How Much Does AI App Development Cost?
Artificial Intelligence is increasingly becoming an irreplaceable part of mobile applications, software and CRM systems across different types. Payroll is a significant item in a company's budget, as it ranges from 20-30 to 60% of costs, making up 40% on average. Implementing AI algorithms in technological processes means abandoning low-skilled and mid-level employees, reducing labor costs and progressively increasing profits. Let's take a look at examples showing how the introduction and adaptation of AI into business process structure proves effectiveness and how much does it cost to develop an AI application.
This solution is useful for engineers and designers, builders and analysts. Just sketch a drawing by hand and supplement it with textual clarifications, and the software will produce a ready-made chart, diagram or plan with clear lines and dimensions in a matter of seconds. Simple code written in Python and embedded in AI services provides a clear reproduction of a given linear format. In order to solve complex problems, import modules and packages, download and compile distributions, and install other libraries.
Jupyter project has such options for implementing and developing AI algorithms: web environment, application for calculating analytics and digital data, simplified version of static pages, widgets and dashboards with multilateral interaction. One or more elements of the functionality can be used depending on what the developers' task is, adapting the AI to the requests.
Labelme is an example of a classic graphical application created on the open-source LabelMe platform developed by Massachusetts-based specialists in 2008. Segmentation and classification, customizable UI-format guarantee convenient manual markup work online or offline. Qt is the graphical tool of its interface.
Face recognition in real time using the Deepface library, created in Python, provides human identification with an accuracy of 98-99%. Likewise, AI models based on it identify a person's age and emotions, gender, instantly comparing with hundreds of images. The library is the extract of tested model solutions like VGG-Face and OpenFace, ArcFace with Dlib, GhostFaceNet and others, performing recognition tasks as a detector within 5 seconds. This is important for security in places with high concentration and passability of people - airports, stations, shopping centers.
Such solutions are more often developed on closed code to ensure the security of users and owners. Testing and writing prompts is the basis, the “heart” of the idea. The Mistral 7B model in the Apache 2.0 public license is among the best available today. The right model can be selected, developed and launched only by an experienced team of specialists who will assess the scope of tasks, availability of resources and facilities, and the utilized programming language.
Multitask decoding is based on the interaction of multiple target variables and detected regression relationships, data evaluation on a loss scale and their subsequent balancing to achieve the desired effect. These are high-level tasks, so the cost of developing such cross-platform AI applications starts from $100-150 thousand. The training duration of several models on a complex multifactor architecture with the introduction of algorithmic reasoning ranges from 300 to 500 thousand hours, which explains the high cost of such projects.
Expanding the range of language model usage is clearly illustrated by Gemma (a Gemini API product), which runs in 2B and 7B tests. The Keras 3.0 library embedded in the model is responsible for compatibility with JAX and PyTorch frameworks, open training library TensorFlow, preserving high operation performance and flexibility of the proposed solutions. Extending the existing functionality to meet business requirements is supported by interpolation of variables, interpreter parameter customization, unit testing and debugging with profiling.
However, the technical and software capabilities of the platform are enough to generate a business card site, a personal brand page with a portfolio, a simple online shoe store with a small number of positions. Such a platform can also be developed for other purposes - for example, for AI-modeling of the building and house interiors, road design, life support complexes and food production. The first three sites on Wegic are free - 120 credits are given. When they run out, payment for low-cost plans starts at $10 per month. Once a site is created, the platform publishes it online after a short time.
The given information confirms the fact that the solutions of OpenAI and other developments in the field of neural networks are gaining momentum. Immediate analysis of customer data, segmentation of requests and financial assets, maintaining personal contact based on previous transactions - a small list of AI capabilities that are worth implementing in a business project to increase profitability.
Database will remember that a specific person ordered an unmanned cab with a child seat. The next time the application with built-in AI will specify whether a car seat is needed. A laptop buyer in a year or two will be offered to upgrade to a new model that is better and more powerful than the previous version. The AI will send a favorable offer with a basket of the preferred set if it is known that during certain periods of the year people buy only fish and seafood, refusing meat, eggs and milk.
