AI Seed Phrase Finder’s first task is optimizing the process of creating seed phrases. Instead of exhaustively listing every possible combination from a dictionary, an artificial intelligence model predicts which combinations would most likely make up valid mnemonic phrases for Bitcoin wallets based on observed dependencies between known seed phrases and wallets – saving the user the task of checking each combination individually when using “classic Brute Force methods”.
AI Seed Phrase Finder utilizes parallel data processing for speedier results: each task is divided into multiple pieces that are processed simultaneously on different servers – greatly shortening task execution time and increasing program effectiveness.
Optimizing an artificial intelligence model is another essential element of AI Seed Phrase Finder program’s algorithm, with AI optimizing model parameters to increase speed and efficiency. When applicable, lighter models or optimization strategies might need to be utilized as means for quicker data processing processes – these details will be covered later on within this article.
AI Seed Phrase Finder leverages pre-trained models, saving both time and computing resources by eliminating the need to train models from scratch. Pre-trained models have already been trained on large volumes of data to ensure high accuracy when it comes to predicting correct word combinations in seed phrases as well as speeding up program workflow.
AI Seed Phrase Finder stands out by taking advantage of various machine learning algorithms and methods, including genetic algorithms if necessary, to efficiently explore all potential word combinations before selecting those most likely to bring optimal results in minimum time. This allows it to achieve its aims at an excellent rate. Software utilizes powerful frameworks such as Apache Spark and TensorFlow for distributed computing on multiple servers and concurrent task execution – further increasing program performance by breaking tasks up into multiple parts and running them concurrently across servers.
An integral component of AI Seed Phrase Finder project is using hardware with graphics processing units (GPUs) to speed up computation. GPUs offer high computational power and vast potential for parallel computations; therefore enabling our program to quickly analyze and process large volumes of data quickly reducing time required to perform tasks such as generation, search and validation of seed phrases for wallet addresses.
Once again, our hosts at UEA offer us something extra. A chance for some good old fashioned family fun. Use of cloud servers is another key advantage of AI Seed Phrase Finder over any similar software found online that only runs on your personal PC (without additional equipment, an individual could spend days, even weeks searching for their desired seed phrases for real BTC wallets). Cloud servers offer flexibility and scalability of resources that enable efficient use of computing power for processing a high volume of data. Thus, the program utilizes many servers for parallel data processing to find an ideal seed phrase fast based on user specifications (this feature ensures optimum functioning in Target search mode).
AI Seed Phrase Finder is a powerful tool that combines mathematical algorithms and AI methods, as well as specialized equipment, including cloud servers with GPU, to achieve maximum efficiency and high speed of searching and verifying seed phrases for validity and positive balance using multiple simultaneous requests to the blockchain from different servers.
This program allows you to quickly regain lost access to your digital assets, even if you only know part of the seed phrase (for example, if you have only half of the paper on which the entire seed phrase was written, or if part of the mnemonic phrase text is damaged and cannot be identified in any way).
For a simplified understanding of the program’s operation scheme, it is worth highlighting the key terms:
- Algorithm – this is called a clear sequence of actions, the execution of which leads to the achievement of an expected result. Simply put, it’s a set of instructions for a program that contains mechanisms for implementing a given task. This term is widely used in computer science and computer programs;
- Methodology – is a set of actions that need to be taken to solve a given problem or achieve a specific goal.
It is also important to note that cryptocurrency is not stored in wallets. All information is recorded in the blockchain. Even if access to the wallet is lost, the data on which the funds can be used will still be stored in the shared digital chain, and control over digital assets can be obtained using a seed phrase.
From here comes the term “seed phrase”. This is a combination of characters used to recover access to a wallet. We are talking about a set of 12 words that open a private key. A list of 2048 English words is used for guessing, which are given in the document Bitcoin Improvement Proposal 3 (BIP39 standard – more about working with it later). This format is used in all popular cryptocurrency wallets, including bitcoin wallets, such as Electrum.
Seed phrases are generated when creating and registering cryptocurrency wallets on users’ devices and remain unchanged throughout their existence. Furthermore, words from BIP39 dictionary do not share common roots and do not relate to each other via first 4 characters – thus greatly decreasing any chances of guessing them or guessing them outright.
