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These top 10 cryptocurrencies have the foundation for lasting success even in the bearish trend

In the last few months, Bitcoin and several best cryptocurrencies have been in a bearish trend. The price of many cryptocurrencies experienced a rapid decline following the crash of Bitcoin. Cryptocurrencies, as an asset class, are highly volatile. They are well-packed to look through, but the boatload of extreme volatility still resists many crypto investors to gain the benefits of investing in the best cryptocurrencies like Bitcoin and Ethereum. This article features the top 10 cryptocurrencies to buy in the bearish trend.

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Bitcoin

Similar to any speculative investment, buying Bitcoin obviously carries risk. Since its inception, Bitcoin was the 1st digital asset to beget the current ecosystem of cryptocurrencies. Even after its roller-coaster journey and entering into a bearish mode, crypto investors and analysts are highly astounding to realize the true potential of BTC. Therefore, Bitcoin is one of the best cryptocurrencies to buy in the bearish trend.

Ethereum

Ethereum is a cryptocurrency built on the principles of decentralized finance because the products and services that live on Ethereum are available to anyone who can access the internet. It is a decentralized open-source blockchain system that works as a network platform for numerous other cryptocurrencies and executes decentralized smart contracts. Many crypto investors are eagerly waiting for the Eth 2.0 upgrade that is expected to be faster and more efficient.

Cardano

Cardano is a proof-of-stake blockchain platform that focuses on ensuring that the owners can participate in the operation of the network. The fact that Cardano is more energy-efficient and superior when it comes to facilitating DeFi transactions and smart contracts makes it one of the most useful cryptocurrencies, and an attractive option for crypto investors who want exposure to cryptocurrencies that haven’t run up to exorbitant prices. Cardano is one of the best cryptocurrencies to buy in the bearish trend.

Polkadot

Polkadot is one of the most exciting projects to emerge in the cryptocurrency market. Polkadot is gaining interest from investors because it is more interactive. Developers can link blockchains to the Polkadot system and even create entirely new blockchains. It is one of the best cryptocurrencies to buy today and hold forever.

Terra

Terra is a blockchain protocol that uses fiat-pegged stablecoins to power price-stable global payments. The network offers competitive programmable payments, logistics, and an infrastructure that focuses on simplifying the use of decentralized apps, and stablecoin development. Furthermore, Terra highly focuses on interoperability. The network is designed to run on multiple chains.

XRP

XRP or Ripple is an open-source cryptocurrency that uses an open-source distributed ledger. The two biggest advantages of XRP are the speed and low cost of every transaction. A standard transaction on Ripple costs 0.00001 XRP. That’s a small fraction of a penny at the current XRP price of under US$1. The average transaction time is five seconds.

Chainlink

LINK is a blockchain abstraction layer that enables universally connected smart contracts. Not only does it present the ideal combination of a project with the right technology behind it, but it also has enough resources for further development. The best part: Chainlink possesses an excellent community. Therefore, many crypto investors prefer Chainlink over other cryptocurrencies.

Floki Inu

Since its inception, Floki Inu has shown consistent performance. As of December 2021, the market cap stands at US$1.06 billion. This is pretty impressive for a cryptocurrency that hasn’t even been around for a full year. If you are new to this crypto world and do not want to take high risk then Floki Inu is a cryptocurrency built for you.

Dogecoin

Dogecoin is one of the most popular tokens, even if it was started as a joke. It gives crypto investors an easy way to make their first foray into cryptocurrency and learn about volatility. Given the speculative nature of cryptocurrency, popularity alone is critical. As for a valuation, Dogecoin is worth what it’s worth because others believe the token will increase in value. Those investing in DOGE also are banking on more headlines from celebrity hype.

Aave

In my last post, we saw how AI breaks down language into tokens, so basically turning words into a set of numbers. But here´s the problem: To a computer, the number for “dog” and the number for “cat” are just two different integers. It has no idea that they are both pets or why they should be connected to each other. To solve this issue, we use vector embeddings which allow the AI to understand semantic similarity.

Are you confused? That´s okay, I was to. Let´s start with the basics. What exactly is an embedding? At its simplest, an embedding is a dense list of numbers, so a vector, that can represent unstructured data like text or images. Compared to just tokens, it carries the meaning of the data. So, when two words have a similar meaning, their vectors in this high-dimensional space are mathematically close to each other. As an example, the vector of “dog” will be closer to the vector of “cat” than it will be to the vector of “airplane” because dog and cat are both pets and therefore closer related.

Very cool, right? However, it wasn´t always like this. Before we had modern embeddings, we used a method called TF-IDF which stands for “term frequency- inverse document frequency”. It counted only how often a word appeared which made it great for basic searches, but it disregarded grammar and order completely. Then, with Word2Vec, there was a major breakthrough. The philosophy was: “You shall know a word by the company it keeps.” So it learned word relationships looking at their neighbors in a sentence which allowed the model to actually learn meaning for the first time.

Now that we have embeddings, we can actually perform math on them! This is called semantic arithmetic. Because vectors capture relationships, researchers found that if you for example take the vector for “King” and subtract “Man” and then add “Woman”, the resulting vector will be…you guessed it: “Queen”. This really proves that we are so far that the model does not just memorize words, but it really understands concepts like gender and royalty as mathematical directions.

This works because AI embeddings have so many dimensions, and every dimension combined allows the AI to create those unique mathematical signatures for every concept. Why does it matter, you might ask? Embeddings are the foundation of everything we do with AI today. They are the hidden underlying power of recommendation systems, like when amazon.com again suggests you a great new product? Yeah, that´s based on embeddings. Also, they are used for many more topics like image recognition or fraud detection. Most importantly, they are the first step in the retrieval-augmented generation pipeline. Without embeddings, the AI could not search through a company´s SharePoint to find the right answer because it would not know which chunks of text are relevant to the actual user question.