral part of the decentralized finance (DeFi) ecosystem, where people can lend, borrow and trade assets without relying on traditional banks. In these systems, having a stable currency to work with makes it easier to manage risks and avoid the extreme price swings common in other cryptocurrencies.

How Do Stablecoins Work?

There are a few different types of stablecoins, each using different methods to maintain their stable value. Here are the three main types:

1. Fiat-collateralized Stablecoins:

These stablecoins are backed by actual reserves of fiat currency (like US dollars) held in a bank. For every stablecoin issued, there’s an equivalent amount of fiat currency sitting in reserve. One of the most popular examples is Tether (USDT), which is pegged 1:1 to the US dollar. So, for every USDT in circulation, there should be a dollar in reserve.

Example: If you have 100 USDT, theoretically, the company behind it holds $100 in a bank somewhere to back up your digital assets and allow your tokens to maintain their precise value.

LEARN MORE:
Fiat-Backed Stablecoins: What You Need to Know About Tether, USD Coin and Others – CoinDesk, Oct. 2022

2. Crypto-collateralized Stablecoins:

Instead of being backed by fiat money, these stablecoins are backed by other cryptocurrencies, often over-collateralized to account for the volatility of crypto. This means for every $1 of stablecoin, there might be $2 worth of cryptocurrency backing it. DAI, created by the MakerDAO platform, is a well-known example of a crypto-collateralized stablecoin.

Example: If you want to create $100 worth of DAI, you might have to lock up $200 worth of Ethereum. If the price of Ethereum falls, the system will liquidate your assets in order to keep the value stable.

LEARN MORE:
“What are crypto-backed stablecoins and how do they work?” – Nuant, July 2024

3. Algorithmic Stablecoins:

These stablecoins are not backed by any collateral. Instead, they use algorithms to control their supply, automatically increasing or decreasing the number of tokens in circulation to maintain a stable value. When the demand for the stablecoin rises, the algorithm issues more coins to bring the price down. If demand falls, the supply is reduced to increase the price back to its pegged value.

Example: TerraUSD (UST) was one of the more well-known algorithmic stablecoins before it collapsed in 2022 due to its inability to maintain its peg to the US dollar, highlighting one of the most important risks associated with this type of stablecoin.

LEARN MORE:
“A beginner’s guide on algorithmic stablecoins” – CoinTelegraph, 2023

Why Are Stablecoins Important in Web3?

Stablecoins have become indispensable in the broader Web3 ecosystem because they serve as the bedrock for many financial activities on the blockchain. Here’s why:

Liquidity and Trading

Stablecoins are often used as a medium of exchange on decentralized exchanges (DEXs). Traders use stablecoins to quickly move in and out of more volatile cryptocurrencies like Bitcoin or Ethereum without needing to cash out into traditional fiat currencies.

Decentralized Finance (DeFi)

DeFi platforms rely heavily on stablecoins. Lenders and borrowers use stablecoins as collateral, ensuring that their loans or savings won’t lose value overnight due to market volatility.

Onboarding to Crypto

Stablecoins offer a familiar value system for people new to crypto. Instead of having to understand complex pricing of volatile assets, newcomers can start by using a digital currency that mirrors traditional money.

Safety from Market Crashes

During significant market downturns, investors often convert their holdings into stablecoins to protect their portfolios. This acts like a “safe haven” during turbulent times.

Popular Examples of Stablecoins

Let’s take a look at some of the most widely used stablecoins in the cryptocurrency space:

  • Tether (USDT): The largest and most popular stablecoin, pegged to the US dollar.
  • USD Coin (USDC): A highly regulated stablecoin backed by US dollar reserves, known for its transparency.
  • DAI: A decentralized stablecoin backed by crypto assets, primarily used in DeFi applications.

Because of their proven stability, both USDT and USDC are accepted as payment methods for many products sold in the Gala ecosystems. Additionally, payments are also accepted in both GUSDT and GUSDC, the GalaChain-bridged versions of these Ethereum-based stablecoins.

Each of these stablecoins offers unique benefits depending on the use case—whether it’s transparency, decentralization, or regulatory compliance.

Stablecoins are the unsung heroes of the cryptocurrency world, bringing much-needed stability to a notoriously volatile market. They are an essential bridge between the traditional financial system and the world of Web3, facilitating everything from day-to-day transactions to more complex decentralized financial activities. Whether you’re new to blockchain or a seasoned crypto trader, stablecoins play a pivotal role in making digital assets more accessible and usable.