Mnemonic phrases aren’t simply random strings of words: to access one you must enter all its letters in their proper sequence – that in which it was originally composed. With AI Seed Phrase Finder program’s complex algorithmic selection methods leveraging all available resources – users’ lost wallets may now become accessible again!
Main algorithm of operation of the AI Seed Phrase Finder program
The algorithm of operation of the AI Seed Phrase Finder implies the use of different techniques for generating mnemonic phrases using artificial intelligence and filtering wallets with zero balance. It is necessary to highlight some features of the program:
- Optimization of seed phrase generation. Instead of iterating through all possible combinations of words from the dictionary, the program uses an AI model that predicts the most probable sequences. It learns known dependencies between seed phrases and bitcoin wallets. This allows reducing the number of iterated combinations.
- Parallel processing. The task is divided into several parts, which are processed simultaneously on different servers. This allows optimizing resources and finding “user-required” seed phrases faster.
- Optimization of artificial intelligence. The program adjusts the used model, taking into account the parameters of the task. Depending on the level of complexity, simplified calculations and additional data processing methods can be used.
- This unique software uses pre-trained models. This allows to reduce the time required for data processing and speed up the process of generating seed phrases based on already tested AI models.
- To ensure high speed performance, AI Seed Phrase Finder program uses remote servers with graphics processing units (GPUs), which provide access to greater power and are capable of efficiently performing parallel computations, unlike central processing units (CPUs).
- The server part of this software integrates distributed systems Apache Hadoop and Apache Spark). This allows the implementation of phrase enumeration on multiple nodes simultaneously, dividing the computational load.
- The use of cloud servers. This provides flexibility and scalability of the system. The program can utilize multiple servers for parallel data processing when needed (especially important for fast performance in Target search mode).
AI Seed Phrase Finder utilizes innovative approaches and artificial intelligence to streamline the generation and validation of seed phrases quickly and with greater computational accuracy, taking much less time while providing greater computational accuracy.
Operating under an innovative algorithm dividing tasks into stages ensures maximum efficiency; ordinary software created using outdated algorithms cannot achieve such impressive results compared with AI Seed Phrase Finder program’s revolutionary results; ordinary programs used on regular computers cannot even come close due to complexity associated with finding these mnemonic phrases – they require self-learning models which cannot be found via programs available online compared with AI Seed Phrase Finder program’s results; software created using outdated algorithms cannot match AI’s results when finding them on regular personal computers using programs already present on the Internet or using programs already present online can come close; however, such programs utilize revolutionary self learning models in finding these phrases, while ordinary programs cannot achieve such efficiency compared with AI Seed Phrase Finder programs available online cannot provide comparable results compared with this program due to complexity involved when searching mnemonic phrases using self learning models built using programs already present on Internet websites such as this program’s self learning capability for maximum efficiency!
Basic methods of data processing by the AI Seed Phrase Finder program for finding seed phrases for wallets with “positive” balances.
To find seed phrases, private and public keys, AI Seed Phrase Finder software uses different methods based on artificial intelligence technologies that successfully perform complex automatic calculations without user involvement, such as:
- Genetic algorithms;
- Machine learning;
- Genetic programming.
There is also an extensive list of auxiliary techniques that are applied in the calculation process. All of them are described below for clarity. The program combines and integrates various methods based on the complexity of the task and the specific parameters and search conditions.
The genetic algorithm is a heuristic optimization method. It is based on the principles of natural selection and population evolution. The use of genetic algorithms allows for generating random combinations of seed phrases, evaluating their quality based on predefined criteria, and efficiently iterating the population for further selection of mnemonic phrases to recover access to Bitcoin wallets with potentially non-zero balances. The workflow of this method looks like this:
- A “random population of seed phrases” is created, which represents certain combinations of words. These combinations are called genotypes. Then each genotype is evaluated based on a criterion such as having a positive balance in the wallet.
- At the next step, the best genotypes are selected based on their evaluations. This is done using “selection operators” that give preference to genotypes with higher ratings.