Here is an example: a woman can talk on the phone with a wireless device, fry steaks and pour yogurt for her child at the same time, switching then to other matters. Nowadays, a neural network generates and executes up to a dozen algorithms of actions in parallel. But we need control and well-defined prohibition protocols, because in order to achieve above-threshold efficiency and energy saving, the AI might allow dangerous actions.
Presumably, to calculate that a drone car will travel faster on three wheels. It may be considered that unfamiliar relatives who came to visit during the absence of the owners are burglars, so it is necessary to block windows and doors and call the guard. For this purpose, you need a control with the indication of absolute prohibition to perform certain operations.
AI-modified texture will be useful for furniture and fabric manufacturers, porcelain manufacturers, and other manufacturers where it is necessary to adjust the color scheme. The method embodies an indispensable “magic wand” for graphic design, exterior and interior building design. Suppose the customer wants to finish the living room and bedroom in the style of rococo or baroque, classicism or luxury. Choose the right elements and the AI application generates them anew in the right palette, instantly presenting a number of prototypes.
These functions are also suitable for creating games, design, visual support of the project, so they can be considered a component of society with increasing importance. The analog of the closed DALL-E is CLIP, the functionality of which has been cut by half in a comparison with the original. An extension of the two neural networks is the adversarial VQGAN, which works in an adversarial generation format where the generator and discriminator compete. VQGAN and CLIP interact perfectly, as the former generates the image and the latter as a ranker analyzes the relevance to the task.
The greatest cost of training neural networks is in data collection and subsequent AI development. In order to produce high resolution pictures, the quantized encoder and decoder are taught to reconstruct patterns based on semantics. It requires a codebook and vector quantization with distribution. A problem exists in the limited volume of convolutional layers and transformer architecture considering quadratic scalability. That is why moving away from pixels to code words with index sequences, using Colab service is a way out of the resource scarcity problem.
Trillium, the 6th generation TPU that Google will be releasing on a mass scale soon, combined with optical switches, stands ready to train AI models of low to medium complexity. Trillium is 5 times faster than the previous version, contains 256 working chips in a single unit. TPU is capable of utilizing 4096 chips in a Multislice-functioning cluster. There are hundreds of “pods” in the cluster itself.
If we take into account that the average annual salary of an employee in the US and developed EU countries is $50-60 thousand, and the development of an AI application will replace one to three to five people, the economic benefits are obvious. Neuron model training, creation and implementation of AI-application in CRM of medium complexity level will pay for itself in 3-12 months. Development of the data feed structure, algorithms for engaging updated modules and analyzing relational bases require the usage of parallel programming and sockets, testing operations during the launch process, so the order price may be higher.
Self-Discover is based on the principle of self-consistency and paradoxical reasoning, when an AI model creates a logically correct algorithm on the basis of the involved stack. Universal reasoning goes through the stages of selecting a way to solve the problem, adapting it to specific conditions and direct execution. The environment is suitable for solving complex tests, reasoning structures are implemented and transferred to different LLMs.
Training AI models to produce 1080p pictures and drawings is indispensable for businesses that produce high-quality and realistic photos and videos or for the development of AR applications. This method is also important for SLAM in situations where robotic mapping and navigation are used, based on sensor observations and odometry. In practice, it is implemented in AI training processes for safe movement of unmanned vehicles, underwater and flying devices such as drones, visualization of body organs during medical examinations.
An add-on for selecting catchy moments from podcasts, videos, conferences has recently been written in Python, so that the software interacts with CrewAI and version 4 of GPT-o (the latter AI service needs a key). The application adds subtitles to the new video after cutting the frames according to the algorithm laid down. Reducing and smartly extracting key points of information decreases the time to analyze the volume: this is the principle “Don't make the client think too much”.
Language model learning offers a wide field for website and graphic design businessmen performing multimodal generation. The developed AI applications are based on Gaussian principle and self-recognition method. AI assistants help with the training of AI models. The most important thing is a precise statement of protocols and algorithms: complexity determines the price of AI application development, not exceeding the price threshold of $150,000.