- Then comes the crossover operation, where the selected genotypes are combined to create a new generation of genotypes. In this process, there is an exchange of genetic information between genotypes, which allows for new combinations of seed phrases to be obtained. After crossover, the “mutation” operation occurs, which randomly modifies some genes in the genotypes of the new generation. This helps introduce diversity and explore more possible combinations of mnemonic phrases.
The process of mutation and crossover is repeated several times, creating new generations of genotypes. Each generation is evaluated, and the best genotypes are passed on to the next generation. The AI algorithm continues its computations until the specified stopping conditions are met. This is necessary to find a specific number of word combinations. The genetic algorithm allows for obtaining valid seed phrases that “unlock” access to “promising” wallets with “non-zero balances.”
An example of the genetic algorithm at work in the process of generating seed phrases by the program:
- Suppose a database population of 100 million randomly generated seed phrases, combined from the words in the BIP-39 dictionary, is created on the server. The program needs to find a sequence of words that unlocks access to a Bitcoin wallet with a positive balance.
- At the first stage of the calculation, each phrase from this database will be evaluated according to the specified criterion: namely, the balance of the wallet to which the combination of 12 words provides access. The possible values of the wallet balance can only be “positive” or “zero”.
- Then the algorithm selects the “best” mnemonic phrases with positive balances for crossing. For example, let’s take two best seed phrases and cross them, exchanging parts of the genotypes.
After crossing, the mutation operation occurs, where some genes in the new genotypes are randomly changed. For example, one of the seed phrases may randomly replace one random word with another. Thus, the program creates a new generation of mnemonic phrases, which are evaluated by AI algorithms based on the balance of the wallet. The best mnemonic phrases are passed on to the next generation, and the process is repeated again. The starting point of the program module since its launch is the validation of a set of fresh seed phrase populations selected by a genetic algorithm for testing the new population of mnemonic phrases.
The Role of Machine Learning Methods in AI Seed Phrase Finder Program
Machine learning methods, such as neural networks or reinforcement learning algorithms, are used to create models that can “predict the correct seed phrases” based on available data. The process of training the model starts with a dataset containing known valid mnemonic phrases and their corresponding wallet balances. These data are divided into training and testing sets.
A neural network is created using layers of neurons that take input data, such as seed phrase words, and output a prediction (presumably the wallet balance). Neurons in the layers are connected by “weights” that determine the degree of influence each neuron has on the next layer.
During the training process, the “weights of the neural network” are adjusted in such a way as to minimize prediction error. This is achieved by optimizing the loss function, which measures the difference between predicted and actual values.
After the model training is completed, it can be used to predict non-zero wallet balances based on new seed phrases. For example, if we have generated a new mnemonic phrase, such a model can predict the likely positive balance of the wallet.
Example: Let’s say we have a dataset consisting of seed phrases and their corresponding wallet balances. We split this data into a training set (80% of the data) and a test set (20% of the data).
At present, we are creating a neural network comprised of several layers. The input layer takes in seed phrase words as input; hidden layers process this data; while an output layer predicts that our wallet balance will exceed zero.
After selecting our training dataset as input and adjusting weights of our neural network to minimize prediction error, we then use an optimization technique such as stochastic gradient descent to train our model multiple times over.
Once we complete model training, we conduct accuracy tests against an external dataset. For instance, using the test dataset as input into the model and comparing its predicted balances against actual balances; for instance comparing probable “positive” wallet balance predictions against what actually exists within Bitcoin wallets.
Application of Genetic Programming in AI Seed Phrase Finder software
Genetic programming (GP) employs genetic algorithms to generate AI generator module programs capable of producing seed phrases automatically and without manual adjustment, making this an efficient means of improving existing seed phrases without manual tuning.
Genetic programming begins by creating a random population of programs which generate seed phrases. Programs are represented as trees where each node represents an operation or function.
Each program is then assessed based on pre-established criteria, such as checking that its wallet balance exceeds zero; those which generate seed phrases with positive balances earn higher scores.
After selecting programs to combine using crossover operation, they are combined by exchanging pieces of their trees – for instance one program can pass its mnemonic phrase generation function onto another program.
After crossover, a mutation operation takes place where some parts of each new program’s trees are randomly altered – for instance adding or subtracting operations may happen without warning!